{"questions": {"1d8a0cfc-df53-467f-88e8-cd378990da4b": "What are the key steps to obtain input from stakeholder communities to identify unacceptable use in AI systems?", "9ec9d981-9115-4672-bd74-23035ecc2e7f": "How can organizations maintain an updated hierarchy of identified and expected GAI risks?", "0605df28-3443-4e71-b065-c5e957b1a3be": "What are some examples of unacceptable uses of AI as identified by stakeholder communities?", "bf3d5106-092b-4dcd-84c8-a6f876550060": "How do harmful bias and homogenization impact AI systems?", "84fa4ea9-be18-4dd5-9e29-a6a5c02feb54": "What is the significance of reevaluating organizational risk tolerances in the context of AI and GAI?", "bb5dcf48-cb19-47b4-b313-265f9f7cb3c8": "What are the potential risks associated with model collapse and algorithmic monoculture in GAI systems?", "bc5f183f-8819-4d54-9853-b8f799e02906": "How can organizations address issues related to obscene, degrading, and/or abusive content in AI systems?", "8d9f5ceb-fce8-4d14-9811-6140c0e69900": "What strategies can be employed to mitigate dangerous, violent, or hateful content in AI applications?", "2f174ff7-4261-4c60-a49e-51bc536fd900": "How do immature safety or risk cultures affect the design, development, and deployment of AI and GAI systems?", "1cef392e-71ff-400b-a4bb-39f4c8d78dab": "What are the public information integrity risks associated with AI and GAI, and how can they be managed?", "b2fdeb09-6112-4cbd-a860-6b770d65c9ef": "What are the short, mid, and long-term impacts of AI in cybersecurity according to De Angelo (2024)?", "50a10f19-e2b0-4f53-bf39-c09e6b2adedb": "How do chatbots and generative AI affect mental health, based on the insights from De Freitas et al (2023)?", "41d1c796-9d40-450d-bb90-58541f4dc294": "What is algorithm aversion and why do people avoid algorithms after seeing them err, as discussed by Dietvorst et al (2014)?", "8ea4ce00-241b-4a28-9f10-127da59b19a3": "How do companies learn consumer secrets according to Duhigg (2012)?", "ee13b775-a27a-4b83-b019-8da1bfe33cd4": "How can images altered to trick machine vision influence humans, as explored by Elsayed et al (2024)?", "0835eb5b-ff9b-4c95-98a1-c1aa96b695d1": "What are the key findings of the Harvard Business School study on the safety of generative AI in mental health?", "a25fa3f1-5fad-4e5f-8635-3c5d7564bc9d": "How does the New York Times article by Duhigg (2012) explain the methods companies use to track shopping habits?", "cad3f6f1-e1cf-428f-b6c0-986a72e27923": "What are the implications of the research by Google DeepMind on altered images and machine vision?", "7795698f-b343-44b2-90b7-333d3e874947": "How does the study by Dietvorst et al (2014) contribute to our understanding of human interaction with algorithms?", "0563fa4d-b516-4410-ba89-1f0315067735": "What are the potential risks and benefits of AI in cybersecurity as outlined by Palo Alto Networks?", "32e11143-ad57-48c7-b0ce-e4922c8b1cc7": "What are the different risk response options mentioned in MANAGE 13 for high-priority AI risks?", "94e3e1d2-3500-48e6-97a6-8c83517b41e0": "How should organizations document trade-offs and decision processes for AI risks that do not surpass risk tolerance?", "abb3f98f-480d-4f2d-bf70-0bb22379dbae": "What is a staged release approach in the context of model release for AI systems?", "2a61da93-9e17-4be7-862f-ff9f941284a1": "How can organizations mitigate, transfer, or avoid AI risks that surpass their risk tolerances?", "6b6dc282-ed05-4387-ae3c-28fea9f6aa32": "What methods can be used to monitor the robustness and effectiveness of AI risk controls and mitigation plans?", "a435043d-540e-4134-9d59-e921db6866dd": "What is the role of red-teaming in assessing AI risk controls?", "c64396a8-0017-4d46-aea9-58f81191f6b9": "How can participatory engagements help in monitoring AI risk mitigation plans?", "90341a67-3948-47fe-acaa-32e9896acdd5": "Why is it important to consider the projected use cases of a model when planning its release?", "a93e9f47-5572-4f65-810c-e65f0c0cbc35": "What are some examples of performance assessments for AI risk controls?", "6b14b109-2e7e-4d40-b149-1eb05bc882a0": "How can user feedback mechanisms contribute to the effectiveness of AI risk mitigation plans?", "cde52e0d-45eb-41b7-89ac-0e8e28ac0457": "What methods can be used to trace the origin and modifications of digital content?", "0d6f47cc-2f11-4d1e-9d54-90b10f6bf2b6": "How can tools designed to analyze content provenance help in detecting data anomalies?", "ed8c6ae4-9a32-44a5-b820-0681f03fd325": "What are the best practices for verifying the authenticity of digital signatures?", "cf07e760-9b9f-4be0-aaf2-9ce158ee1c98": "How can patterns associated with misinformation or manipulation be identified?", "7a9b270d-4022-4dee-8044-c221948c7d25": "Why is it important to disaggregate evaluation metrics by demographic factors?", "93f3824c-e2a6-424d-a45b-f7a6e593c5d7": "What are the potential risks of harmful bias and homogenization in AI systems?", "c0441d12-0139-47e0-a780-13868a3b0469": "How can discrepancies in content provenance mechanisms across diverse populations be identified?", "7a65af06-b620-44fe-90b4-53bdcb7c8559": "What metrics can be used to evaluate structured public feedback exercises?", "3cc7ff9c-22a7-4d2c-a02f-353ba7ef9fe1": "How should risks or trustworthiness characteristics that cannot be measured be documented?", "daf97136-c510-4453-a3f3-dfdd41c8a7eb": "What are the most significant AI risks that should be prioritized for measurement?", "4f8ef4f7-9616-44aa-abfe-8cdaf1756b90": "What are the key points of the Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence issued by the White House in 2023?", "6f46f00e-c286-4eb0-815e-32faf4967e59": "How does the 2022 Roadmap for Researchers on Priorities Related to Information Integrity Research and Development address misinformation?", "bf6d72d3-a20e-4589-8cbd-9e4fcf8ff4f9": "What were the findings of the Stanford Cyber Policy Center's investigation into AI image generation models trained on child abuse?", "1c142ec8-b4a3-456e-ba1c-a485944b6ca4": "How does the White House's 2023 Executive Order aim to ensure the ethical development of AI technologies?", "b39288aa-0a9d-4d94-82e2-35409659c7d1": "What are the main objectives outlined in the White House's 2022 Roadmap for Information Integrity Research and Development?", "21eaa61b-6208-40e7-b9a3-5a37038f9d48": "What measures are being proposed to secure AI development according to the 2023 Executive Order by the White House?", "1233bc76-0ce0-4740-bad7-5de774ca0fd7": "How does the 2022 Roadmap for Researchers contribute to combating disinformation and ensuring information integrity?", "988d7c42-6b16-42d7-8c3b-eca27423ec98": "What are the implications of the findings from the Stanford Cyber Policy Center regarding AI image generation models and child abuse?", "d0ee89a9-21ce-4521-a946-de628b905143": "How does the White House plan to address the challenges of AI safety and security as per the 2023 Executive Order?", "23394fb9-945c-4c8e-a361-a1cfd375abe0": "What steps are being taken to ensure trustworthy AI development according to the latest executive order from the White House?", "37aabec8-0539-4438-8489-8a52afbff96e": "What are the best practices for implementing real-time monitoring processes for content integrity?", "a8ce087b-ada7-4cca-8488-e90b57a28b9f": "How can machine learning models be used to flag illegal or violent content in GAI applications?", "607fa183-8c10-4e68-860f-41798c764cc8": "What are the challenges in detecting CSAM and NCII content using automated filters?", "f9c3b55d-7f98-4fca-a8b3-2276e0cf58d9": "How can rule-based filters be effectively combined with machine learning models to identify harmful content?", "f8fcd7dd-4077-4dd8-8a19-cea03ba0bda5": "What measures can be taken to ensure information integrity in generated content?", "21f56f77-f14f-4eb0-ae84-a15ddf44c478": "How can real-time monitoring help in identifying deviations from content standards?", "c1c10c23-aba8-48a1-a47f-0ea7b9ee4058": "What are the key characteristics to monitor for ensuring content trustworthiness?", "bb1d1592-7123-4163-a963-913da8006be9": "How can human intervention be effectively triggered by automated alerts in content monitoring systems?", "07ea05d4-6b90-4936-9dae-b67d0e70640d": "What are the potential biases that can arise in machine learning models used for content filtering?", "2f84ffbd-1a21-475b-a55e-ed7b70ad40b5": "How can the homogenization of content be prevented in GAI applications?", "9e4c34f4-3d3e-45f8-b44c-86725048d92b": "What are the key findings of the study \"Dissecting racial bias in an algorithm used to manage the health of populations\" by Ziad Obermeyer and colleagues?", "64f82a67-4768-4e6b-a43d-f04086818e85": "How does the Data & Trust Alliance propose to safeguard against algorithmic bias in the workforce?", "7f45b7a7-9fcf-4391-89e9-8cc77c095f2a": "What are the main IT accessibility laws and policies outlined on Section 508gov?", "78c93a0c-adfa-4c7e-a126-d47d3e13352b": "Can you summarize the 2019 Science article on racial bias in health management algorithms?", "f9d25a5e-23c8-45ee-aef2-d7db0c12b767": "What measures are recommended by the Data & Trust Alliance to ensure fairness in workforce algorithms?", "86604d73-f71a-46b4-b444-0f78f434d3a8": "How does Section 508gov help organizations comply with IT accessibility requirements?", "511742cc-dc64-43a3-a033-bd545ce33e57": "What are the implications of the findings by Obermeyer et al on racial bias in health algorithms for healthcare providers?", "04a0b08c-92b8-44bb-886c-252f86746d2c": "What is the purpose of the Algorithmic Bias Safeguards for Workforce document by the Data & Trust Alliance?", "3e71278b-e893-4a19-955e-1505554c8686": "How can organizations implement the guidelines provided by Section 508gov for IT accessibility?", "04516eef-32ce-4fcc-8b77-263ca9de6e10": "What are the potential impacts of algorithmic bias in workforce management as discussed by the Data & Trust Alliance?", "a0c0459c-054c-42ad-bffd-3e69e7a03bbc": "What are the potential impacts of automated systems on data privacy?", "b159acfb-35e3-4cbb-8158-d4d89ccc5870": "How can we ensure that automated systems do not use data inappropriately?", "391ca451-b0e7-43cc-afcc-32b7d1fa8da7": "What measures can be taken to protect against the compounded harm of data reuse in automated systems?", "b15c0ca5-79fe-4cb6-971d-891ab63966bb": "Why is independent evaluation important for the safety and effectiveness of automated systems?", "f8ed278b-212e-45c9-ae9f-5fe98bbd00fb": "What steps should be taken to mitigate potential harms of automated systems?", "c034102c-8cc6-4f9f-aa97-54c4123b05b8": "How can the results of independent evaluations of automated systems be made public?", "19a80a1d-4c42-4b4a-a9f1-8c58f96c948b": "What are the foreseeable uses of automated systems in various industries?", "84b94c19-44d8-4b0e-a9ea-21d1b4e745a9": "How can we ensure transparency in the development and deployment of automated systems?", "08b5ee06-991e-4f06-9629-71d3500295ab": "What are the best practices for reporting the safety and effectiveness of automated systems?", "4328f04f-39f0-472e-a479-26bcd1915133": "How can we protect individuals from the misuse of data by automated systems?", "03a9fe91-d78e-473a-a2f8-3106648d7314": "What are black-box credit models and why is the CFPB acting to protect the public from them?", "c5f06a48-24b4-4bf0-85f8-836e9d96099d": "What does California's AB 701 law entail for warehouse employers regarding quotas?", "2335610a-fe1a-4ccd-b194-0d8b2734a4d1": "How does the National Institute of Standards and Technology (NIST) contribute to AI explainability research?", "fe0c5f11-3d4c-44d7-8f27-6a2da2f8536e": "What is the significance of explainable artificial intelligence (XAI) according to DARPA?", "5342b516-b61d-4ea4-a2da-9a05638d3918": "How might complex algorithms in credit models impact consumer finance?", "f43fcf7f-345c-4942-b43d-e75917a9d53a": "What are the potential benefits and challenges of implementing AB 701 in California warehouses?", "4a15e20a-7144-40e1-93e3-114864d97085": "Why is explainability important in artificial intelligence research?", "32cfcd73-0b8c-4469-91c1-5f5209f15d84": "What are some examples of black-box models in the context of credit scoring?", "85538c5c-826d-45bc-8de8-297408b1897a": "How does DARPA's XAI program aim to improve the transparency of AI systems?", "08be8570-a2e0-4e56-af80-157c2427baf9": "What steps can employers take to comply with California's AB 701 law on warehouse quotas?", "24c87258-bf5b-4144-b1cf-149daa5a5c29": "What is the NIST framework for AI technologies and systems?", "1f1e3f39-8772-4eb1-b7f0-12ff89060503": "How does the NIST framework address robustness in AI systems?", "69e2d6b3-12b3-47d1-a249-65657ba34d64": "What measures does the NIST framework propose for ensuring the safety of AI technologies?", "f139859c-a3ce-4700-a971-5548dc026253": "How does the NIST framework aim to enhance the security and resilience of AI systems?", "04bebb3a-8ecf-4543-8736-671e1a4585be": "What strategies does the NIST framework suggest for mitigating unintended and harmful biases in AI?", "df7b1cdc-bb0a-43b5-a10c-7189eb63373e": "How does the NIST framework promote transparency in the development and deployment of AI technologies?", "7cb4296e-4abe-4bd0-a8ff-edaf4a243ffd": "What accountability mechanisms are included in the NIST framework for AI systems?", "12b8555f-380e-4b4a-adc7-418d59a61297": "How does the NIST framework ensure fairness during the pre-design and design phases of AI development?", "3aef7413-5f60-4e9b-a6ac-191b6972651c": "What are the key principles of the NIST framework for AI testing and evaluation?", "65303757-3ce8-4416-96eb-99d843d040d1": "When is the NIST framework for AI technologies expected to be released?", "a7a1d3dc-f420-48c3-a3cb-1e0a676e9e7b": "What are the key considerations for using AI in sensitive domains like criminal justice and health?", "24566fed-3d75-47f8-80b2-03f3d0e9e7d3": "How can meaningful access for oversight be ensured in AI systems used in employment and education?", "1cc3e51d-3cba-4b58-b525-f86babb21bfb": "What kind of training should be provided to people interacting with AI systems in sensitive areas?", "e0f9ad8a-c33a-4717-88ac-d8559f6c974a": "Why is it important to incorporate human consideration in high-risk AI decisions?", "d4342127-5df0-405f-bbe8-dc24711944be": "How can organizations report on the human governance processes of their AI systems?", "65bf43cf-81c8-4872-ae3b-81bf21751ba3": "What are the best practices for assessing the timeliness and effectiveness of AI systems in sensitive domains?", "2f3abec1-74b5-405f-b734-843ecc211a3a": "How can transparency be maintained when using AI in areas like criminal justice and health?", "a4768a2a-62c0-471c-ab81-e9e0d81d83c0": "What are the potential risks of not including human oversight in AI systems used in employment?", "d68eeb41-7bcf-4744-80e9-7614c92438a8": "How can adverse decisions made by AI systems be mitigated in sensitive fields?", "5d143734-c64d-4ee5-9600-544de3dc380b": "What role does public reporting play in the governance of AI systems in education and health?", "2aac2f6a-920b-4393-b61e-98aa36d35f27": "What is the role of NIST in the research on explainable AI systems?", "6de62d16-19cb-45d2-949b-92609186983f": "What are the core tenets of explainable AI that NIST aims to support?", "8d9912fd-4615-4118-8134-a893b80920c1": "How does the Defense Advanced Research Projects Agency contribute to explainable AI?", "8e48c274-2976-4927-b9ab-6bef0546c6e1": "What are the goals of the Defense Advanced Research Projects Agency's program on Explainable Artificial Intelligence?", "7c6ecd5b-5475-43a4-8259-af3a5f014d39": "What is the importance of explainable AI in machine learning models?", "cfab0915-6e9f-412a-a432-bc0a06148923": "How do explainable AI systems help human users?", "eaa0dca7-f7a9-4bac-a8f3-dc0e410b9a94": "What are the potential adverse employment actions for failing to meet a defined quota?", "67312adb-b7a3-4c16-84b9-4e4697e002e8": "What kind of research is being conducted across federal agencies on explainable AI?", "d1c669d5-4d91-4300-8e70-5a49b9b7b517": "What are the best practices for implementing explainable AI according to NIST?", "a44278d2-1d80-4211-93b9-785f091ee871": "How does explainable AI maintain a high level of learning performance while being understandable to users?", "670b6be9-bff2-4e3f-9ddb-48503a59925b": "What are the key components of effective governance procedures for automated business processes?", "966409cb-250a-4100-9cb5-4cc606c16452": "How can organizations ensure that stakeholders are adequately involved in the governance of automated systems?", "42ce5b4d-fe04-4d95-87e8-bd0a8f2a1cf3": "What level of organizational responsibility is necessary for prompt decision-making in resource allocation and incident response?", "5a9cd608-2ac4-4bfa-8cfa-ca357e9841ac": "Why is it important to consider risk mitigation objectives against competing concerns in automated systems?", "a18b2932-8fa5-4635-9302-7ee0cbaf194a": "How should organizations handle use cases that have a significant impact on people's rights and opportunities?", "379549a5-d7e5-47a9-bafb-a7408746aca0": "When is it appropriate to conduct an independent ethics review before deploying an automated system?", "03540efe-c7b8-4bd6-8835-c6f7bb4e30b5": "What are the risks associated with the use of inappropriate or low-quality data in automated systems?", "09f74024-8869-4f32-b626-2138e3564a74": "How can organizations prevent the compounded harm of reusing low-quality or irrelevant data?", "d8dc0a3b-18dc-42ae-93f3-7614e9b55cfa": "What procedures should be in place for risk identification in automated business processes?", "ecdf8fe5-f149-44ac-b465-3fbacb40865e": "How can organizations balance the need for automation with the potential ethical implications for stakeholders?", "f5606d22-27dc-4b36-9ace-72d6cc48660e": "What are the best practices for engaging diverse communities when introducing a new automated system?", "ae491447-4cf4-4991-b43e-08454411a5a6": "How can we ensure that the concerns of disproportionately impacted communities are adequately addressed?", "7ee78a3e-1ea7-4da5-875a-f65aa6f20054": "What types of experts should be consulted during the development phase of an automated system?", "2078e8f7-9bea-4153-bc28-2944699c7a6e": "How can privacy and civil liberties be protected when implementing large changes in automated systems?", "7b087c9c-e491-4d32-b692-81313a1e6afe": "What are the challenges of maintaining confidentiality in private sector consultations before product launch?", "208c1297-47eb-4aca-9561-f53fdb900d7b": "How should government applications balance the need for confidentiality with stakeholder engagement?", "44b1a320-c340-4a37-bcf5-c93a6963e2e0": "What are the specific considerations for law enforcement applications of automated systems?", "c223bce2-8a81-489c-9230-31400072a3fc": "How do preexisting oversight laws impact the consultation process for new automated systems?", "8b96696a-d368-4159-b644-3e82a3269da4": "What strategies can be used to engage sector-specific experts effectively in the consultation process?", "e0ca9dfa-fbe1-41a0-b064-9e4655a76477": "How can the risks unique to certain communities be identified and mitigated during system development?", "ee3ed9e9-e13a-43ae-8468-ceb8ffcf49b6": "What are some current uses of technology that impact equity of opportunity in employment?", "56c869aa-9f69-476f-bb2c-ff1cb0080445": "How is technology influencing equal opportunities in education?", "ecc2c5eb-78a6-4d19-b33b-19b08c0fdbfe": "What role does the White House Office of Science and Technology Policy play in promoting civil justice?", "db262b36-e3f4-48a0-bddc-dc36a289a41e": "How can technology be leveraged to ensure fair housing opportunities?", "6d61f78a-7ebf-45f4-a5e6-4881a583f4c8": "What insights did Christo Wilson provide regarding technology and employment equity?", "d1b8703a-3114-4088-9309-0c02821f5a37": "How does Pymetrics, led by Frida Polli, use technology to promote equal opportunities?", "80cdf547-f019-49d5-b954-fc44fb501eef": "What are some emerging technologies that could impact civil justice, according to Karen Levy?", "074222ac-fda2-47de-b57c-5ddc1063b7ba": "How does Upturn, directed by Natasha Duarte, address issues of technology and equity?", "55189c9a-9917-4b08-9b39-7f0a6c48256e": "What legal perspectives did Elana Zeide offer on technology's role in civil justice?", "50e8150e-4538-45b0-a17d-be191d1fa248": "How does Fabian Rogers' work with NY State Senator Jabari Brisport's office relate to technology and community advocacy?", "eb5cb844-864a-468b-8c58-527d3531343d": "What are the best practices for involving national security professionals in AI system risk management?", "62d2b5a7-b986-4048-bb97-766d7b98ce5e": "How can organizations effectively map and measure national security risks associated with AI systems?", "f72b3652-6c80-4c83-8aeb-9eee8ef96c3e": "What mechanisms can be implemented to protect whistleblowers in AI governance?", "afb866f7-aa0b-4116-9378-f258a4bf12ad": "How should organizations handle CBRN information or capabilities in AI systems?", "a1ddee9f-3320-4745-8c67-624c95b262a7": "What steps can be taken to manage dangerous, violent, or hateful content in AI applications?", "099e3b3a-218d-4c72-8460-0c899484ecd1": "What are the key components of an effective whistleblower protection mechanism in AI governance?", "b923df73-4a58-4d22-8b55-1a01145c5ac7": "How can AI systems be designed to comply with information security requirements?", "1464f6bf-4914-46ea-a181-13cbb9e7058b": "What role do national security professionals play in the oversight of AI systems?", "4e333af2-62cb-4a18-9737-5e42d27891af": "How can organizations ensure that they are not violating laws related to public safety with their AI systems?", "44cf4f5a-ee5c-4173-8c24-e6a9084636d9": "What are the challenges in providing protections for whistleblowers in the context of AI governance?", "732e3e58-5725-48ab-a40c-961aea398141": "What are some methods to evaluate gender bias in coreference resolution systems?", "c0e18063-83e5-462a-b99d-ca04e73f72f1": "How can gender bias in NLP coreference resolution systems be detected?", "ab81895e-d428-4fd5-bed3-030440a61e22": "What datasets are available for assessing gender bias in coreference resolution?", "33ec5775-e26d-4365-a8e5-69cfded28cf2": "Are there specific metrics to measure gender bias in coreference resolution systems?", "595f4527-0e21-40a7-b9ec-6a757d80f511": "How does gender bias impact the performance of coreference resolution systems?", "1bc870b7-1589-44a0-ae78-e41f637ce93b": "Can you recommend tools for evaluating gender bias in NLP coreference resolution?", "25ab951c-e59e-43dc-9315-79f04297d81b": "What are the challenges in evaluating gender bias in coreference resolution systems?", "c8004ebf-4187-4dab-b1fe-1c725fa9d4f4": "How can we mitigate gender bias in coreference resolution models?", "99062576-8040-45bb-ba14-33e7d06843c4": "What role do pronouns play in gender bias within coreference resolution systems?", "f631fe4b-8511-4605-b562-6b32a5fc4ce3": "Are there any case studies on gender bias in coreference resolution systems?", "e909abea-82ea-425e-9eb4-e7fc5cfd1afa": "What are the key technical and governance interventions needed to protect against the harms of emerging technologies?", "8f2b141e-7e25-48c4-8d6e-c7649407098e": "How can transparency and data collection help in mitigating the negative impacts of new technologies?", "2504edde-ca0f-4ab0-b316-072c94ed4fd7": "Why is flexible and reactive policy development important in the context of technological advancements?", "ee944244-c6e4-4f82-81c9-f965ee4f8f7c": "What role do clear guidelines play in fostering a consistent environment for innovation in technology companies?", "fddee110-d5c1-4e71-a392-a18885c4d603": "How can principles and guardrails contribute to responsible innovation in the tech industry?", "0a8ddcee-d0d1-41e1-a6c9-246be5b5ae5f": "What are the current and emergent uses of technology in the criminal justice system?", "c51a2c1a-9f87-488a-9d42-41968bf4cab1": "How do technological advancements in the criminal justice system impact public safety?", "95c6ba82-ae2a-411b-8572-31a3d48cc6a7": "In what ways can technology undermine justice and democratic values within the criminal justice system?", "0c97280b-063a-46a8-bbd5-f47e888354e5": "What are the potential benefits of using technology in the criminal justice system?", "fa8d6dc4-7eba-45d5-a66a-eb6b8ab2ecad": "Who is Suresh Venkatasubramanian and what is his role in the White House Office of Science and Technology Policy?", "21ceca0c-ce44-43e3-8f77-a9dc1f5fbcc7": "How has facial recognition technology led to wrongful arrests?", "d3a9c980-e575-44e6-bab5-07aaca0e2886": "What are the implications of AI bias in law enforcement?", "7f116d0d-2c08-40d1-817d-6f4c1826f047": "How many Black men have been wrongfully arrested due to facial recognition errors?", "380fee90-ebb8-4757-8fa4-7bb4a3b50dfd": "What steps are being taken to prevent wrongful arrests based on AI?", "f0b6fb64-5d64-4512-97bb-0a674ad3b42f": "How did the wrongful arrest affect the Jersey man accused of shoplifting?", "e2b27dbd-6b32-4fba-8260-c9b54e2ac8de": "What are the consequences of AI bias in recruitment, as seen with Amazon's tool?", "dbe0bf87-a716-4127-9f80-f9e325332d95": "How can AI systems be improved to avoid racial and gender biases?", "b8b6fbea-dea8-487e-bf33-6235d3a607e2": "What is educational redlining, and how does it affect student borrowers?", "a0a96c91-6c5a-4fd0-8127-b7c974303838": "How did the wrongful arrests based on AI impact the lives of the three men mentioned?", "dbd41bb0-0c09-4495-b286-dc9622de9e86": "What measures are being implemented to address AI bias in various sectors?", "0e1301c3-0b83-4603-9d39-8c374b37340d": "What are the benefits of documenting and reporting GAI incidents?", "c00fe054-52c2-4561-80e1-4b27a535ac03": "How can standardization of GAI incident reporting improve risk management?", "fd45462e-12d0-40d0-a428-90041a7dff99": "What roles do AI Actors play in reporting AI incidents?", "a531e2af-3989-43fb-8d5a-5808c6ec17bc": "Why is it important for organizations to develop guidelines for incident reporting?", "69db45ba-aef9-4c24-b15a-824ead34c0cf": "How can guidelines help AI system operators identify GAI incidents?", "c8828f01-879b-4d90-bc2c-f97dde5bf765": "What should be included in the guidelines for publicly available incident reporting?", "ce0d270a-d64e-4526-97cf-96ef519cf24a": "Why is the documentation of third-party inputs and plugins crucial for GAI systems?", "b8747453-8022-467b-b1b5-5145d44ff203": "How can greater awareness of GAI incident reporting promote transparency?", "ddd8c6c0-1296-4762-b557-374a51ff3add": "What measures can organizations implement to prevent future AI incidents?", "14fc80ec-eef8-48bb-9d01-33069ee9b8fe": "How can AI Actors trace the impacts of GAI incidents to their source?", "df8094ac-8e28-4a78-838d-606526447758": "What are the different applications of GAI systems in organizational settings?", "4b8eb074-1b7f-448a-ac6d-be4d1ddaed05": "How can organizations restrict AI applications that exceed risk tolerances?", "3710b3fa-3a13-4381-b514-9fc7f8dea69b": "What governance tools can be applied to GAI systems?", "8aa6ab37-2653-45b2-a725-a7735747f754": "How is content moderation handled by AI technology?", "4c0876f0-776a-4fac-a0e2-a3148db5b6f9": "What are the qualifications required for AI actors interacting with GAI systems?", "288d8ca3-7d48-4d33-8b24-d9e7bc4d94a8": "How can AI technology be used for code generation and review?", "fe80034d-0f1d-4bd0-8551-8f0d79001f23": "What protocols are involved in auditing and assessing GAI systems?", "23dc8c4c-f982-4955-b9bd-af9b54a6b57e": "How do organizations ensure AI applications align with their values?", "90900ded-0b53-44a3-9a22-13f8a5988204": "What are the change-management controls for GAI systems?", "0ca2f759-ebbe-4a9b-817b-1c16c7d1e376": "How can AI technology assist in data labeling and preparation?", "40801caf-7abe-479e-9818-e654ea44c389": "What are the key differences between AI risks and traditional software risks according to the National Institute of Standards and Technology (NIST)?", "0943156a-41b4-4d6c-8add-0bb5010e1936": "How does the NIST AI Risk Management Framework (AI RMF) address AI-specific risks?", "10a26c62-5c72-487a-b041-044cc2f6e7e7": "What resources are available in the NIST AI RMF Playbook for managing AI risks?", "66155b2d-caf6-421b-86c6-ca18b2579570": "How does NIST suggest framing risk in the context of AI?", "120752de-fe52-4f54-9e4a-49a9641d77ff": "What terms are included in NIST's glossary for trustworthy AI?", "28130de3-a5d1-4a75-aef6-60681684793e": "What steps does NIST recommend for identifying and managing bias in artificial intelligence?", "a74132c1-3fa1-462f-88d0-d418f51aaebf": "How can the NIST AI RMF Playbook be utilized by organizations to improve AI risk management?", "66be8191-b960-4fed-b0ba-c92018e56838": "What foundational information does NIST provide for understanding AI risks?", "edbb2f46-b7fe-4483-98f0-ebc5eef57da8": "How does NIST's 2022 publication contribute to the standardization of bias management in AI?", "cb87b719-4b5f-41e2-af94-c5ee3c301e18": "What are the main components of the NIST AI Risk Management Framework?", "02e280c0-6258-47f4-bb62-1324b012cd32": "What are the key challenges in ensuring automated systems work as intended?", "57a1c358-afc7-4547-8390-0545a91d0b6f": "How can automated systems be protected from unintended harmful outcomes?", "9ec63ba3-4a78-4919-9641-06406a26d3df": "What are the consequences of 'alert fatigue' in medical settings?", "30f03404-8efd-4a10-8b15-4563ba490e24": "How can the accuracy of predictive models in healthcare be improved?", "5911ed64-f3fb-4bbc-a354-710e9eb4a6c8": "What measures can be taken to prevent automated moderation systems from silencing counter speech?", "0a2e4e30-4e96-4313-8701-66fb74fbaa6e": "How do automated systems impact the safety and well-being of the public?", "754bdb70-fd0d-42db-b514-ed3e792c9c66": "What are the ethical considerations in designing automated systems for social media moderation?", "2b123ed9-5e26-4f5b-8bac-71dde9f51ca1": "How can hospitals mitigate the negative effects of false alerts in predictive models?", "a72510fb-3627-482b-bc59-e8a9d2d9c7fe": "What role do independent studies play in validating the performance of automated systems?", "77f146ae-3822-4a25-b535-3110c58c0759": "How can automated systems be designed to better distinguish between harmful and non-harmful content?", "b2d56c7c-fa94-47b2-9b32-0c4729fb2f12": "What are the primary information security risks associated with Generative AI (GAI)?", "31cf8128-b127-4673-88f6-875bd9d671be": "How can GAI lower the barriers for offensive cybersecurity capabilities?", "4c7d4d1b-256a-408a-8d84-d8a691961a20": "What types of attacks are GAI systems vulnerable to?", "b5d4dcd0-59de-49a8-97e5-1bc4c4de0c99": "How might GAI expand the available attack surface in cybersecurity?", "43f7aac1-4168-4700-b4c2-ba575419b046": "In what ways can GAI augment traditional cybersecurity attacks like hacking, malware, and phishing?", "b5e47640-3a12-4f25-80db-01036d1872b5": "Are there reports indicating that Large Language Models (LLMs) can discover system vulnerabilities?", "032a7d8e-cbd4-4005-96ab-461828a13663": "How can sophisticated threat actors use GAI-powered security co-pilots in cyber attacks?", "7ab5047e-51ca-40c0-8cc4-48fd68fcb7df": "What role can GAI play in helping attackers evade threat detection?", "0338aa3a-47c1-4a51-acce-90bfd9a2dcf2": "How might GAI assist attackers in escalating privileges after gaining system access?", "5001a4f7-f1ac-4bf1-9152-b893c1f45412": "What measures are necessary to maintain the availability of GAI systems in the context of information security?", "06e02bbe-ec13-46b6-a82a-c3eedbe9df94": "What is the significance of a waiver of sovereign immunity in legal terms?", "c5af22e4-d127-4a04-a563-47eaad15d6e0": "How does sovereign immunity protect the United States and its entities?", "d073d233-f4cd-4e5a-a3af-b8fa829b6a27": "What is the difference between substantive and procedural defenses?", "f810f097-05b7-43e9-b7e2-fa7d21b5c53b": "Can a work of the United States Government be copyrighted?", "b56876d6-1fb9-40ab-86b9-a78a889bbbec": "What does 17 USC \u00a7105 state about government works and public domain?", "73e2f0c1-f0cf-49da-906d-fc8510921e3f": "How can one enforce a legal defense against a US government agency?", "d8c94105-67dc-479c-a469-65e8104efca1": "What are the implications of a document being in the public domain?", "1a7e6b55-7f76-4439-9567-12cc8d835c96": "What legal protections do officers, employees, or agents of the US government have?", "c0aa67d6-de29-4bf6-8b18-04bbaf49240a": "How does the concept of equity differ from law in legal proceedings?", "88df5351-74b0-465c-9de9-b5807548c0dd": "What are the limitations of enforcing legal claims against the United States government?", "168b2e48-4e05-44a6-b944-aa2feb95f9e4": "What are the potential impacts of surveillance technologies on individual rights and opportunities?", "b72701b8-aef7-496e-8747-79854e65fcda": "How can one ensure that their data decisions are respected in automated systems?", "68af651a-6b8b-41bb-8f3e-14604272284d": "Why is it important to have access to reporting on the use of surveillance technologies?", "7faa544a-97f1-4d9c-804c-36a978652159": "What kind of documentation should designers and developers of automated systems provide?", "3d27b603-05bb-4a64-bc55-e9add2c9f314": "How can automated systems limit access to education, work, and housing?", "63d1952d-d789-4fd2-b18a-c7ddf8ce8cc1": "What should be included in the notice provided by automated systems?", "44065a66-2c8a-4d0f-9ebb-8dcfbdefe195": "Why is plain language documentation important for automated systems?", "fa9aff28-f81d-4034-acb6-19b295cae5fa": "Who is responsible for providing explanations of outcomes in automated systems?", "7e79602f-7d17-47d4-8874-50337e61fdc9": "How can individuals understand the role of automation in systems that impact them?", "eba5ba0f-95a3-4429-9437-7d0be9b5e0b8": "What measures can be taken to ensure transparency in the use of automated systems?", "b3486f90-735d-49df-86bc-739ba6403a31": "What are some top progressive companies building ethical AI in 2021?", "d5195aba-7870-4c55-961d-ed0ffe276376": "What methods are being used to assess equity according to the Office of Management and Budget's 2021 report?", "f0365668-2d3e-4a22-aac1-d25a64683ef8": "What is the AI Risk Management Framework by the National Institute of Standards and Technology?", "ce4365ac-9fdf-43ce-b139-503ec9ad37a4": "What is the purpose of the US Department of Energy's Artificial Intelligence Advancement Council?", "6737307a-5bbc-4ab4-b524-9437eee812f1": "When was the US Department of Energy's Artificial Intelligence Advancement Council established?", "e209d21e-f9c1-41cd-bbf5-14d112a1db70": "What are the key points of the US Department of Defense's Responsible Artificial Intelligence Strategy?", "139ad9ad-384f-497d-af84-dc9b24d2dade": "How does the AI Risk Management Framework help in managing AI risks?", "a24c2df7-395d-4019-8e4c-feb9d16b19d6": "What are the main objectives of the US Department of Energy's Artificial Intelligence and Technology Office?", "93b1cd97-2fe1-4152-ab7c-a0efbf49a6b5": "How can companies ensure they are building ethical AI?", "9c028b3c-c92c-4ca5-b7c4-e8d1c358b6c6": "What are the latest developments in AI ethics according to the 2021 article by Disha Sinha?", "0bfaf653-4226-41e5-865c-a5d63578d4e7": "What are the main concerns associated with the expense of broadband service for telehealth?", "0fd4687b-e9e7-498f-acd7-9eb020850852": "How do privacy concerns impact the adoption of telehealth systems?", "ebdadd5c-1215-40f5-8b2b-f242fbd35451": "What are the equity issues related to the cost of health monitoring devices?", "fba46c57-4104-40f5-bc91-fb9b706c2ef2": "How can racial biases in technology-enhanced care perpetuate discrimination in medicine?", "dfef4df6-fa61-419f-82ae-6a148536db56": "Why is it important for medical technologies to be accountable to relevant stakeholders?", "0fa04860-d710-40b5-856d-1dbc9d3bc759": "How can the voices of those subjected to medical technologies be better heard?", "6275567f-707b-48df-93ce-787e58e407de": "What are the potential solutions to address the expense of broadband service for telehealth?", "5c0dd9dd-bd3d-4f2f-b1d3-e8d142665e33": "How can privacy concerns in telehealth systems be mitigated?", "be446845-3854-499c-886a-d08121ae6700": "What steps can be taken to reduce the cost of health monitoring devices?", "21abc9b0-3037-4ca1-bebe-3ebbb20cbd20": "How can the medical community ensure that technology-enhanced care does not perpetuate racial biases?", "735c4032-1519-4fd5-8cdb-0e9a0ce6da5c": "How can the principles of the AI Bill of Rights be implemented in real-life scenarios?", "9daf1259-d81a-4cc8-8d81-e60f2962b064": "What are some practical technical approaches to protecting rights and opportunities in AI?", "d927d226-242f-4436-8243-c62ee8339ab8": "How can sociotechnical approaches help in actualizing the AI Bill of Rights?", "920eaf59-a989-498c-8964-7ac0a342d7b2": "What role do laws and policies play in ensuring the AI Bill of Rights is respected?", "1ddaf3a2-3fbb-4e1f-8bea-3a5bd70e5f8d": "Can you provide examples of how industry and civil society can collaborate to protect AI rights?", "aa9fb7f7-6205-45a6-8e2c-e7713a8420fc": "What are some illustrative cases that show the implementation of the AI Bill of Rights?", "f738f637-ecf5-43fc-b89f-65431bac4cb2": "How important is the cooperation among researchers, policymakers, and technologists in implementing AI rights?", "9db348ec-94bf-435c-aec7-b1da0e3acad9": "What are the expectations about technologies in the context of the AI Bill of Rights?", "2af37117-da7d-4d16-afb2-b96ea0513e67": "How can the public contribute to the effective implementation of the AI Bill of Rights?", "2939615e-23fc-4214-966c-6ba4fe1b7335": "What are the challenges in moving the principles of the AI Bill of Rights into practice?", "a7c4e78f-9e12-4e77-80a9-1b6d0e378dc7": "What are the key findings of Karasavva et al (2021) regarding the predictors of non-consensual dissemination of intimate images?", "f9d93ab9-108e-49db-901e-3dc647847f97": "How does the study by Katzman et al (2023) contribute to understanding representational harms in image tagging?", "73c8f947-0282-4541-8b91-1746ecf82b5a": "What are the main components of the value chain analysis for generative AI as discussed by Khan et al (2024)?", "f28b1c3a-c692-41ea-8144-dd7b5230aab8": "What is the purpose of the watermark proposed by Kirchenbauer et al (2023) for large language models?", "14f8c882-d08f-4bd0-923e-5d8b8841fd45": "How does Kleinberg et al (2021) address the issue of algorithmic monoculture and its impact on social welfare?", "17eb019d-fa03-4024-90b1-435b97d565de": "What insights does Lakatos (2023) provide in the report \"A Revealing Picture\" published by Graphika?", "e0f19f85-0585-4ce1-b033-c658c72c6731": "How can the findings of Karasavva et al (2021) be applied to prevent the non-consensual dissemination of intimate images?", "ff276cd8-c1b4-4ac4-ad1a-fe49517a74c0": "What methodologies were used by Katzman et al (2023) to measure representational harms in image tagging?", "afaa6994-4806-44cf-958a-057084b24a97": "What are the implications of the value chain analysis by Khan et al (2024) for the future development of generative AI?", "b7b673c0-0b37-42fe-9b9a-93758490f9ef": "How effective is the watermarking technique proposed by Kirchenbauer et al (2023) in protecting large language models?", "98816e76-3c36-44a7-9f7b-e1c94ca23586": "How can active learning techniques be used to identify model failures or unexpected outputs?", "8fe3db0a-9fc1-49f4-b08a-ed387dd67784": "What are the benefits of sharing transparency reports with stakeholders regarding GAI system updates?", "62865470-d8f3-4ebf-bf2b-050f5fcbce3b": "How does tracking dataset modifications help in maintaining the provenance and integrity of information?", "fe41122b-c0e0-4a47-9424-b21efd0d8405": "What role do AI actors play in user research and experience?", "c5fabcc7-22e9-49c6-b965-c80316d5b4d8": "How can harmful bias and homogenization be mitigated in Human-AI configurations?", "8086f26a-3e53-45ca-8e09-adcaeb35b100": "What steps should be included in transparency reports to enhance accountability in AI systems?", "61e1e6a5-ba18-4763-9a90-5f6b278dcda0": "Why is it important to monitor data deletions and rectification requests in AI datasets?", "45090c7b-a6aa-4517-8b79-30964e872d62": "How can collaboration with AI actors improve content performance and impact?", "3b005aea-9582-4e7e-b2ed-86f7c16dffa6": "What are some effective methods for ensuring the veri\ufb01ability of content origins in AI systems?", "2bb3e489-4c81-4e1b-aa8a-149336e61c0f": "How does confabulation affect the transparency and accountability of AI systems?", "77aa993b-372c-4534-8252-ca9c4010c1cf": "What is predictive policing and how does it work?", "6a1dc5f7-53a2-431d-80bd-8ddfbb546084": "How can predictive policing systems impact individuals' privacy and rights?", "0b5870d7-28c3-4da6-82be-4f2dcc63e1bf": "What are the potential risks of using automated systems in law enforcement?", "673c25a5-a7a8-4bfc-82aa-81b7f1bda04f": "Why is transparency important in predictive policing systems?", "ea441231-122d-47f5-8f5c-11085f9fd1f4": "How can data entry errors in automated systems affect individuals' access to benefits?", "0ed1645c-4661-46cb-8443-35a4c8e8ce60": "What measures can be taken to ensure fairness in automated decision-making systems?", "11076db2-fd60-471a-aba9-62b355aed19e": "How can the public be informed about the criteria used by predictive policing systems?", "3ae32342-738f-4cb9-b5dc-16fcf2130ea2": "What are the ethical concerns surrounding the use of predictive policing?", "ff50e166-1288-43c1-a067-65b0cf902d06": "How can individuals challenge decisions made by automated systems?", "f12d83b4-be05-4565-86df-f93a0c64b324": "What role does public transparency play in the effectiveness of predictive policing systems?", "37dd7447-0e75-4e14-8e17-865d6555c74a": "What is the Labor-Management Reporting and Disclosure Act (LMRDA) and what does Section 203 cover?", "1687fec4-dc70-4040-b728-4b5e44edc435": "How do I fill out the US Department of Labor Form LM-10?", "10d62236-489c-42fd-81dd-7885112ad9b2": "What are the key points in the OLMS Fact Sheet regarding Form LM-10?", "e9cd49c5-55d2-4b58-b05a-d0534264115e": "How does Apple protect user privacy according to their documentation?", "e659b628-dfa2-49f4-a768-e8761ae1c74e": "What measures does Google take to ensure Android is secure by default and private by design?", "7ea78477-98bc-4ff3-8d95-b316f391a035": "What are the main arguments in Karen Hao's article about algorithms trapping people in poverty?", "74061af4-43ea-4d23-9765-abe2b5fbb9e1": "How are lawyers fighting back against hidden algorithms that create poverty traps, as discussed in the MIT Tech Review article?", "dfdb3835-219b-4d3a-9673-d2923df2fb4b": "What concerns does the ACLU raise about family surveillance by algorithm?", "18a0946d-d4d3-4c73-b1bc-ef5d2d6cca86": "What are the implications of algorithmic surveillance on families, according to the ACLU fact sheet?", "3f73048f-6c23-48db-be72-402295190c87": "How can developers design for safety and privacy in mobile applications, as suggested by Apple and Google?", "f9d78f26-8f38-45a5-a05d-126e99e0b295": "What are the best practices for testing automated systems in real-world contexts?", "caec4118-4465-454f-8361-aebd8d21a912": "How should feedback be documented when reconsidering the deployment of an automated system?", "318fb3a4-b202-4e61-870b-b9a18c7c8f54": "What are the key differences between automated systems testing and human-led testing?", "3681a289-6754-4f14-9c68-bba82f3179af": "Why is it important to mirror real-world conditions during the testing of automated systems?", "424ac5ef-46e1-4f01-bee3-d71a0e907e5d": "How can material differences in deployment conditions affect the performance of automated systems?", "032fd89f-0b92-4533-a520-39fe68cc1744": "What role do human operators or reviewers play in the effectiveness of automated systems?", "a788ae08-165b-4797-b530-9054fffc79b9": "How should system performance be compared with existing human-driven procedures after testing?", "c823ae3a-5c23-421a-a316-3fb0a90fdff6": "What domain-specific best practices should be followed for testing new technologies?", "4e06d594-f59f-43ed-9c42-766b3d71377a": "Why might new testing be required for each deployment of an automated system?", "f0a8cfb7-ca5a-41af-874f-24ca1c10564a": "How can the outcomes of testing influence the decision to deploy an automated system?", "ceea82a8-3f36-499c-8999-f705089fd5c4": "What are the expectations for automated systems in sensitive domains?", "4da1b1fe-5a0f-4873-9a51-592e7031b5f0": "How can users opt out of automated systems in favor of human alternatives?", "2d5f0e7a-37f4-41f3-a270-083718406673": "What mechanisms should automated systems provide for human oversight?", "b597f3f4-73ca-41d6-805f-ea8566ee4335": "Why is it important to have human consideration and remedy in automated systems?", "51a36031-cbe6-4896-a26f-0d1231ac9ac5": "What kind of training and assessment is necessary for human-based portions of automated systems?", "28e9d3c8-9aad-4ac2-8b76-8112ba317fc7": "How should automated systems ensure the effectiveness of human alternatives?", "3cd1b051-c5ec-4ba6-85a3-6c8ecc3d382e": "What safeguards are recommended for automated systems in sensitive areas?", "93157218-65e8-4b27-bdc0-d3b5c75016f2": "How can automated systems provide clear and accessible instructions for opting out?", "6a607a7d-6808-444f-a772-aa55eccd8e61": "What role does human oversight play in the effectiveness of automated systems?", "522e086d-9b12-48c9-b070-b9f0c6b871e8": "Why is it important to have fallback systems with human oversight in automated systems?", "ce02496c-71b3-4ab7-98bb-eed1cc3edc11": "What are built-in protections for abusive data practices?", "55c73a61-2c93-43db-b06b-142fea09d1a3": "How can I ensure I have control over how my data is used?", "8dae2406-bb95-4836-9224-224fa830dd81": "What design choices help protect my privacy by default?", "1ddfec1f-63dc-4114-8d2c-6c6b080df23d": "What are reasonable expectations for data collection?", "ca588f53-c672-4ec4-8c2f-4edb75780625": "How can designers and developers seek my permission for data use?", "f01609ce-a9ca-4166-bc21-4837e9f8dbe6": "What are alternative privacy by design safeguards?", "bf05189a-5783-4529-9a04-33ecb2b039f6": "How can I avoid privacy-invasive default settings?", "69cd9e44-ebad-4444-bd6a-0ffe7dd0fea1": "When is consent necessary for data collection?", "5592a53b-bc51-4eb2-ad09-d91eab84cbca": "What are the best practices for respecting user decisions on data use?", "da87855a-e8d3-464f-b44a-2f1c0f36efd9": "How can automated systems ensure my data privacy?", "537d6d33-2d70-4cda-bfd2-a7e7d58dca1c": "What are the guidelines for ensuring surveillance is proportionate and necessary?", "f9c45eea-e5e9-4963-b36b-eac4e1041f10": "How can designers and developers minimize the invasiveness of surveillance systems?", "95df7bca-5759-48de-aded-0bdcfd73b47d": "What measures should be taken to inform individuals about surveillance activities?", "08b6077f-18cf-437e-93e3-b2272cafdf09": "How can surveillance systems be designed to protect civil liberties and civil rights?", "32c66693-7c38-4482-b27e-1226a0d82810": "What are the legal requirements for providing notice to individuals subject to surveillance?", "b0213953-d766-4b10-aa1b-c7170ea2c1ab": "How can surveillance be limited to avoid infringing on democratic rights like voting?", "a7153e52-4939-4c06-bfa6-43f880a88d70": "What are the best practices for restricting the number of subjects monitored by surveillance systems?", "c1a6fa3b-e163-482c-8ca2-b05ca142d9f1": "How should data gathered through surveillance be managed and used responsibly?", "1b8e4a92-c4c9-4200-9e7f-a441aa82cd9b": "What are the ethical considerations for deploying automated surveillance systems?", "b3ed9e28-9cca-467c-9c04-1b533b1ff751": "How can surveillance systems be aligned with national security needs without compromising individual rights?", "b814a05e-73e6-4ac4-8098-646df1806acd": "What are the common biases found in automated sentiment analyzers?", "e2b9260e-db2c-4449-9f56-d5cbf8e617c2": "How do automated sentiment analyzers affect social media content moderation?", "9a8125b8-6346-4652-9584-b5e5399fa7bd": "What steps are being taken to address bias in sentiment analysis tools?", "2c59dede-dec0-4ef4-9a1c-f4e8e47a6727": "Why do searches for terms like \"Black girls\" or \"Asian girls\" often return sexualized content?", "3c7f39ce-861e-4abc-8b91-941233a6ff50": "How can researchers help in mitigating bias in sentiment analysis tools?", "0e532265-3e9e-4043-ac99-d073b610bb72": "What are the implications of biased sentiment analysis on minority groups?", "3479b71e-e61b-42b5-9866-827680891f1c": "How can technology platforms ensure fair sentiment analysis for all users?", "6334ec05-5071-42d8-98b8-fc5306d236b2": "What examples illustrate the bias in automated sentiment analyzers?", "c5293c46-c7bd-4332-b088-0f07e7fca312": "How does bias in sentiment analysis impact online communities?", "5386554b-00b3-4e7e-b130-eafd4d8eb057": "What measures can be taken to improve the accuracy of sentiment analyzers?", "22b750f1-231b-489a-bebd-3b193bea2a49": "What is the importance of calibrating automated systems to the level of risk?", "5de799b0-d874-492e-aa45-4fd7647abab2": "How can summary information about automated systems be effectively communicated in plain language?", "81900311-01e7-4092-a602-1d8187f760e4": "Why should assessments of the clarity and quality of notices and explanations be made public?", "65bccbee-7732-4dd2-be47-39627cdfeab0": "What are the key components of a good notice and explanation for automated systems?", "db31ef6b-186d-4690-9967-65f38c663c5b": "How can organizations ensure that their automated systems are transparent to the public?", "540f0169-64c9-4548-888a-05f286d81496": "What methods can be used to assess the quality of explanations provided by automated systems?", "415e4fbc-b69e-428a-9f94-7312d737e467": "Why is it important to report on the clarity of notices related to automated systems?", "1bfaa0c5-41a4-4311-a8ca-15d61ff4d3cf": "How can the public benefit from having access to summary information about automated systems?", "768e8af3-91d4-480a-8e3c-f3fb6fa362a0": "What are the challenges in making automated system reports understandable to the general public?", "85eec5c3-d2d6-458e-ada1-b311bf4a72f9": "How often should assessments of automated systems' notices and explanations be updated and made public?", "3d150e71-c79a-4bd8-8084-2ae5bafda260": "What are the key findings of Acemoglu's 2024 paper \"The Simple Macroeconomics of AI\"?", "1a24bdd1-8636-4d56-8125-f82bbece4d8e": "How does the AI Incident Database track and report AI-related incidents?", "84f606b0-d5e2-46fe-b0fe-9f8bd603926f": "What were the main incidents and responses discussed in Atherton's 2024 survey on deepfakes and child safety?", "b0068345-aa37-45f2-a66d-ab765c64e4c3": "What are the implications of intentional biases in LLM responses as discussed by Badyal et al in their 2023 paper?", "322cd2e4-d7f9-48b7-8de7-f1bb820e45a4": "How was the Bing Chat data exfiltration exploit discovered and fixed, according to Embrace The Red's 2023 blog post?", "555f7d72-2732-4953-b60e-5aa9bb3b5329": "What is the concept of algorithmic monoculture and its potential impact on outcome homogenization as explored by Bommasani et al in 2022?", "0a9a8d6d-03b6-4a09-a022-86b5bcbb4f9d": "What strategies do Boyarskaya et al suggest for overcoming failures of imagination in AI system development and deployment?", "28ffa310-5101-4271-a96f-ae81552638be": "What are the main security challenges in the AI pipeline as identified by Browne et al in their 2023 report?", "e59e161d-73b9-44a7-ad00-86e936500c7d": "How does the AI Incident Database contribute to improving AI safety and accountability?", "7712df59-b5e6-4300-81f2-1d0e16da04e2": "What are the potential risks associated with deepfakes, particularly concerning child safety, as highlighted in Atherton's 2024 analysis?", "ecfdcb90-ee70-422b-9850-10c9ebbf34c6": "What is the AI Bill of Rights?", "6dd78dc1-02ed-4f5b-abe6-398caa87184d": "How can AI improve Americans' lives?", "43f126a5-f5cf-47b2-a267-d84e162dc483": "What are the potential harms of AI technologies?", "2d69fe62-48f6-443a-af60-47dd8aa8e223": "How can we prevent the harms of AI technologies?", "b15d2c3c-6578-4ac7-bf29-1bb9ffae84d3": "What role did public servants play in shaping the AI Bill of Rights?", "c4aaa7b2-60f1-480b-9a24-5f8d421c6136": "How did the international community contribute to the AI Bill of Rights?", "98490660-182e-4994-a0e9-79f5063132a2": "What are some examples of public engagements included in the Appendix?", "db8d310e-c511-4d66-9486-f8723f206d2f": "Why is it important to have a formal request for information regarding AI?", "4dce7da8-27f9-40a3-917b-17d3726fd5ee": "How was the input from the public collected for the AI Bill of Rights?", "9f0a6fe1-594c-447e-8837-2a78a94f7b03": "What are the core messages from the discussions about AI technologies?", "60709a95-43fe-4194-a602-00bee13a364a": "What is algorithmic discrimination?", "d64d1e05-da97-4caa-a99f-c615a4ec29f3": "How can we protect against algorithmic discrimination?", "ec9e492e-7c12-49e0-b47d-e552f7d1f972": "What are some examples of algorithmic discrimination?", "336ad8fa-faaf-4447-bfc6-ef161da017ce": "What laws exist to prevent algorithmic discrimination?", "3b634a49-58a5-4fcf-a112-9a86f5ac0893": "How do algorithms contribute to discrimination in hiring practices?", "4b58cb88-0109-4889-95e2-055c73c49939": "Can algorithmic discrimination be completely eliminated?", "21b86043-f03c-4c93-a916-be8fd8b2ad61": "What role does transparency play in preventing algorithmic discrimination?", "63133742-a77f-4db6-846d-4d1f5059f01a": "How can companies ensure their algorithms are not discriminatory?", "661fa6f5-10ba-4b3b-a3aa-67fcb6b7c0ec": "What are the ethical implications of algorithmic discrimination?", "d181a784-4cc1-4749-98e2-0f0ce4f2e3be": "How do biases in data lead to algorithmic discrimination?", "ebf17b14-0e3f-4c3d-904d-649dfc42fa95": "What are examples of automated systems that can impact individuals' rights or opportunities?", "a6fabc41-7dfb-4c46-aa88-b4a3530b1d84": "How do automated systems derived from machine learning differ from passive computing infrastructure?", "24c03da2-ba86-485a-86f8-59894c03d3e1": "What is considered passive computing infrastructure in the context of automated systems?", "5e4464c8-91c2-44f1-9ab2-914ebaa083c0": "How can automated systems influence policy implementation?", "6784a5e2-6056-4306-93f8-80a495e09e01": "What types of data processing techniques are included in the definition of automated systems?", "79f1c48b-968c-4851-928d-ae6f42c61343": "Why are web hosting and domain registration considered passive computing infrastructure?", "925e7b0d-8fe7-40c2-a359-c8ee0f5ed344": "How do automated systems interact with individuals and communities?", "3397b416-793c-48c5-be7e-199cd416c910": "What criteria determine if an automated system is in scope for impacting communities' rights?", "fc6683f3-3edb-4168-be40-07bfdd0d288b": "How do automated systems aid in decision-making processes?", "f7d73d0c-df20-4ca2-91d2-a8c5afdc14c4": "What is the significance of excluding passive computing infrastructure from the definition of automated systems?", "36690cae-c8ac-4416-86a2-94636c14e662": "What is algorithmic discrimination and how can it be avoided in automated systems?", "ed1dbeba-1948-4424-9f4e-49940e6ced35": "Why is it important to limit data use in automated systems to avoid group-based inferences?", "6144bb8c-dc20-482c-b508-3a6746a31aad": "How can human oversight ensure that automated systems are tailored to specific use cases?", "10bc0fe7-54f9-4f07-8e70-4dc100547fa8": "What are the risks of using automated systems in sensitive domains without human oversight?", "a2df3dd2-4f82-4dc5-a09b-87f4bb447213": "Why should validation testing of automated systems not be assumed to transfer to different locations or use cases?", "1ceaf948-0544-42aa-998b-834363202b17": "What role should human consideration play in high-risk decisions involving automated systems?", "7ecb6173-5692-4d0c-9c5e-8b0b13bffa23": "How can automated systems provide positive outcomes without directly intervening in high-risk situations?", "1e214f08-1e4a-4588-b61a-55376c21b541": "What are some examples of high-risk decisions where automated systems should not intervene without human oversight?", "68fab0c7-c29b-44ec-af9d-05ad2474f8b0": "How can evaluation testing ensure that an automated system is safe and effective for a specific situation?", "7bd24a17-0f1e-4165-ad6c-a177ddda289f": "What are the potential consequences of allowing automated systems to make high-risk decisions without human consideration?", "c8b856a5-bdd4-468f-967f-2a2d971d1c03": "What are the legal limitations on the use of surveillance technologies by the government?", "403aa84b-752d-4588-b4e3-fa5a8c170913": "How do surveillance technologies impact the rights and opportunities of individuals?", "d6cc3ca1-888e-40c0-be4f-a80b26fe264f": "What constitutes \"real-time or subsequent automated analysis\" in the context of surveillance?", "33590f14-1e42-4a8a-b98e-4b50ed420647": "How can surveillance technologies affect underserved communities?", "a2a6d551-b7e7-4648-9043-311d908a8546": "What is the definition of \"underserved communities\" in relation to surveillance technology?", "8da5e9a2-f967-4417-a687-2d49feb921bc": "How does the framework address the protection of data and communications?", "2826ff48-bba2-4f87-9f2e-e425dd1999ff": "What are the ethical considerations for using surveillance technologies on individuals or groups?", "ff195633-1d86-4b29-8add-e361af17a5fd": "How can commercial use of surveillance technologies be regulated to protect individual rights?", "d1ee3ce0-b52c-4ea9-a326-9e3a36f91eab": "What are the potential consequences of surveillance technologies on community access to opportunities?", "655de1e5-ce3a-4bce-95ec-ebe789004f66": "How does the framework ensure the preservation and protection of identifying information?", "ec6b21b6-677f-430b-b3f1-682615b0c999": "What are the best practices for obtaining consent for data collection in sensitive domains?", "16885872-4b72-4e64-b7db-18121bb64984": "How can notice-and-choice practices for data use be made more understandable?", "f9d9b18c-d71e-4abd-b3ca-0223dec3ad95": "What are the enhanced protections for data related to health, work, education, criminal justice, and finance?", "2bb558fb-06ba-4259-b5c2-1069543d1700": "How should data pertaining to youth be handled to ensure their protection?", "9082084b-5bcf-44c9-acbf-4b018579d045": "What are the necessary functions for which data and related inferences can be used in sensitive domains?", "5fc54a90-cce1-45f8-8502-abf134313535": "What ethical reviews are required for the use of data in sensitive domains?", "98454bb2-eaf7-45a3-8e6d-9781a4a9d584": "How can communities protect themselves from unchecked surveillance?", "e9753e53-f009-433f-83b1-86b01c4fdf46": "What kind of oversight is necessary for surveillance technologies to protect privacy and civil liberties?", "7c787e2d-b2de-4444-a4e9-08b349e388a4": "What are the potential harms of surveillance technologies that need to be assessed before deployment?", "6c304545-a0cf-4473-aec5-25670f40a825": "How can continuous surveillance and monitoring be regulated to protect individual privacy?", "34a2354d-7bf6-4914-8c4a-cf196db36040": "What are the key points discussed in the document \"Records, Computers, and the Rights of Citizens\" from July 1973?", "0aad6105-223c-4dab-912f-526f486cdc6c": "How does the Office of Management and Budget's Circular A-130 guide the management of information as a strategic resource?", "f59c944c-112c-40a8-a47f-ac2b0347e2c4": "What are the main recommendations in the OECD's guidelines on the protection of privacy and transborder flows of personal data?", "c8df4ea5-17bd-4cca-a295-e7ee59f9e7d0": "How effective is the proprietary sepsis prediction model validated by Andrew Wong and colleagues in hospitalized patients?", "98b08556-abfd-4833-ae35-a8535571fea9": "What are the implications of the findings from the study on the sepsis prediction model published in JAMA Internal Medicine?", "cba6f835-caec-48d5-9b82-232ba8416963": "How does Facebook's moderation policy affect discussions about racism, according to Jessica Guynn's article in USA Today?", "d5c902d5-6803-43ce-9cc7-e41da57f53fe": "What does the term 'Zucked' mean in the context of Facebook users discussing racism?", "b810fe11-8639-4aa1-9680-e9aed0a7f23f": "How has the recommendation of the OECD Council concerning privacy and data flows evolved since its revision in 2013?", "cf8d9d77-d12d-4feb-affb-6668a8f6b2ce": "What are the criticisms of Facebook's handling of hate speech and discussions about racism as reported by USA Today?", "d47a2d26-34fd-45b5-b3ae-e8dfe20c77ac": "How does the 2016 update to Circular A-130 impact federal agencies' information management practices?", "345ce069-495e-49b5-af9c-c3149193f72c": "How can new technologies help reduce health disparities?", "74332ba4-7dba-484a-b7f3-db3c9b6c6955": "What are the potential risks of relying on technology for healthcare delivery?", "8480a6c9-125b-435b-87a1-ffad65340e1f": "How can policymakers ensure equitable access to healthcare technology?", "d4afcb88-ecf5-4717-9b29-d9b4cd68121b": "What role does artificial intelligence play in improving healthcare outcomes?", "468af870-6b02-4fa5-9205-37a33e43b63c": "How can healthcare providers integrate new technologies into their practice effectively?", "12891465-101e-4897-a86f-046d85706186": "What are the ethical considerations of using technology in healthcare?", "14c6eb6a-036f-4f26-bb80-a075fd2979a1": "How can technology improve healthcare access in underserved communities?", "861a1a80-5a7a-4b03-b86b-e6d7b357b14c": "What are the most promising areas for research in health technology?", "beb717de-9182-47e4-82bf-c27fde4a43fa": "How can healthcare systems balance technology use with patient privacy concerns?", "840b62a5-c2ca-45e6-9793-40fed59c838d": "What impact has telemedicine had on healthcare delivery during the COVID-19 pandemic?", "bd65a985-6adf-4ca0-800a-2f5e4eaf9313": "What are the best practices for monitoring AI-generated content for privacy risks?", "d1bdd54c-5d9d-4677-b5ac-065fd4b4e8e8": "How can organizations address instances of PII or sensitive data exposure in AI-generated content?", "e937f160-66b0-4289-83b1-2a5616b701ae": "What processes should be implemented to respond to potential intellectual property infringement claims in AI?", "a9f3fd07-2b06-4abc-9bae-9cb5c884420a": "How can new GAI policies be integrated with existing IT governance and legal compliance activities?", "00c694b6-964a-4ff8-9c00-082579e3705e": "What are the key components of effective data curation policies for AI training data?", "0d2d3927-99e8-44c3-aec5-08fdc4fc2fd1": "How can companies ensure their AI technology does not infringe on third-party intellectual property rights?", "227007e5-7052-4b42-b7b0-b914bcbe185f": "What are the legal risks associated with using third-party data or software in AI development?", "262df558-56e7-445f-9a93-ad716c929f95": "How often should organizations conduct monitoring of AI-generated content for privacy risks?", "b6f4c293-115e-4811-a3aa-9a9b8ddf6f11": "What steps can be taken to document AI training data curation policies according to applicable laws?", "46fd166c-6f0e-4c3f-85c3-b30f0a1d53a0": "How can information security be maintained while integrating new GAI policies with existing systems?", "560ee295-11c4-41df-a82c-d7e7f0f44386": "What is a performance baseline for an algorithm, and why is it important before deployment?", "66e50da4-fea8-4795-8a27-663c0cde6f02": "How can human performance be used as a lifecycle minimum performance standard for automated systems?", "4d449176-2653-4092-8b2f-4f047ac02fb5": "What are the decision possibilities resulting from performance testing of an automated system?", "b8a080cb-dbf5-4ca7-b5a4-5c84f821b1ef": "Why is it important to consider the possibility of not deploying an automated system after performance testing?", "cde58352-24e9-4fc4-aae0-9d41f4d197d6": "What are the key steps in identifying and mitigating risks before deploying an automated system?", "3426f11e-e5f4-418e-b97a-01f241a68b12": "How can potential risks of an automated system impact people's rights, opportunities, or access?", "f3e038cf-7997-4724-8e6b-99c701363442": "Why should risks to impacted communities that are not direct users of the automated system be considered?", "d730bbe4-b1d4-48dc-9ae6-737485ab0e96": "What are some examples of risks resulting from the purposeful misuse of an automated system?", "e4aae9a3-d377-43f0-b0b7-61cca8c61714": "How can the consultation process help in identifying concerns related to the deployment of an automated system?", "4237e65b-dc5a-4002-b88b-cd45f37bc5f7": "Why is it important to measure the impact of risks and balance attention towards high impact risks?", "a824bf8c-fd69-4e1b-a7fa-d8a0e946b3e3": "What are the key factors to consider when determining the expected and acceptable GAI system context of use?", "305a21f4-80f2-4d2b-9d75-6745caca88fb": "How can organizations assess the potential positive and negative impacts of GAI systems on public safety and democratic institutions?", "d4751075-70d8-4ec0-ae48-12518f492e05": "What are some common assumptions and limitations that need to be documented for GAI systems?", "9a023a00-7a74-40a4-9616-0444aeadb0bb": "How can socio-cultural and domain experts contribute to the assessment of GAI systems?", "01f67521-6c20-4fd8-8434-616c85133c1e": "What are the potential risks associated with individual and group cognitive biases in the design and use of GAI systems?", "2fd099a7-bb3b-4ae7-97cf-d4a44e7b14fd": "How should organizations document risk measurement plans for GAI systems?", "c09872bc-2fe0-44c2-92ff-4737772a9980": "What are some known past incidents and failure modes of GAI systems that should be considered in risk assessment?", "01e6920d-c467-4660-aeea-b58e1ad39cbf": "How can organizations address the issue of over-reliance on quantitative metrics in the evaluation of GAI systems?", "1ef08275-0345-43e2-87d8-2c0014a954c9": "What are the potential consequences of harmful bias and homogenization in GAI systems?", "5d1ea4e8-03c0-4918-a4b0-ee3fb7de061a": "How can organizations ensure that GAI systems align with social norms and expectations?", "f15a27f7-7498-4ada-be1c-3cac898dc341": "What are the key expectations for automated systems in terms of notice and explanation?", "b3491e6c-e129-4aa9-81b0-cb27a5390728": "How should an automated system provide notice of its use?", "02f41084-6947-4e5d-a014-2701aa7a8524": "What type of documentation should be provided for an automated system?", "37901011-f77e-472d-bc43-758d35691417": "Why is it important for the documentation of an automated system to be in plain language?", "d152bc28-9605-4041-84f0-75278caf5c62": "Who is responsible for ensuring that the documentation of an automated system is accessible?", "29842944-f55f-426a-b9fe-f93af91ad99a": "What should the documentation of an automated system include?", "8eb02857-2af2-4998-a936-ddb76db5f513": "How can an entity ensure that the documentation for an automated system is easy to find?", "7bebfe19-175e-4123-abe1-e08b0c2d683d": "What are the benefits of providing clear and understandable explanations for automated system decisions?", "98de5d6b-fc75-4dd6-90ed-3be730aeab0c": "How can automated systems ensure that their actions are transparent to users?", "45c83246-49f0-4517-8449-22f61e1ac6a2": "What role do human components play in the documentation of automated systems?", "d0176225-348b-4c83-ab7d-82277925e6e9": "What is the Blueprint for an AI Bill of Rights?", "f75dba8f-4254-4fad-b3ba-5ce51b3065e9": "How do AI and data-driven systems impact Indigenous communities like Tribes and Clans?", "d6be5ece-a538-4e8a-a374-7789a34d34c8": "Why is the concept of community integral to the Blueprint for an AI Bill of Rights?", "a1d04dee-74ab-4d43-8717-6e2684c5670b": "How does United States law currently protect the rights of individuals against AI harms?", "48ff1eaf-6834-4862-8e80-624bb71169e7": "What challenges exist in protecting communities from the effects of automated systems?", "7b9de209-f9fa-4ef0-8ced-8969ee2ae73c": "How can the harms of automated systems be evaluated at the community level?", "a2d29100-ebeb-4076-9ddf-1f64b365290a": "What are some examples of formal organizational ties mentioned in the context?", "fd57bf95-f994-4cf5-b914-af75dc140b11": "Why might the impacts of AI be more visible at the community level than the individual level?", "4eae01bd-26ed-4b64-9606-abf42d1039e7": "How does the Blueprint for an AI Bill of Rights propose to redress harms caused by AI systems?", "c93c5ccd-cd7b-4a31-b8fe-2730399bf76e": "What are the potential benefits of evaluating AI impacts at both individual and community levels?", "8e93918d-d152-4bda-a527-51eb1e4a563a": "What are interpretability and explainability methods in AI systems?", "8bd0ab3a-519e-4f8b-bd09-52e086f06ab1": "How can we evaluate GAI system decisions for alignment with their intended purpose?", "9ea19168-923a-4776-b043-9cc4c8d33b84": "What is the importance of monitoring and documenting instances where human operators override GAI decisions?", "48f1823c-987c-43b8-ba09-2f7f30c39478": "How can content provenance issues affect GAI system decisions?", "69904a33-e3bc-4725-a589-ae8903083507": "What are structured public feedback exercises in the context of AI system design and deployment?", "1ff81582-703f-4f1c-9591-b190d995ac44": "How should the results of public feedback be incorporated into AI system decisions?", "70b48d78-cf62-458d-9cc8-cdee5b6b30ce": "What are the roles of AI deployment, domain experts, end-users, and operation and monitoring in AI systems?", "3cbba8c5-608e-41ba-acc1-e266269a8d04": "What is the significance of verifying information integrity in AI systems?", "c0dbcb52-583f-455e-ae5b-a4baefe89ffb": "How can harmful bias and homogenization be addressed in AI systems?", "022fb6ca-e847-4f32-a2d8-a01f772f1c21": "What are the key considerations for making \"go\"/\"no-go\" decisions in AI system deployment?", "776a11f6-1df2-463f-8f5e-9ab8c838c2ed": "What is the role of the Connected Health Initiative in advancing healthcare technology?", "b183d8c6-087c-4de9-9b29-7b89974ffa14": "How does the Consumer Technology Association influence tech policy and innovation?", "611c347f-fd3b-498b-87ff-095aa469d501": "What contributions has Courtney Radsch made to digital rights and online freedom?", "ccd936e2-e89b-41c3-9b5d-4c171d9f1eb6": "What are the primary research focuses of the Data & Society Research Institute?", "de9aab5b-822b-43a9-97f2-e9d6959e33ba": "How does Data for Black Lives use data to address racial disparities?", "daa39ee8-a5c1-4bef-bb7a-eadbcc70f33b": "What projects are currently being undertaken by the Data to Actionable Knowledge Lab at Harvard University?", "cc6d42a1-429f-4ea8-a0c8-481571c586ea": "What services does Deloitte provide in the realm of technology consulting?", "1fa9c10e-8e74-472e-98c1-62ee3c81305f": "How does the Digital Therapeutics Alliance support the development of digital health solutions?", "3d8c9a00-451d-4097-95da-7db467588dc5": "What is the mission of the Electronic Frontier Foundation in protecting digital privacy?", "d5fd9d65-12bb-4f39-a0f1-3cb54d012fe7": "How does the Electronic Privacy Information Center advocate for consumer privacy rights?", "cb0bf5f3-38b6-4eec-81ff-530a778e0328": "What are the key findings of Smith et al (2023) regarding the use of neuroanatomy as a metaphor in large language models?", "207c0258-6572-48ec-ab8d-8f6558681013": "How do Soice et al (2023) propose that large language models can democratize access to dual-use biotechnology?", "eba2a62c-de0b-4649-8f1e-438799536f1a": "What methods and considerations are discussed by Solaiman et al (2023) in \"The Gradient of Generative AI Release\"?", "015148ae-410b-409f-a89d-73d1a425a37d": "What privacy concerns are raised by Staab et al (2023) in their study on violating privacy via inference with large language models?", "b4463b2e-409a-48a2-9a74-455373d37285": "According to Stanford et al (2023), whose opinions do language models reflect, and what implications does this have?", "6ae4fc70-185d-4aae-bc07-faedd4dbae8e": "What are the energy and policy considerations for deep learning in NLP discussed by Strubell et al (2019)?", "f67fd894-f032-407f-8771-8f564f4f9ca2": "How does the White House's Circular No A-130 (2016) relate to managing information as a strategic resource?", "ae278041-1973-4238-aa7f-a6cac1551a8c": "What are the potential risks of hallucination or confabulation in large language models as discussed by Smith et al (2023)?", "f6cbd86e-2f15-4311-9c83-e407554ff032": "How might the democratization of dual-use biotechnology through large language models impact society, according to Soice et al (2023)?", "38192107-9ce8-4cda-b34a-cc111e33be8a": "What are the ethical considerations in the release of generative AI as outlined by Solaiman et al (2023)?", "af1bb742-8ec7-4495-9141-a44df3bda1a0": "What is the Jigsaw Unintended Bias in Toxicity Classification competition on Kaggle about?", "379fa7b3-02e9-4abb-a67d-f5611f67453f": "How does the paper by Lucas Dixon et al address unintended bias in text classification?", "938ae17a-7800-4fa0-9d13-64d885add576": "What are the key findings of the AAAI/ACM Conference on AI, Ethics, and Society paper by Lucas Dixon and colleagues?", "c1a34901-9205-4c40-81b9-92d9bccfe577": "How has Google reduced racy search results for terms like 'Latina teenager'?", "fcd299fd-aad2-49b8-9fd4-d6d51e7d6d06": "What impact did Google's reduction of racy search results have on search outcomes?", "8fe9af88-6425-4dce-ba89-5f8170af3a50": "What are the main arguments presented in Safiya Umoja Noble's book \"Algorithms of Oppression\"?", "dbf83cba-a1ec-4513-a5ee-dbb91d87f238": "How do search engines reinforce racism according to Safiya Umoja Noble?", "07560e9e-9c12-44bd-8b3e-a2aa039ef9bc": "What measures has Google taken to address bias in its search algorithms?", "773283eb-6b5a-4256-8ddf-8f255df3f593": "How effective are Google's efforts in mitigating unintended bias in search results?", "d57e3ef2-9ba0-4083-91e5-bbbc46ea63c6": "What are the ethical implications of unintended bias in text classification and search algorithms?", "ae1eb349-2033-4722-ae50-edd77d230dee": "What are the expectations for automated systems in sensitive domains like criminal justice and health?", "f123f8ad-0f9d-473a-a63f-f10e7686745d": "How can human oversight be implemented in automated systems to avoid discriminatory impacts?", "61295097-606f-4249-968f-47372578c40c": "What safeguards should be in place for automated systems used in employment and education?", "663dd7a9-c1b9-432e-8fbf-ea8ec15a775b": "Why is it important for automated systems to have narrowly scoped data and inferences in sensitive domains?", "a0a14c6f-86f9-4164-99b9-4db3716b659e": "What are some examples of inappropriate impacts that automated systems should avoid in sensitive areas?", "5b5f3867-1803-4238-af24-bd788829ee4c": "How can technical standards and practices be tailored for specific sectors when developing automated systems?", "5e60b645-855e-47df-8ee9-48b1a1a83efd": "What role does human oversight play in ensuring the proper functioning of automated systems in sensitive domains?", "7e2af9b3-68e7-46c0-9213-acdc636f4273": "How can automated systems justify each included data item or attribute in sensitive domains?", "3176e372-80fb-44f7-ba7b-210022be925b": "What are the potential risks of using automated systems in criminal justice and how can they be mitigated?", "dc35ee01-7ac3-4ccf-8b45-14b5aa5a6c9e": "How can automated systems be designed to meet the expectations laid out in the framework for sensitive domains?", "d599c961-25c4-4fee-8ed1-d5c62a73647f": "What is AI red-teaming and how does it work?", "73118592-ad30-419d-b6b2-3dd0d9384da9": "Why is it important to have large groups of AI red-teamers?", "e5807faa-9a9f-4510-807d-c4553fcd9780": "What are the benefits of having domain experts in AI red-teaming exercises?", "d70f0a08-4229-4e3c-96e1-75b97e2bd955": "How can AI red-teaming be applied in the field of cybersecurity?", "e56fdc33-7ce6-4293-9d14-efd06aa134c7": "What challenges are faced when recruiting specialists for AI red-teaming?", "e3954bfb-ba3d-4cae-bbcf-993ccb500b97": "How can a combination of experts and non-experts improve AI red-teaming exercises?", "1bbd547f-2198-4ec1-ae87-5a5ac9ebc2d1": "What specific skills are required for effective AI red-teaming in medicine?", "54655f06-a110-44d5-84da-2b618c017d76": "How do AI red-teaming exercises help in identifying harmful model behaviors?", "775f37c2-5451-467c-8c55-81cbdf42dc44": "What are some examples of harmful behaviors that AI red-teaming aims to prevent?", "6092bd99-29ad-4e06-bb27-ad1ae9006a58": "How can AI red-teaming be beneficial in the biotech industry?", "bc600deb-fbcd-400f-9140-0d915fcdaa91": "What are the limitations of current pre-deployment TEVV processes for GAI applications?", "2aef734a-ac35-429c-a7ed-45f4bc41a30b": "How do organizations measure performance and capabilities in pre-deployment testing for GAI?", "14c90494-2295-4e90-ae42-73e7ae4a413c": "Why might anecdotal testing through video games be inadequate for GAI systems?", "cb928351-26a1-491c-9262-10297fb46ede": "What are some recommended \"pre-deployment testing\" practices for GAI?", "90e2f5ef-ab38-4486-ac93-f172d2500a85": "How do current pre-deployment TEVV processes fail to reflect deployment contexts?", "d860db03-3ac9-4ee9-8e9d-68730a2dbd6e": "What are the risks associated with using standardized tests designed for humans on GAI systems?", "7629f220-d4f3-493d-8160-89a311a495a7": "How can organizations improve the validity and reliability of GAI system testing?", "e54dbc2a-f5cc-47d4-b7f5-2cdad36a161d": "What is the role of risk measurement and estimation in pre-deployment TEVV for GAI?", "864610a5-0a37-4ef4-98d4-1b6d7d32f886": "Why might jailbreaking or prompt engineering tests be insufficient for assessing GAI systems?", "8fc6576e-192f-4f3b-af15-d1c21b908da9": "What are the state-of-play methodologies for pre-deployment testing of GAI systems?", "9bec12eb-4fa7-477e-a667-fd165c16f38d": "What are the key principles of the Privacy Act of 1974?", "ce2ec10e-da61-4462-b06b-0aa052282a80": "How does the Privacy Act of 1974 limit data retention in federal records systems?", "782d7b57-c109-49a4-aee8-fce11007be0d": "What rights do individuals have under the Privacy Act of 1974 regarding their personal information?", "04329baa-7e91-421f-b129-dcab9672ade8": "How can federal agencies determine what data is \"relevant and necessary\" under the Privacy Act?", "f84ca6ea-58d1-48f6-a5a1-cd8ef9f4658f": "What are some real-life examples of laws that protect data privacy?", "f2ce84d8-0c07-4e0e-9bcf-3aaecc8dc8a2": "How do technical approaches help in protecting data privacy?", "366462e4-8d9e-40ee-b30d-f4817377ba05": "What are sociotechnical approaches to data privacy, and how do they work?", "e8433dc8-3bc8-4eee-9a40-71e4005f3386": "How can policies be designed to ensure data privacy in practice?", "ead8c5d0-e517-4da2-b4b7-885f6c6031b4": "What are the limitations of the Privacy Act of 1974 in protecting personal information?", "7f75740d-9d77-4338-9f3a-78ab85ae1906": "How can individuals access and correct their data under the Privacy Act of 1974?", "caeaec67-6507-428f-8b4b-41751a7af496": "What are the common data privacy violations in system training data?", "2987bea3-66c4-4ccc-92fb-5c073f60fd97": "How can organizations address intellectual property concerns in AI training data?", "48581f7f-03f6-4ee0-abe0-09bdb7f54800": "What measures can be taken to prevent obscene or degrading content in AI outputs?", "66f09013-2126-4c82-bc9a-c3a11320b3d7": "How can harmful bias and homogenization be mitigated in AI systems?", "a7a8bc83-2e72-4a24-a793-f1b816f0c283": "What are the risks associated with dangerous, violent, or hateful content in AI-generated outputs?", "cfb4d915-c088-4618-925e-02e974b919bd": "How should organizations re-evaluate safety features of fine-tuned models when risks exceed tolerance levels?", "ae31cf33-efff-4297-a26b-ea5db0b92c1c": "What steps should be taken to review GAI system outputs for validity and safety?", "c8138f61-21b5-4802-ac6d-f18233410054": "How can organizations ensure that generated code does not lead to unreliable downstream decision-making?", "0f1e8318-43b1-4523-8576-17ceb1fc8061": "What are the best practices for verifying that GAI system architecture can handle and recover from security anomalies?", "25ff123c-f46a-4669-9903-16149a4ec2d2": "How can confabulation and information integrity issues be addressed in AI systems?", "1e6c80b3-721c-45ae-88a6-cf0f8ced7156": "How can organizations effectively leverage feedback from boards or committees when deploying GAI applications?", "df6054be-5a75-416a-9eaf-0be1a05ee1d6": "What are the best practices for using human moderation systems to review AI-generated content?", "288339c7-c00a-4dd4-aa6b-e2002ba889ce": "How should organizations align human-AI configuration policies with socio-cultural norms?", "deaad193-bda5-46ff-afa9-72206425c873": "What criteria should be used to evaluate the performance of pre-trained AI models?", "2d47d0ae-c76d-4ae5-a638-a6517c6220ba": "When is it appropriate to decommission or retrain pre-trained AI models?", "76fab1b0-0e24-4c35-a7ed-8d49cfe2720b": "How can organizations determine their risk tolerance for AI deployment?", "495b8ac6-a421-46e9-a6c3-985e29b71272": "What are the key considerations for integrating third-party pre-trained models into an organization's value chain?", "9326e08e-8852-4d72-a983-7e09ff35af6e": "How can human moderation systems be configured to handle AI models that perform poorly?", "a4b17ec5-fc35-40d7-9721-d18501274964": "What role do organizational boards or committees play in ensuring information integrity in AI applications?", "9bc8756b-e0e6-4b2c-8ff9-a26618ca918d": "How can organizations monitor and manage the risks associated with AI deployment and operation?", "fc3b2287-133b-4a7d-beb3-436fe108fc3f": "What are the best practices for reporting AI system errors and near-misses?", "b35cb75c-71fc-4af1-9c57-c5ae6ccd8cb3": "How should incidents involving AI systems be communicated to regulatory bodies?", "381e4eab-6b5b-4ca7-8571-31aba3dfe943": "What policies should be in place to track negative impacts of AI systems?", "08bba123-7cf2-4473-830e-9c28dc6dbce4": "How can organizations ensure information integrity when dealing with AI confabulation?", "ff25d5f3-7350-498b-8341-45dae4e79977": "What are the legal requirements for reporting AI-related incidents?", "8ae5b2b8-aeff-4c5e-aa72-6924b2fc4dd3": "How can companies establish effective procedures for recording AI system errors?", "c1f383d3-687b-4a57-a98a-c2f2212368bf": "What steps should be taken to maintain information security in AI systems?", "a8540ee7-471f-42c8-8ff5-4d74af3e9e84": "How do you handle confabulation in AI systems to ensure accurate information?", "abee8f0e-95b6-4a66-9584-2fa2c87344cd": "What are the key components of an incident communication plan for AI systems?", "86a7086e-9edd-4247-96a7-f4bd37a9d20e": "How can organizations track and mitigate the negative impacts of AI systems?", "582fa583-c146-4227-a529-e7428ecadbd5": "What are transparency artifacts in AI, such as system cards and model cards?", "f5ab7c6f-0d8c-4379-a524-ea0abad40378": "How do transparency artifacts help in managing third-party AI models?", "62dbacb4-0a6c-437d-b130-68d38e4fb182": "What is the importance of monitoring pre-trained models in AI systems?", "a8ba6c23-7fb6-47bc-8dcd-4242dca46afe": "What are some techniques used in explainable AI (XAI)?", "495f990c-cfe1-4bd2-99e7-728aaca889b1": "How can explainable AI (XAI) techniques mitigate risks in AI systems?", "dbf021da-491b-4d03-b6c9-7641362406aa": "What is model compression/distillation in the context of explainable AI?", "f2e9d547-10c8-470f-be55-7919d3b9fc76": "How does gradient-based attribution work in explainable AI?", "333ba50b-1816-4a01-9ec5-0dc8942bd96e": "What is the role of counterfactual prompts in explainable AI?", "f743f398-d354-4757-a791-669763758105": "Why is it important to document adaptations of pre-trained models?", "493410a8-8da9-4c05-af25-02344ce5fb36": "What are the risks associated with unexplainable generative AI systems?", "d43b5165-b424-4efb-8ac5-c70839068a9b": "What are the key components that should be included in the reporting of accessibility evaluations for sensitive domain systems?", "e745cebf-169d-42f5-a769-451d4e947df1": "How should training and governance procedures for technologies in sensitive domains be documented?", "48cc0ef1-0635-4131-ad9d-a75b6f87ba6c": "What kind of information should be included in the documentation of goals and their assessment?", "77a87b11-faf6-450d-bc8c-8fc3bb450471": "Why is it important to consider the data included in the reporting of accessibility evaluations?", "32dbfbc4-6fc4-4307-879f-1a14277108ac": "How can the governance of reasonable access to technology be documented effectively?", "d129f587-db8c-42b2-b15b-f48854e829b5": "What are the benefits of providing reporting in a clear and machine-readable manner?", "595e4aba-2967-46e1-9276-4619eaf23ee3": "What are the best practices for documenting training procedures for sensitive domain technologies?", "70ad54f1-132d-4b05-b0d5-ec776fc6a092": "How can organizations ensure that their accessibility evaluation reports meet the required standards?", "e782da3f-efb4-4a2b-952d-815b7704c1c2": "What challenges might arise in documenting the governance of access to technology?", "d7780233-e970-44f8-941c-d04776c461f0": "How can the assessment of meeting goals be effectively reported in accessibility evaluations?", "411f2cb4-761f-4481-acc9-3379b98be822": "What are gradient-based attributions in the context of GAI risk measurement?", "aff655e4-7805-4005-96dd-97e57a4ed1f6": "How does occlusion/term reduction help in improving the transparency of GAI systems?", "b2cca45d-920c-4cfe-81d7-5dfa18ea4ac3": "What are counterfactual prompts and how are they used in GAI risk assessment?", "c834f9d2-569f-4a49-aecb-ae1382201dda": "Can you explain the role of prompt engineering in mitigating risks associated with GAI systems?", "15467914-2915-4097-a975-a2b7a2bf6e0d": "How is the analysis of embeddings useful in measuring GAI risks?", "7233a36e-44dd-4945-bdca-92ff30a47933": "Why is it important to assess and update risk measurement approaches for GAI systems regularly?", "22334989-4055-455c-a95e-7e517df2a381": "What are the benefits of using standardized measurement protocols in GAI risk assessment?", "d818454e-443f-4926-8398-9edbf7ce1b23": "How can AI red-teaming contribute to the risk measurement of GAI systems?", "895f4711-def6-4b59-833c-f71a070facef": "What is the significance of independent external evaluations in the context of GAI risk measurement?", "c4d00e1c-836a-4ceb-973d-e0df3779b23f": "How do policies, procedures, and processes help in detailing risk measurement for GAI systems?", "1057d1c5-3ac4-4d8c-9193-566dac0f5640": "How do new surveillance technologies in education disproportionately harm disabled people?", "8c3f757b-977d-4050-b35d-aea49c010cf6": "What are the impacts of surveillance technologies on disabled individuals in the workplace?", "1468fc8a-bccd-4e2e-a99c-fd18b4bd12c2": "How does policing with new surveillance technologies affect disabled people?", "ff6dc571-3da6-4cb6-ab29-a41494392ed0": "What are the specific ways in which health care surveillance technologies harm disabled individuals?", "5e523726-a9d1-4807-9295-3881cd46f457": "How can we mitigate the negative effects of surveillance technologies on disabled people in various sectors?", "83c676ae-600e-4c27-98f4-24e784b1d7e9": "What are some examples of ableism in new surveillance technologies?", "c2b9fec3-5182-456a-8d05-894e91037f8d": "How does the Center for Democracy and Technology suggest addressing disability discrimination in surveillance?", "0da8dd83-5ddb-4544-a4ca-0fe64ff97e5d": "What are the ethical concerns regarding the use of surveillance technologies on disabled people?", "3d03cf3e-8e29-4424-b5ee-db3ce2aef10c": "How can education systems ensure that surveillance technologies do not harm disabled students?", "9466ba73-2db9-4dbb-a45c-9cf5fc4b9233": "What policies can be implemented to protect disabled people from the harms of surveillance technologies in the workplace?", "c8753999-1abf-4fe0-b602-96c7badbe1b8": "What is the main argument presented by Tirrell in \"Toxic Speech: Toward an Epidemiology of Discursive Harm\"?", "b146064b-3808-4dc7-ae9c-1fd32c51462d": "How does Tufekci address the challenges of computational agency beyond Facebook and Google?", "26296ada-303b-4757-99c1-d0b666b5ebe6": "What are the key findings of Turri et al in their study on AI incident documentation practices?", "22a9a1b9-5625-453a-8f38-7e6e1faece16": "What concerns are raised by Urbina et al regarding the dual use of AI-powered drug discovery?", "456281a3-2fc9-42d0-aaee-b9e644b01898": "How do Wang et al evaluate the energy and carbon considerations of fine-tuning BERT?", "d0fe0b08-146c-467e-8042-9160ccec66de": "What is the purpose of the \"Do-Not-Answer\" dataset introduced by Wang et al in their 2023 study?", "1c65bc00-7698-4aac-ac75-f4cf0a56d7d7": "How does the concept of discursive harm relate to toxic speech according to Tirrell?", "3b23f18c-6948-482c-ad4b-4094da577801": "What emergent challenges of computational agency are highlighted by Tufekci in her 2015 paper?", "4474dccd-e072-4606-bf97-01a59797d81c": "Why do Turri et al believe it is important to improve AI incident documentation practices?", "bc98f064-db21-492e-8cbe-6bb73bfc8422": "What are the potential risks associated with AI-powered drug discovery as discussed by Urbina et al?", "660c7ba7-9614-4425-afbe-8e9230f9e5a3": "What are the main risks and harms associated with automated systems discussed in the panel?", "3d79fef1-7ec1-4629-8dbb-c4c88e55354f": "How do automated systems impact consumer rights and protections?", "19a6f91d-d99b-479f-974f-60046204684a": "What insights were offered regarding the use of automated systems in the criminal justice system?", "926d89a3-3c21-4df7-9dfd-ced249915ecb": "How can automated systems promote equal opportunities and civil justice?", "8aee8607-430b-469e-86d5-4232adc7e194": "What are the policy opportunities for 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"66d10b11-4e1c-4323-90e6-162723085f38": "What are some of the reporting elements included in the framework for machine learning systems?", "be510be5-869b-457f-8999-878fdb0b09ba": "What federal laws require lenders to notify consumers about certain credit decisions?", "e5d619fa-49b5-435a-adc3-565acb71c415": "What is an \"adverse action\" notice in the context of credit reporting?", "c5c5e007-9f35-46e7-aa48-ce8e0f608d5b": "Under the Fair Credit Reporting Act, what must be included in an \"adverse action\" notice?", "5437738f-c791-44c0-bb4c-acc4b6d2ff09": "How do the Fair Credit Reporting Act and the Equal Credit Opportunity Act protect consumers?", "cfe9c2ed-5bf9-478c-89c7-794e93148715": "What are disparity assessments in the context of machine learning systems?", "48425d12-7cb9-4383-b947-e6e9566b9e7e": "Why is transparency important for machine learning systems used by companies and non-profits?", "692bc9da-55ae-42fc-b205-f3bafca5a068": "How do safety evaluations contribute to the 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initiatives does the International Association of Chiefs of Police undertake to improve policing?", "d7d6e108-130a-4ab9-915e-d9ee5a20c635": "What are the key functions of the International Biometrics + Identity Association?", "b9ccc9b0-0028-4ba4-bbb6-5233720451b2": "How is IBM (International Business Machines Corporation) involved in AI development?", "609aa6d8-e41e-4fc7-83a5-2cf32901c497": "What humanitarian efforts are led by the International Committee of the Red Cross?", "2e407155-794d-4127-a539-3071466d8964": "What is the mission of the Lawyers\u2019 Committee for Civil Rights Under Law?", "b3a14e62-cbd5-446d-bce9-c73acd2baea8": "What are the main challenges in mitigating bias in AI systems?", "236f0306-90cd-49d3-8ec0-6a0cba6252a5": "How do datasets contribute to bias in AI?", "e08d701d-e244-404e-a35d-5e7a74b18eb5": "What are the best practices for testing and evaluating AI for bias?", "a0516a4f-2bd5-4c53-9ddc-49b6d709e2ef": "How can human factors influence bias in AI?", "18f7d41a-eacc-4b77-bff7-dd63adf0b0e5": "What is a socio-technical perspective in the context of AI bias?", "b1ff8e57-f9c8-4c9c-b80d-0b8cab8414d0": "What preliminary guidance is available for addressing AI bias?", "99396743-8ac7-4e6a-8174-ca002a8bc22c": "How can algorithmic discrimination protections be implemented in AI systems?", "e1119908-110c-41ef-a480-2c1db95e1206": "What role do datasets play in algorithmic discrimination?", "59a7e5e5-28fd-40e7-9eef-7a8c47988333": "How can we ensure fair testing and evaluation of AI systems?", "f6fccc6d-ae1d-4832-a6a1-6a02d216d0ef": "What are some strategies to manage human factors that contribute to AI bias?", "2ad0d5f2-d9ad-4172-9854-643c6a273f4a": "What are the ethical considerations for human subject experimentation in medical and scientific research?", "d378ac98-249d-4ce1-9350-5282c48770f8": "How can organizations ensure the quality of data in sensitive domains?", "7dee64d8-bf12-4366-bc43-ff71821a2047": "What are the consequences of using 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"8dbba1cb-269d-4957-b4fd-308f00b91882": "What are the implications of AI cameras punishing drivers for mistakes they didn\u2019t make?", "fcbbdd00-85b9-4396-9b7a-5de417c1179f": "How have Amazon drivers responded to the AI camera system?", "4d05c32c-5866-4426-a745-2d2c554a5691": "What steps can be taken to improve the accuracy of AI cameras used by Amazon?", "7f590c18-47a2-438e-977a-cdd098e7fa86": "What are participatory engagement methods in product development?", "edde2af3-d243-4ef8-869b-bbc0626bc609": "How can focus groups with experts be used in AI development?", "541450fd-838a-4b58-94cc-20e3944691ea": "What is the role of small user studies in evaluating new products?", "b0e29ede-db9c-4382-943f-c21b4946bdb7": "How do anonymous surveys help in gauging reactions to specific features?", "e6832258-3b72-4cb6-a1d3-f906eb781da4": "Why are participatory engagement methods often used in the early stages of AI development?", "b6d68612-46b8-42cc-ab3e-31be5702199b": "What is the difference 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2022?", "3cd1a4cc-ca2b-4d1e-8ada-446a7c42cb20": "What customer service solutions are recommended for small businesses according to Business News Daily?", "182886ff-5412-4948-8295-701e0d7fbfe1": "How can small businesses improve their customer service based on Sara Angeles' article?", "37631ff1-592b-4472-94a4-2ce2caf8eafc": "What are the benefits of co-intelligence between robots and humans in customer service, as discussed by Mike Hughes?", "75e3d9c3-d911-48df-9ddb-8914d28e9008": "How effective are bots in customer service according to the Forbes article by Mike Hughes?", "421b5545-cea3-4524-bdc8-d3a22c30dd6c": "What strategies can businesses use to get the best out of their bots in customer service?", "83379563-52c0-4b59-b40b-f4418017f011": "What are the latest trends in customer care as reported by McKinsey & Company in 2022?", "d76b947b-8f88-4163-9e86-05a0d2e86981": "How has the Biden-Harris Administration's approach to Health Care Navigators impacted the HealthCaregov Open 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minorities in AI-generated images?", "30e3bc0e-5f22-4216-a2c0-f27f861b5634": "What are the consequences of biased or stereotyped outputs from image generator models?", "1b6a2ed0-d374-4c90-9b2f-26802ca2cc85": "What are examples of sensitive domains that require enhanced data protections?", "6c6d9102-09bf-4244-b8ba-21686bf078c4": "How do sensitive domains impact human rights such as autonomy and dignity?", "397d1460-bd65-4980-8b60-2ff58fcfc82e": "Why is health considered a sensitive domain?", "bc39145c-d1dd-4e69-a545-04944b0249af": "What makes family planning and care a sensitive domain?", "c567b788-ba2a-471d-8a61-f8acc8154f67": "How does employment fall under the category of sensitive domains?", "29011969-35fb-4185-9b93-65a5945bf067": "Why is education considered a sensitive domain?", "5f790da9-449c-41e8-865a-7f51afe460fc": "What are the implications of criminal justice being a sensitive domain?", "cd10682a-f510-462e-b688-e6038e4d2166": "How is personal finance classified as a sensitive domain?", "20c5ca9a-d0a2-4fa0-b02f-0f7351890b70": "How do societal norms influence what is considered a sensitive domain?", "7d213d18-b9dc-4003-bf54-21ec8dfb8397": "What is the role of surveillance technology in sensitive domains?", "575386df-5852-4b96-98b2-146127539141": "What are the established security measures to assess vulnerabilities and threats in AI systems?", "f0b324e0-dd60-4f57-b879-e56ece38360e": "How can backdoors and compromised dependencies in AI systems be identified and mitigated?", "5d3ecf42-2ce1-468b-9dbf-e4bbc5707389": "What are the best practices for benchmarking AI system security and resilience?", "e4d68479-8a79-4216-bc1a-4c8b156f3b37": "How do industry standards for AI system security compare to state-of-the-art methods?", "fc9490b3-396e-4ac3-95ef-80d13f6cf544": "What methods are used to ensure the integrity and security of AI-generated content?", "1cd90900-c572-4975-b7b8-fc93f4189d8e": "How can data breaches and eavesdropping be prevented in AI systems?", "2e2511f7-776d-400f-99e8-22c70ecc04d5": "What are the common threats to AI system security, such as model theft or exposure of model weights?", "e3b81075-8ba7-49f1-a7d2-87168a99617e": "How can user satisfaction with AI-generated content be effectively measured?", "e5339170-f4f7-4d0f-851e-a4b684f4de56": "What are the implications of man-in-the-middle attacks on AI systems?", "db8ab762-0912-47d7-9d30-648164bab39b": "How can the security of AI inference and extraction processes be ensured?", "59c7ac21-d712-480d-b1f2-638dff0439e1": "What are the potential risks of using technology in social welfare systems as discussed by the panelists?", "00e72162-956b-4ed9-94b5-b0ce264a828b": "How can digital ID systems impact the efficiency and cost of social welfare programs?", "0dcfc118-6d07-45b7-9542-8c8fa5036354": "What concerns did the panelists raise about the burden on individuals interacting with new technology in social welfare?", "60fe80fd-12ab-4a19-acb4-511d6cade220": "How can feedback loops in technology systems reinforce inequality according to the panelists?", "6152c7f7-4267-40c0-a522-620e1574f605": "What are some methods suggested by the panelists to mitigate the harms caused by technology in social welfare?", "bc2942af-52bd-4fbb-816d-9db9e02d78c1": "Why is community input important in the design process of social welfare technologies?", "ba3309a2-8a2a-4ac9-a89a-5df5b997a37c": "What role does data collection play in the potential harm caused by social welfare technologies?", "8f11cb0a-3059-4f8b-991a-c534983d2ab8": "How can individuals opt out of technology systems in social welfare programs?", "18631367-2871-45d9-8b6f-049eee6e413e": "What are the benefits and drawbacks of using technology for fraud detection in social welfare?", "da3446ed-9014-4635-b576-0dc495e48111": "How can the implementation of technology in social welfare systems affect government agencies and the people they serve?", "bf7e5553-71b4-4912-8f36-d5596c343802": "What is the Blueprint for an AI Bill of Rights?", "99d4fab5-34b6-4be5-ae63-ed96a8f6f688": "How are federal agencies ensuring AI systems comply with the Executive Order?", "cee03924-6fe3-43d2-8378-250f3240ea48": "What are the key principles outlined in the Blueprint for an AI Bill of Rights?", "1ccab29f-bc4b-428c-98d7-f783de1b512b": "How does the National Highway Traffic Safety Administration ensure vehicle safety?", "e3ea9516-f177-4b9a-b7a2-f1e46892ec09": "What role do local rules play in the implementation of road safety measures?", "bc2b4942-0fd8-48fa-989a-4c49c46c7b96": "How can strong safety regulations enhance innovation in complex technologies?", "6c84c34b-2170-4b7d-b82c-331dd7539cbd": "What measures are in place to address harms caused by AI systems?", "278b5143-0278-4559-bf04-512ef1f0c323": "How are AI use case inventories being utilized by federal agencies?", "0059e842-db08-4e0a-a061-7d5f37511184": "What is the relationship between safety regulations and innovation in the automotive industry?", "ae4d086c-aee0-4107-8d11-6d98cd132c52": "How does the law and policy landscape for motor vehicles relate to AI systems?", "0f1efd9c-7fbd-4b7b-ab5b-c3e90282a9ce": "What is algorithmic discrimination and how does it affect individuals?", "067133f9-c096-431e-b340-aaafffcd7f18": "How can automated systems be designed to prevent inappropriate or irrelevant data use?", "f50ad4e5-8546-4e08-aa4a-2f9430c6ef48": "What steps can be taken to mitigate potential harms from automated systems?", "74155138-199c-4f03-8c74-36f550d07afc": "Why is independent evaluation and reporting important for automated systems?", "bc6e0508-7335-48f1-89e2-85a0b185e8d7": "How can the public access the results of evaluations of automated systems?", "8c0cd3e7-b416-4eef-9685-68b4a810756b": "What measures can be implemented to ensure equitable use of automated systems?", "90cd38de-1740-48c6-b5cd-21899eb63f8b": "How does algorithmic discrimination impact people based on their race or ethnicity?", "f5303ea3-19f1-4a4f-952a-803e65a5a0fa": "What are some examples of algorithmic discrimination in automated systems?", "4d896f9d-2d20-47a9-8054-3f5b528ef495": "How can organizations ensure that their automated systems do not contribute to unjustified different treatment?", "18fd587a-4be2-4840-9c67-9ea224d4de50": "What protections should be in place to prevent compounded harm from the reuse of data in automated systems?", "dfe37234-9ca3-43f7-a3e8-b86a80b04f3c": "What is the AI Bill of Rights?", "f23d3c7e-3ec7-4ff7-bdab-5cdac88803fa": "Why was the AI Bill of Rights created?", "702c8d56-ad6f-4de1-9926-285169f470d4": "How does the AI Bill of Rights aim to protect American citizens?", "be6e8191-35d3-4f3f-94a2-c509ba2c3e49": "What are the key principles outlined in the AI Bill of Rights?", "4f8e4872-d2dc-4de1-aea1-da76b4471020": "Who is responsible for enforcing the AI Bill of Rights?", "e614182a-3697-4fd6-9166-b61c28d345dc": "How will the AI Bill of Rights impact the development of automated systems?", "d01414e7-9f4e-4a8f-b650-88cbc28f03f1": "What are the potential benefits of the AI Bill of Rights for the American people?", "d6520c9d-85d3-4d22-81a2-22649cf66c30": "Are there any specific guidelines for companies developing AI under the AI Bill of Rights?", "ec9b0344-0489-4878-b603-f0e89be5311b": "How can individuals report violations of the AI Bill of Rights?", "85e83a32-66ea-4124-934e-cc197072ddea": "What role does the government play in the implementation of the AI Bill of Rights?", "00bb38cc-b363-4224-9cad-242db0bd67bb": "What are the applications of General Artificial Intelligence (GAI) in CBRN information management?", "a221d1ab-5fd6-45a4-b6d8-8b93d9ab4bdd": "How can AI be used to detect and prevent the spread of obscene, degrading, and abusive content online?", "12a024fb-ee6f-4e56-a00e-3f762d802ec5": "What are the key considerations for data privacy when deploying AI systems?", "857a98f9-c84c-4e60-a015-c7857dfc889e": "How can AI help in monitoring and preventing civil rights violations?", "77ca506b-f725-4298-bb8b-1192ff1727c0": "What tasks are involved in AI development and how do they differ from AI deployment?", "6ad116cd-414d-4fbe-9971-f3c0165700e9": "What governance and oversight mechanisms are necessary for responsible AI deployment?", "06c33b54-b7f9-4684-ae49-4ef790e2a2ee": "How can AI improve capabilities in handling Chemical, Biological, Radiological, and Nuclear (CBRN) threats?", "3af5e01d-6e1d-41c7-a864-f35d9f4c081a": "What are the ethical concerns related to AI in terms of degrading and abusive content?", "1e4703d7-50c1-48e9-9662-fd835aca738f": "How can AI be used to enhance data privacy protections?", "d84d75d8-f21b-48d5-87ba-40e65b40b8e5": "What roles do governance and oversight play in ensuring ethical AI development and deployment?", "dff03de3-cf16-47fe-8c62-7acc7396c8e5": "How is technology helping farmers grow food more efficiently?", "f5dd8a98-1cb1-46cc-9437-9e36b92e9027": "What role do computers play in predicting storm paths?", "4c8db1bc-307b-4041-a352-9f9af6cbb286": "How do algorithms identify diseases in patients?", "8ec278ab-326a-4b26-81cf-07a2748a5f1c": "In what ways is data revolutionizing global industries?", "8e131803-f72b-4edd-a60c-cdf1ae47f020": "How is American innovation redefining different parts of society?", "c4536521-f7e6-42da-876e-138c80d5af1d": "What are the potential benefits of these technological tools for society?", "28061b71-fa18-4a73-973b-595f5e9f23b5": "How is President Biden's administration addressing civil rights in the context of technological progress?", "6a32e6c5-5b4d-425c-9310-ac9e34058595": "What steps has the Federal government taken to root out inequity and embed fairness in decision-making processes?", "8b41d54a-0e4f-4063-9bfb-e5633ef01f3d": "How is the Biden administration advancing civil rights, equal opportunity, and racial justice in America?", "620c90fd-87a8-4508-aef6-49ce040c25b3": "What are the urgent challenges to democracy that President Biden has spoken about?", "b2771425-f693-4b11-8a2c-cd5ece2a9f39": "What are some examples of sensitive data that have changed over time due to societal norms?", "d5648e81-154d-4e7a-9f98-89e26af03143": "How do societal norms influence what is considered sensitive data?", "8c9a7763-5902-48de-9624-1fe4f06180aa": "Why is it important to understand that sensitive data can change over time?", "71023f86-db69-4922-aa49-0c7884cda337": "Can you provide historical examples of data that were once considered sensitive but are no longer viewed that way?", "95e33fee-d6c2-4676-8f91-f97b88f4e897": "How do organizations adapt to changes in what is considered sensitive data?", "c5122f36-0c06-4f80-9d69-d7b5b7ba4c0c": "What role does context play in determining the sensitivity of data?", "6eda9f1e-d41d-4951-aeeb-6e3163a690d8": "How can individuals stay informed about changes in what is considered sensitive data?", "1ee096ea-f4e1-48d5-8859-1d486e08313e": "Are there any legal implications when sensitive data definitions change over time?", "3908a945-dd75-4d68-b75a-c42acfd1c173": "How do cultural differences impact the perception of sensitive data?", "e20ddb14-9cac-4fc8-8013-cc39c4a8924f": "What are the challenges in managing sensitive data that evolves with societal norms?", "52b9675c-9516-452a-94a4-69f03f5c10d5": "What is a fallback and escalation system in the context of automated systems?", "f678bc09-26c6-49a9-838d-b7ed1c773949": "How can human consideration be proportionate to the impact of an automated system?", "56255088-9e23-47d6-b73f-3890da92fc7a": "Why is it important to have safeguards against human bias in fallback mechanisms?", "046fd2c8-285c-4ea1-b2dc-0acdba7f5f1b": "What are some examples of high-stakes decisions that might require greater human oversight in automated systems?", "7f889e3b-de8e-4bc4-895f-af886478d21f": "How can organizations ensure that their fallback mechanisms are accessible to all users?", "c66a77c5-9ed9-48c7-b414-54d06b37b5c4": "What types of training are necessary for staff involved in human consideration and fallback systems?", "14df2313-e73b-4475-9175-b15e327a4691": "How can the availability of human consideration be increased for automated systems with significant impacts?", "7442ff35-391c-4c27-821d-8246d671bdd3": "What are the potential consequences of not having an effective fallback and escalation system in place?", "6da33505-e013-4410-87b2-c06a8f9a986c": "How can the effectiveness of fallback mechanisms be tested?", "0c6a74d4-9976-4dac-82a0-85562c58e9fa": "What are some common challenges in implementing accessible fallback mechanisms for automated systems?", "90cdaeaa-2d23-47cc-9c62-a678caaff1fe": "What is the role of NIST in advancing AI technology?", "c94bb207-795e-4949-afb5-51060a4c898a": "How does NIST ensure AI is safe and trustworthy?", "aed91732-c782-4c41-b30d-74b4bb0bccdb": "What is the US AI Safety Institute established by NIST?", "9df72cbc-5cee-4e8b-a0f6-a71f2453c828": "How does NIST contribute to the 2023 Executive Order on AI?", "5fb78f30-b8ee-4a7c-9d4b-49a3d7203935": "What are the main goals of the AI Safety Institute Consortium?", "76bff3c9-e07b-42a2-a053-f2b1aaa03c51": "How long has NIST been working on AI research?", "aeb7622a-78ad-4d23-add9-376a60612c11": "What kind of standards does NIST develop for AI?", "11b4686b-199b-42c0-87ea-4cfdf61fc1a0": "How does NIST address privacy concerns in AI development?", "b80438a1-1067-4a5a-820c-4133f009d448": "What contributions did the NIST Generative AI Public Working Group make to the report?", "50466b56-2814-489e-a27c-db75ad0859de": "How does NIST ensure AI is fair and transparent?", "720b9aed-8f99-4d96-9c31-c592612cad56": "What constitutes sensitive data under the AI Bill of Rights?", "52379352-3058-4c02-8a14-bf94e6ff2793": "How is sensitive data defined in the context of AI technologies?", "a6730cb7-c308-49ef-976d-2cd8dae8fea7": "What types of data are considered sensitive for individuals who are not yet legal adults?", "eb718d42-c1f0-4bc4-b821-2f51d3d1c876": "How can sensitive data lead to meaningful harm such as identity theft?", "9d567b63-4cdc-4526-bc7c-9227afac30df": "What are some examples of sensitive domains mentioned in the AI Bill of Rights?", "c673db12-f99b-450f-b738-61159c6ee5c3": "How does the AI Bill of Rights address data related to criminal justice interactions?", "7d8746aa-a1a7-4dbc-bf5e-40f65e995b9f": "Why is biometric data considered sensitive under the AI Bill of Rights?", "449278d1-b673-4878-8c11-d1d5ab0d6db5": "What measures can be taken to protect sensitive data in AI applications?", "5969e8c6-02b2-4c2a-b739-bdc23cad38f9": "How does the AI Bill of Rights define the potential for data to cause financial harm?", "205446ad-e139-481b-81fb-2548db84a0e0": "What are the implications of handling sensitive data in AI systems for privacy protection?", "928e6923-bcf0-4580-ad02-7769964afe49": "What are the implications of digital surveillance in a post-Roe world?", "a1b627aa-a1ff-4a68-a3ac-2a726f36747d": "Why did the FTC sue Kochava for selling data that tracks people at sensitive locations?", "70fa19b9-7985-4eb6-9cc2-7bf86776c53a": "How does digital surveillance impact reproductive health clinics and places of worship?", "16562b7c-6b93-483f-a689-d28eab8e4aea": "What companies are being acquired by private equity firms that collect data on children?", "b86ef95b-cdcf-455f-bdc0-474aac5b35eb": "What are the concerns surrounding private equity firms collecting data on America's children?", "9aa09b13-c9c6-4729-8029-8b893a1772a7": "How does the collection of data on children by private equity firms affect privacy?", "c971ec0d-ff6d-4adc-8ce4-f31428e4b284": "What are the potential risks of data tracking at reproductive health clinics?", "85942b84-5c76-435a-b971-83296f24e8fc": "How does the FTC's lawsuit against Kochava highlight issues of data privacy?", "7a683ec1-c238-48c5-bf76-00845333806c": "What are the ethical considerations of collecting data at places of worship?", "aa558c0c-2ab3-40c8-bdd9-3daf1f4f43a0": "How does the job database classification of former Apple employees as 'associates' affect their career prospects?", "19703e97-9d93-49e6-864a-23847656346f": "What are the best practices for ensuring data privacy in AI systems?", "52e88558-d8cc-413e-80e0-9f094bf4270b": "How do you manage intellectual property when using AI models?", "6ad81596-3e02-481b-b7ac-73940d631df3": "What are the key components of AI governance and oversight?", "dd2e0e56-2211-4a81-9712-aecf2fda1a6b": "How can you ensure information integrity in AI applications?", "bcd77494-a31b-4fe9-b2c7-3876f1f5306e": "What are the different access modes for underlying AI models?", "83631b6a-fd3c-4582-973c-c108cbc54c76": "How do you handle sensitive data in AI projects?", "fa5423e6-cb1e-4043-af5e-e939741381e2": "What is the importance of value chain and component integration in AI?", "45fc2c2b-6bc0-4a8d-8731-dfa83c3ba355": "How do you configure AI systems to align with human-AI interaction guidelines?", "94cf27b3-d287-4e48-b4f0-1acdf891f42f": "What are the challenges in managing proprietary data in AI?", "47124446-7ae2-4444-8f9e-e86adddd76bc": "How do you oversee the tasks performed by AI actors?", "af389dfd-cca2-4851-9450-166e9fbd38d2": "What are the key technical and governance interventions needed to protect against the harms of new technologies?", "9bc603e1-c26c-4926-b91a-c8d4e1a57fbf": "How important is community input in the design and use of new technologies?", "be75402c-f043-4191-9c8b-7d5af25bef31": "Why is public reporting on crucial elements of technological systems necessary?", "0dc744a1-6026-46d6-aeb0-8af84f722ae7": "What are better notice and consent procedures, and why are they important for privacy?", "66f03050-aedc-47b1-aa15-51450e4329a2": "How can users opt-out of using certain technological systems and revert to a human process?", "9c5cf2e4-1467-4a23-8857-28214677eca8": "Why is it important to provide explanations of decisions made by technological systems?", "710fdf52-6834-4b9d-9ce6-a653d5cece1b": "What kind of training is necessary for the proper governance of new technologies?", "c505559b-8a65-4f47-80ef-b510d054137a": "How can we ensure that technological use cases are genuinely related to their goal tasks?", "b0c53b5c-f74e-4529-a8d6-a123ed691081": "Why is local validation important for the effectiveness of technological systems?", "86fad521-a1f8-4c03-9313-ef0a9cee5091": "What is the role of third-party audits in maintaining the accountability and validity of technological systems?", "55bec949-76bc-49c1-a3ae-5f874eedfddc": "What are the risks associated with the synthesis of CBRN materials?", "9cd11b1f-87d1-484b-aba4-b76a5cb30945": "How can confabulation in AI systems mislead users?", "9ee178ca-364a-4792-8ee5-68de0f17f7cc": "What measures can be taken to control the spread of dangerous, violent, or hateful content online?", "616332c3-0795-4741-9e22-e94ffa2fcb13": "How does the unauthorized use of personal data impact data privacy?", "d00c3c3b-c827-4205-bc58-f5520ba6e148": "What are the potential consequences of de-anonymization of biometric data?", "bf6e3576-bc85-4045-a9ec-7701f2ba852c": "How can access to CBRN information be restricted to prevent misuse?", "3a2a0084-eefa-406c-b6a6-ae09a47d2c23": "What are the challenges in detecting and preventing confabulation in AI-generated content?", "3139865a-00dd-4da3-9038-84cb5a1b8b12": "How can online platforms mitigate the risks of inciting or radicalizing content?", "ef18f0e4-616a-4bde-9199-8407daad074d": "What are the best practices for protecting sensitive health information from unauthorized disclosure?", "65c26694-76cc-42b2-9982-8baf476bbaed": "How can individuals protect their location data from being leaked or misused?", "ca38f0f2-707f-4776-8565-5a88ac901073": "What is confabulation in the context of GAI systems?", "dc4c667a-b953-456e-a31d-8b4221f41335": "How do confabulations differ from hallucinations or fabrications in GAI systems?", "c90a6481-11b9-4db8-b24d-cbb9f232a4a5": "Why do generative models like LLMs produce confabulations?", "f989e408-3f17-4129-8bd2-87ae2ceecc72": "Can confabulations occur in all types of GAI outputs and contexts?", "dac82b9b-8e84-414d-aafc-7f3764ca2b23": "How do statistical predictions in generative models lead to factually inaccurate outputs?", "df4dfdd7-6c4c-4dde-b6dd-5123571b1254": "What are some examples of confabulations in GAI systems?", "5a88e70b-4815-451a-bc8f-e1606c9f23e7": "How can confabulations affect the reliability of GAI-generated content?", "9882e344-3c67-494a-b083-c0b2ae59a9df": "What measures can be taken to reduce confabulations in GAI systems?", "26c3c033-6002-4d01-8f46-96bad11d3572": "How do confabulations impact the consistency of GAI-generated statements?", "6536996f-b790-440e-afc7-66774db4a2e3": "Why is it important to understand the phenomenon of confabulation in GAI systems?", "f9e8bebc-884c-4775-95e1-78d70dc642b2": "What are the best practices for verifying information sharing and feedback mechanisms in AI systems?", "6a36fd5d-98db-42d5-b0d4-493641747d7b": "How can organizations ensure data privacy while sharing information about AI system impacts?", "d4f86701-19bc-43eb-9713-57eb57e073f6": "What steps should be taken to conduct an AI impact assessment effectively?", "ff6fe932-7482-44fc-bd67-812520e17bcf": "How can feedback from affected individuals and communities be integrated into AI governance?", "830c3554-63ea-4a61-a4f9-95e5c8297675": "What are the key components of an effective AI governance and oversight framework?", "621c0613-588a-4422-951a-45a7ed78fca5": "How can organizations prioritize feedback from external stakeholders regarding AI risks?", "df860556-2e58-4780-972c-1293c0231372": "What resources are necessary for effective outreach and feedback processes in AI system development?", "9c78e9c5-3af3-4520-a602-f9a45cebb1a3": "How should interactions with GAI systems be documented to ensure transparency?", "359d8ba9-c8b2-4d18-b5c2-9c0369390b86": "What are the potential risks of harmful bias and homogenization in AI systems?", "e1de377f-ddbf-4599-99e2-116dc45fac8e": "How can organizations address the issue of confabulation in human-AI configurations?", "e5df3265-2f97-4196-b75a-ab39e66e7b97": "What are some examples of time-critical systems where immediate human intervention is necessary?", "ae852f4b-1551-4734-b962-337bb0060682": "How do automated systems impact the criminal justice system?", "5ce6cbf8-e3c8-414e-8e92-59e44f212a1f": "What safeguards are necessary to prevent unfair outcomes in automated systems used in sensitive domains?", "9a8e63e5-0caa-4533-b223-17d6c3c56133": "Why is human oversight important in systems that use automation for pre-trial risk assessments and parole decisions?", "fee74500-d0b9-468f-a6c0-cbb66d324f73": "How can automated systems in healthcare lead to dangerous outcomes without proper safeguards?", "7e4ebd6f-c29f-4c5b-a9e6-c00489ace11f": "What are the potential risks of using automated systems in employment and education?", "cf2fab83-75d6-4fea-a72d-449833ab78e8": "How do existing human processes complement automated systems in providing public access to government benefits?", "bcb8ba55-d026-4851-a522-40e9b1e175af": "What are the benefits of having a building manager available when an automated card access system fails?", "f89691af-5a2e-4c6b-8894-fd6d9cd424b7": "In what ways can automated systems in sensitive domains be made more accurate and fair?", "6c7e2aa2-558c-4280-93b7-bf73de34e57b": "Why is it important to have fallback options when using automated systems in critical areas?", "9f5142e7-fda2-481b-a08d-fddf4197454e": "What are the main findings of Northcutt et al (2021) regarding label errors in test sets and their impact on machine learning benchmarks?", "0cdcb840-24f9-49b7-b4b6-bd409bb4d50a": "How does the OECD (2023) suggest advancing accountability in AI to manage risks throughout the AI lifecycle?", "4dfa9162-0bd0-4926-a27a-2fe9231160ed": "What are the key points discussed in the OECD (2024) paper on defining AI incidents and related terms?", "49ca8dea-a08f-410a-a643-8e37fc896455": "What information is provided in the GPT-4 System Card released by OpenAI in 2023?", "4636292e-8f3e-4711-a175-b28428d0eaa9": "What technical details are covered in the GPT-4 Technical Report by OpenAI (2024)?", "69456d83-d8c3-4d1c-bd31-704d2c934902": "According to Padmakumar et al (2024), how does writing with language models affect content diversity?", "d62ca080-832e-4f4d-960d-bf8bb0d1b97e": "What examples, risks, and potential solutions are surveyed in Park et al (2024) regarding AI deception?", "fb2ddd6a-239b-4b2f-a336-f921a876390c": "How do pervasive label errors destabilize machine learning benchmarks, as discussed by Northcutt et al (2021)?", "9208081d-3da9-46db-b27d-f25ed1c64ad2": "What governance strategies does the OECD (2023) recommend for ensuring trustworthy AI?", "edb639b7-e492-4442-a339-62b5e921ceb2": "What are the implications of AI deception as explored by Park et al (2024) in their survey?", "572c1b8f-43fc-46ab-ac02-ef9756b67234": "What is the importance of proof history in AI content management?", "5e70d1eb-366b-403f-b833-9bb92e6a6cc5": "How does version control contribute to transparency in AI systems?", "f9e5f377-fe4c-43e8-8cc5-f004e49964e9": "What methods can be used to ensure traceability in AI lifecycle management?", "be867fe3-bca3-4b2b-9a5e-471f230b333d": "Why is user testing crucial for verifying the adequacy of GAI system user instructions?", "4b9a0a17-252c-4972-9be3-1b4156f5b5ce": "What are the key components of Human-AI configuration in AI systems?", "0f22a8c0-7a87-4416-a640-3c2187b8aa3b": "What tasks are involved in AI deployment?", "338a84b7-78f1-442a-8e90-093c313eceb1": "How is AI impact assessment conducted?", "bd811679-d8f6-4568-8799-aa826cd0ca8d": "What roles do domain experts play in AI operation and monitoring?", "6015d9b2-454a-4af5-9a8e-ac87189a84e1": "What does TEVV stand for in the context of AI systems?", "dc4d23d4-5c52-47f4-b5b8-01c23fc3bff9": "How can robust version control systems improve information integrity in AI?", "a6399ec7-f330-4390-8da1-35f4821069f7": "What are the safety and efficacy purposes of notice and explanations in automated systems?", "ec418640-346c-4981-a095-cbed724bdd60": "Why is it important for the American public to know if an automated system is being used?", "7feb0289-a3ca-4a4b-9809-7ff2b8a6518f": "How can clear, brief, and understandable notice help achieve protections in the framework of automated systems?", "c7d1871b-b9ea-4a5f-9ab2-e5b06fe26a8c": "Why are the decision-making processes of automated systems often opaque and complex?", "1f235bf9-1d62-49c3-9f64-b74ff53e1c0c": "What challenges do explanations of automated system decisions present?", "f370e6a8-32c6-4260-8fa8-013612614ab1": "Why should explanations not be avoided in the context of automated systems?", "ee9515a6-b640-4034-98fb-4a5837748cf7": "What is the importance of clear and valid explanations in automated systems?", "745e45f4-bba9-45ec-a7de-e6ad0e0e47e1": "How can experts verify the reasonableness of a recommendation made by an automated system?", "a02fa5da-7bd9-48d0-ade1-35bcb7529e09": "What are the potential harms of not informing the public about the use of automated systems?", "4a54ea01-870a-4fe8-aa51-bbdd95af1a67": "Why should clear and valid explanations be considered a baseline requirement for automated systems?", "d9589a42-1bfd-4e7f-b849-f21901e4405c": "What are the key expectations for automated systems regarding data privacy?", "a2cf57d9-906a-4fa1-83ca-9bcc8e64edbd": "How can individuals access and correct their data collected by automated systems?", "6bb0aeee-f203-4ae1-bdb1-ef25d1fcd53a": "What steps should entities take before sharing data with other entities?", "168e18c4-5764-40f7-83a7-4648c98b69c9": "How can users know who has access to their data in automated 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"6a18c1c1-6ac2-497c-a1fe-11422ba30b35": "What legal protections govern federal government surveillance?", "0af459fc-739a-4dd4-8b24-8e56ff57fd4f": "Why is it important to minimize data collection?", "8d37a2d1-6bd5-4294-8e51-2cadcc1361ac": "How can improving security practices protect consumer privacy?", "d141a6e7-cd0a-4576-a702-58134cba4442": "What are the risks associated with data aggregation by data brokers?", "940504a7-7a40-4be4-be3c-175d09bb3ccb": "How does data harvesting breed distrust and anxiety?", "2c185373-e28c-400c-a25c-f72dfe3eaa57": "What are general fairness metrics in machine learning pipelines?", "35d3df9b-ca04-45d6-ba61-910781efea5a": "How can demographic parity be applied to business outcomes?", "9dc2b214-8912-4afb-9003-08f83e541c16": "What is the significance of equalized odds in ML fairness?", "a5eacbd0-3001-4167-8925-1156e278be54": "How do you measure the prevalence of denigration in generated content?", "fbb7532d-4e3e-41f8-8fa9-f7b5a02d5cf0": "What are some methods to identify harmful bias in GAI systems?", "a9a83f45-168b-4db5-ace9-45e7fc8c91b9": "How can custom, context-specific metrics be developed for ML fairness?", "3d684fd5-d832-42dc-b175-14f788a2e83f": "What is the role of domain experts in creating fairness metrics?", "fd5250fe-6121-425e-b4d1-c8e0bb203d19": "How can potentially impacted communities be engaged in assessing GAI systems?", "08d9cafd-06aa-44de-ba02-3e37b37a6b17": "What are the implications of harmful bias and homogenization in AI?", "98218ea7-de37-4779-8228-a2bbdb9ff990": "How can environmental ecosystems be affected by GAI systems?", "3a930566-71ec-465c-b726-c04b4278a904": "What are the key characteristics of trustworthy AI?", "f5324885-70fb-44aa-abcc-bacc277ed26a": "How does information integrity impact the trustworthiness of AI systems?", "48616ea8-c86b-4f86-aa5b-e94d1bf34068": "What does it mean for AI to be accountable and transparent?", "db5d6aab-79c3-433c-9530-afa6fd56678c": "Why is it important for AI to be 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"ddbf64e7-c5b6-434d-8d6e-31d1e5d33d28": "Why is version history important in AI incident management?", "4a4cbdcc-49b2-4fb2-8c24-812bca763c37": "What role does metadata play in the analysis of AI incidents?", "1c1c0ea6-3ed1-421c-a55f-e58d82db9618": "How can inconsistent access control affect the distribution of content through plugins?", "62ddbc5e-ccb4-4713-b294-20cbbd2eb010": "What are the benefits of regular information sharing among AI Actors?", "ffd63cbd-ea55-4aad-aeaa-0dbe6fa096c0": "How can insufficient access control be mitigated in plugin distribution?", "483b6c63-303b-4f23-8f34-5b22a4ec2765": "What documentation practices are essential for smoother information sharing in AI?", "ac189b5e-6349-44af-bf0f-702798289347": "How can AI Actors use change management records to respond to incidents?", "8a3d3981-24a8-498a-b509-25543fd6afeb": "What are the challenges of maintaining consistent access control in distributed plugin systems?", "638b3c99-e6cb-49bb-95c2-f267b2d1ec00": "What are the risks associated with the validity and reliability of GAI systems?", "f0977b5a-0de8-435b-bfee-e6a457db0442": "How do measurement gaps between laboratory and real-world settings affect GAI systems?", "d2628c21-64b0-4b61-a595-7097a4f233c5": "Why do current testing approaches for GAI systems often fail to assess real-world impacts?", "17c050f3-312d-46b8-b066-2bf66ab0142f": "What are the challenges in estimating the ecosystem-level risks of GAI?", "1116721c-2698-4938-a6bb-f96c2698380d": "How can prompt sensitivity and context heterogeneity exacerbate measurement gaps in GAI systems?", "68367977-e97f-4f35-a78a-63620dbd4fb8": "What is the role of structured public feedback in evaluating GAI systems?", "4770227b-6fd3-4a08-93e2-eac625aa3e2f": "How can structured public feedback help calibrate traditional measurement methods for GAI?", "a50d0a5a-b180-4209-b057-8a3ce7ca5c8a": "What are some examples of structured public feedback for GAI systems?", "e538cb20-92e5-427f-b9ac-cbe7f61c3654": "Why is it difficult to estimate the political, social, and economic impacts of GAI?", "108fa021-85ba-4c80-b094-bc316a5210da": "How can real-world conditions be better integrated into the testing of GAI systems?", "25bfeba9-9dba-40e4-ad97-8c839ca8c51a": "What methodologies can be used to evaluate biases in AI-generated content?", "67f472ad-fa27-4999-b17b-c75cccb0ef3b": "How can computational testing methods help identify stereotypes in AI outputs?", "f40897d1-e74b-4ae9-bed5-132e9360c38f": "What are some common biases that might emerge from AI-generated content?", "07c1cc8e-f86c-4899-82ed-bf9b470ddf20": "How can structured feedback input be used to assess AI content for harmful biases?", "e43daa73-3e5d-4c9e-a3ca-075dec799ed3": "What is the impact of homogenization in AI-generated content?", "ac6364d5-5041-446d-b5d7-e6d6fc9fa97b": "How can we mitigate harmful biases in AI systems?", "eae909c9-9200-428d-9d2d-0cf8ae39ea48": "What role does user feedback play in identifying stereotypes in AI content?", "e04d6574-6d9f-42a2-bf82-086109b4bfec": "Can computational testing methods alone ensure the integrity of AI-generated content?", "43545e6a-0aa6-4c7c-89f0-464c8c0cb1f9": "What are the challenges in evaluating potential biases in AI-generated content?", "9ad47d0f-1d88-4ffb-b427-4f8ecaeaee01": "How can we ensure that AI-generated content does not perpetuate harmful stereotypes?", "5612aea9-1a55-450a-830f-c05c88a34e6e": "What is AI red-teaming and how is it conducted?", "69417cf7-74ea-4fe6-bb4e-c4424621c4e4": "How can organizations collect feedback on AI model outcomes and user experience?", "85b1f1c5-fb0a-43ae-ab3f-703b8aa0663b": "What are the best practices for implementing feedback activities in AI systems?", "1d2c36f2-6923-4498-8504-c5c93c6eec30": "Why is informed consent important in AI research involving human subjects?", "4d3e7bb9-45c2-4918-ad20-9225ef78885c": "How does AI red-teaming help in identifying potential adverse behaviors in AI models?", "886bdf88-e7ed-48b2-8616-3b50743a28b8": "What are the human subject standards that organizations should follow in AI research?", "f6f13394-12e4-41df-8d73-8f8a59b625c8": "How can stress testing safeguards benefit AI models?", "7b479921-3a77-4f29-8406-2f7b03ab8878": "What is the role of subject compensation in AI research?", "c60ab7a5-60a1-49f6-b20a-5707d699cb8e": "How can AI red-teaming be performed in a controlled environment?", "32fe7223-3f84-4ef2-a178-0fba0a0e178f": "What are the potential risks and impacts of AI models in real-world interactions?", "19b3ef87-4631-4218-ba95-80b2c105535a": "What are the privacy concerns associated with social media monitoring?", "005c7c98-75a6-4242-878e-530c529e641f": "How do ankle monitoring devices impact individual privacy?", "1ba49c65-ac05-43c5-806b-21171820c4da": "What are the potential risks of using signature matching tools in voting systems?", "deebad53-75a3-40d9-83f0-b09ff89b0b35": "How do smart home systems collect and use personal data?", "04ad04d2-396e-4701-a6e9-2422c69accc7": "What are the privacy implications of systems that collect health-related data?", "d70da12d-584e-4e52-9eae-1f9e2f62e745": "How do education-related data systems impact student privacy?", "56387c3a-2259-48da-88f8-d5890f89f39d": "What are the concerns with using criminal justice system data for big data analytics?", "857b6f51-d048-46ae-85a7-5495bb30553f": "How do ad-targeting systems use personal information to build profiles?", "8ae7d54f-19dc-4a4f-9065-c5993f18db14": "What is algorithmic discrimination and how can it be prevented?", "fe8e6119-c018-4ce9-9b76-272740890ecc": "How do algorithms that detect student cheating or plagiarism work?", "b1a35db2-e2c3-411a-9942-84f2ce3db112": "What is the AI Risk Management Framework by NIST?", "985b4d2d-1090-4510-b623-7cd70b25fb56": "How does the NIST AI Risk Management Framework address AI risks and trustworthiness?", "a0eb8337-f777-4726-a13b-d7ec625951a6": "What are the key characteristics of AI risks according to NIST's AI Risk Management Framework?", "6c03ed54-6ab0-4045-a251-0dce83ca395f": "What are AI RMF Profiles as described by NIST?", "402b5f7a-b09f-487b-b5a9-72eced264252": "How can organizations use the AI RMF Profiles to manage AI risks?", "18dc0b62-513e-4205-8429-d0f22c15a613": "What tasks are described for AI actors in Appendix A of the NIST AI Risk Management Framework?", "8ce49ea6-adba-418b-a59c-9007b6ae81da": "How does NIST categorize different AI actors in their Risk Management Framework?", "f8ab2a45-69cd-4dc5-a52f-d340a7e463c6": "What are some common AI attacks and their mitigations according to NIST?", "5e9092a5-7669-45cc-af06-639af0388ab2": "How does the NIST AI Risk Management Framework help in improving AI system trustworthiness?", "d829fb79-fb10-4f92-b38b-e155bb3fcee3": "Where can I find detailed descriptions of AI actor tasks in the NIST AI Risk Management Framework?", "a023b48b-2c54-40ef-8767-5d3f03fe2914": "What are the key policies needed to oversee AI systems effectively?", "33fa9547-975a-4352-8f53-81d66f44c49f": "How can independent evaluations improve the oversight of GAI systems?", "a6fa8d04-3c9b-457d-88fd-dfa23ce40ff3": "What types of risks are associated with GAI systems that require robust evaluations?", "8f6d5636-40eb-47a8-ad69-b87dfebea48d": "How should organizational roles be adjusted across the lifecycle stages of large GAI systems?", "a71268a9-4141-4a0e-b1fa-0076d05cd42e": "What is the importance of test and evaluation in the development of GAI systems?", "691fbe00-89ad-498d-8d41-323cf1e97661": "How can harmful bias and homogenization be mitigated in GAI systems?", "e6e14601-db3d-4f7d-8676-d4eab8ecb25a": "What are the best practices for GAI content moderation?", "7068ff06-d301-4011-b487-7cfba94a4861": "How can increased accessibility of GAI tools and interfaces impact their oversight?", "e8dab0e4-d104-4378-a736-39d0227294b1": "What are the critical components of incident response and containment for GAI systems?", "aca5d4a8-7b84-4056-b0e6-e04d36ece68b": "How can information security be maintained in human-AI configurations?", "6897739c-d427-406f-ad1d-d7c4c77294d3": "What are the ethical concerns associated with text-to-image models?", "e0dacf35-3db5-49c4-9766-2c3dad84baab": "How can text-to-image models be misused to promote dangerous or violent messages?", "226859d7-3332-4379-8494-f26272702d7d": "What are the risks of GAI systems producing content that recommends self-harm or illegal activities?", "b791d661-0b16-4057-b391-7d89660c8a6d": "How do current systems attempt to restrict harmful outputs from GAI models?", "18041e17-7026-4c7d-9458-03b95bed2260": "What is \"jailbreaking\" in the context of GAI systems?", "efafd5fa-5e44-473a-89e5-972ae57c28f2": "How can \"jailbreaking\" be used to circumvent output controls in GAI models?", "f6f5b288-0e56-4759-a22e-70b60f145993": "What are the limitations of GAI systems in terms of data privacy and information security?", "06185446-c806-4fde-a2bc-435e67f172e3": "How can GAI systems be harmful in the context of CBRN information or capabilities?", "e23e338c-f249-4c47-9177-bde54d129a27": "What measures can be taken to prevent GAI systems from producing obscene or abusive content?", "20366931-36fc-4932-be26-4a2236da5849": "Why is it important to study the potential harmful effects of GAI systems on mental health disclosures?", "c02e5bf5-5f98-4e9a-9951-b476de779a36": "What are the best practices for applying organizational risk tolerances to third-party GAI resources?", "67fb8dc5-8f12-4f4c-b3dc-891c8219e312": "How can organizations effectively assess personnel credentials and qualifications for GAI projects?", "6df4dda4-63e2-45ab-82e3-2ad196f97ad3": "What are the key steps in performing background checks for individuals involved in GAI development?", "1626e1c6-eaaf-458a-9d62-6539ba4af917": "How can organizations filter GAI input and outputs to mitigate risks?", "ade6ed4e-ae4a-4354-9696-9be41db683dc": "What is retrieval-augmented generation, and how does it apply to GAI risk management?", "c37cf334-7c3f-4151-88b8-baf4569164a2": "How should organizations reassess risk measurements after fine-tuning third-party GAI models?", "8ccf5159-8cbc-4786-9c65-58c3df77213f": "What are the common risks associated with the GAI system value chain?", "91601426-b8bf-4362-b7fe-360c419ef972": "How can data poisoning affect GAI systems, and what measures can be taken to prevent it?", "822d55ee-6b63-4714-a957-a43dc8d843c9": "What are the implications of data privacy and localization compliance in GAI systems?", "284bee81-fb81-49a5-bbe0-49ef74483c20": "How can organizations ensure geopolitical alignment when integrating third-party GAI resources?", "bfa377f7-0ab2-4134-b646-98d6866d752d": "What are the main priorities in information integrity research and development?", "bd0492b6-4b03-4c9c-af31-313a235c4c93": "How does information integrity impact cybersecurity measures?", "8eebfbca-8240-4861-bd05-6a53ad7ccd8f": "What are the latest advancements in information integrity research?", "3ceb3870-78e8-4ec0-9491-241fccb93ec5": "Why is information integrity crucial for data security?", "7d63dee3-6d48-4393-8be6-8480ce6ced6d": "What role does artificial intelligence play in information integrity?", "e027c23e-9be3-40d9-a43f-99b9cc85df42": "How can organizations improve their information integrity practices?", "eaf96d9f-b112-43f1-ac2a-15c56c9e2ed8": "What are the challenges faced in information integrity research?", "4752b74b-3b45-4293-84a6-9129151862be": "How does blockchain technology contribute to information integrity?", "c98a9050-6d52-4601-8554-821c0659bcb8": "What are the best practices for maintaining information integrity in databases?", "015b7ed6-dfc9-419c-b332-8d22138cadfb": "How do regulatory standards influence information integrity research and development?", "b4881d3d-9b06-4fa0-94ca-6df2782ac2fd": "What are the minimum thresholds for performance or assurance criteria in deployment approval processes?", "c187cc72-ec40-4262-a0a8-dd0a7d8236a5": "How often should the reviewed processes and approval thresholds be updated to reflect GAI capabilities and risks?", "ad51c1b1-347d-4f10-b264-363ddcdfa938": "What is the significance of establishing a test plan and response policy before developing highly capable models?", "a7fc40f7-d119-4980-b911-ad106e77b51e": "How can one evaluate if a model may misuse CBRN information or capabilities?", "102600d4-12bd-4196-b867-7b5b9f746130": "What are the key components of a \"go/no-go\" policy in deployment approval?", "307c1ef5-e97b-48be-a89d-57c5db8c3e6b": "What procedures should be followed to ensure information security when dealing with CBRN information?", "761bbb97-b978-43a2-8f4c-50adc790fd0b": "How can confabulation in models be detected and mitigated during the deployment approval process?", "9e565cf7-9f25-43f9-9c04-55f723fcfde1": "What are the risks associated with dangerous, violent, or hateful content in highly capable models?", "b14dae2d-32f4-43d6-80c9-6f7752b5ddba": "What steps should be taken to periodically evaluate offensive cyber capabilities in models?", "b976da61-57a7-4e5f-a8f0-1328f4cd25f4": "How can one ensure that the test plan and response policy are effective in preventing misuse of CBRN information?", "a21ab356-0089-4dbf-b788-2b90e85ee801": "How do remote proctoring AI systems impact students with disabilities?", "b444448c-39c6-4825-a428-c35b6541fd7a": "What are the concerns of the National Disabled Law Students Association regarding AI in remote proctoring?", "af11b4d9-49c2-4c1e-a752-6ee9983d2405": "How do healthcare algorithms contribute to racial disparities in patient care?", "667c8aaf-0338-4557-83a6-11d3be7ef5b8": "Why do AI systems in healthcare assign lower scores to Black patients compared to white patients with similar conditions?", "51f1057f-cd68-4ea1-bf25-3d2e6c150aad": "What are the implications of using sociodemographic variables in clinical algorithms?", "efd5daa3-ad2f-403d-9faa-cfc0f273c6bc": "How can AI in healthcare be improved to avoid race-based health inequities?", "cb42a96f-6b88-4a1d-933c-4b66bf56803e": "What specific disability-specific access needs might cause AI proctoring systems to flag students as suspicious?", "54e478ee-901e-4bfd-b77b-ae6dbf060187": "How do clinical decision-making algorithms affect healthcare outcomes for different racial groups?", "0c29d394-6d79-42ea-ac56-98ef3e0c1ddd": "What steps can be taken to ensure AI systems do not discriminate against individuals with disabilities?", "334d816c-6309-49be-8b84-552c577f1ecc": "How do sociodemographic adjustments in healthcare algorithms impact patient treatment and outcomes?", "ef292182-a80e-4c2e-8112-92ec138b322a": "What mechanisms are typically used to supersede or deactivate AI systems that are not performing as intended?", "9a613a68-8a96-44f3-924a-fd86cb2bd642": "How can responsibilities be effectively assigned and understood for managing AI system deactivation?", "21861de8-59d7-4dbe-a656-594afc0c20c0": "What are the key components of a communication plan for informing stakeholders about AI system deactivation?", "1744f37c-51db-4c5a-b1a0-80edb5bd1d47": "Why is it important to inform AI stakeholders about the reasons for deactivating a specific GAI system?", "4bc70be6-98e2-4044-81b3-a337497b444d": "What are some common workarounds provided to users when an AI system is deactivated?", "73b8b746-f1dc-41ac-8aec-5465b68d6593": "How should user access be managed during the deactivation or disengagement of an AI system?", "55b0124a-dcc6-42f6-b033-337a237adf54": "What alternative processes can be implemented when an AI system is deactivated?", "96eddcb3-606d-4fcf-8ecb-1aabb6410965": "What contact information should be included in communication plans for AI system deactivation?", "7c0b2c60-6f69-4f22-bb40-b69c5ea6020d": "How can organizations ensure that open-source AI models are properly deactivated or disengaged?", "fc8a6a87-f230-4bb1-bcbc-b84d5e624924": "What are the risks associated with not having a proper deactivation plan for AI systems?", "586aeb54-40fd-4a75-a7c0-246e11eb3ae8": "What are the common causes of sensitive data leaks in organizations?", "aa626c2d-93f9-4ce6-a685-92c1a419dc4e": "How can companies ensure that their data sharing practices do not present a sensitive data risk?", "3e4a7bfc-a423-403b-aecb-603a13cbe16b": "What are the best practices for conducting ethical pre-reviews of data?", "dccc7390-abc6-409c-835a-9ebe4f7d0b1d": "How should organizations report the outcomes of their ethical pre-reviews?", "731906bd-9376-465c-885b-47262c0ac060": "What types of data are most commonly sold, shared, or made public by companies?", "a869d0fb-d027-4edc-be16-ca89dad5107d": "How can organizations assess whether their data sharing practices are ethical and safe?", "05fba6f9-2740-4b27-beb4-8b707e3fa913": "What ongoing risk identification and management procedures should companies implement?", "14a3553d-b4f0-4a82-82fd-f4ded8de7679": "How can companies mitigate risks associated with data sharing and public disclosure?", "53598710-70e3-4180-bfa6-20045b17b328": "What are the key components of a clear and machine-readable data reporting format?", "d156ee61-a192-4285-85eb-3e0f4cd4eb13": "How often should organizations update their risk management procedures to address new threats?", "6aceb768-3368-49cb-90f3-790b8d4131a3": "What are the main techniques used for provenance data tracking in digital content?", "13caf8a9-5882-4525-8431-f068b49ab01c": "How does digital watermarking help in tracking the authenticity of digital content?", "0a4c99ed-0f3b-4ec0-b9c8-91d7a35b593c": "What role does metadata recording play in provenance data tracking?", "7a7a8144-8fa6-4ca8-a505-9a5781f7850e": "Can digital fingerprinting be used to verify the integrity of synthetic content?", "cb3616bd-f4d8-4795-866d-04c8fe1a8b49": "How does human authentication contribute to provenance data tracking?", "77e9d110-209d-445e-8b11-16e0f2209022": "What is the importance of tracking the origin and history of data inputs in GAI systems?", "ad18f30e-051e-4a17-aa6a-1192c3cac7a8": "How can provenance data tracking assist AI actors who lack full visibility across the lifecycle?", "4d0345e3-6423-4930-96b7-564bf85f7af2": "What are the differences between overt and covert digital watermarks?", "af6f7cb4-a265-408b-a84b-4b3fee1fde06": "How does provenance data tracking help in protecting intellectual property rights?", "0718d3de-69b5-45f0-942f-79426b4d5ad4": "What are some potential manipulations that provenance data tracking can detect in digital content?", "3e3a23a7-0b1f-4b74-85bd-a73370b108e6": "What are the main findings of Zhang et al (2023) regarding human favoritism and AI aversion in persuasive content generation?", "c4cf1592-0435-4ae4-8a4c-c5ecb9257eae": "How do people perceive generative AI compared to human experts according to the study by Zhang et al (2023)?", "d6c51c91-05a7-402e-893e-5fc29584968b": "What is the significance of human-GAI collaboration in persuasive content generation as discussed by Zhang et al (2023)?", "e0587b4e-ddbf-4754-8557-bd12c8e644da": "Can you explain the concept of \"hallucination\" in large language models as surveyed by Zhang et al (2023)?", "2544321b-4f79-413c-9a51-2b0b5346a1b3": "What are the key points from the survey on hallucination in large language models by Zhang et al (2023)?", "9011cc3e-7c14-4371-99d2-06a06ec529e7": "How does the study by Zhao et al (2023) propose to implement robust watermarking for AI-generated text?", "0048257b-c29b-4594-829c-28fc43d6a999": "What are the benefits of provable robust watermarking in AI-generated text according to Zhao et al (2023)?", "99ba8f01-a9f5-4945-bc6b-2c290ee16f8f": "How does the research by Zhao et al (2023) contribute to the field of AI-generated content security?", "78f31d73-92bf-4caf-ade9-8bed953bdfa5": "What methods are suggested by Zhao et al (2023) for ensuring the robustness of watermarks in AI-generated text?", "33b17f33-82da-409e-8c46-2ba705142a99": "How do the findings of Zhang et al (2023) and Zhao et al (2023) complement each other in the context of AI-generated content?", "8d45f0a9-2470-406e-845a-42ae6faefaaf": "What is the NIST AI 600-1 publication about?", "e1b36541-9713-4537-8ae0-68c508ee31cb": "How does the NIST Trustworthy and Responsible AI framework address AI risks?", "9761ef9d-05ad-4eb6-84fe-a3e40e15721f": "Where can I access the NIST AI 600-1 document for free?", "6f912bc7-a00d-4201-a5ed-67ad675fb196": "What are the key components of the NIST Artificial Intelligence Risk Management Framework?", "d653daf1-bc71-4825-b8c2-d7a2bbbad861": "How does the Generative Artificial Intelligence Profile fit into the NIST AI 600-1 framework?", "c65c29ab-b699-4074-98c3-1d194961096b": "What are the main objectives of the NIST Trustworthy and Responsible AI guidelines?", "2a5dd66d-4d91-48e5-b4d1-0e97ead849bc": "How can organizations implement the NIST AI 600-1 framework in their AI projects?", "7ce28472-4d89-4da8-9e89-4fc46c2a13c5": "What are the benefits of using the NIST AI 600-1 framework for AI risk management?", "afa13ecd-3449-42b8-90ba-ea5b76fb4649": "Are there any case studies or examples included in the NIST AI 600-1 publication?", "83bfcfa0-0f58-42c0-b0fe-8d24efe51b48": "How does the NIST AI 600-1 framework ensure the ethical use of AI technologies?", "efd3986d-bd53-4b00-8759-234ee59b5935": "What is the new initiative announced by the Justice Department to combat redlining in 2021?", "b9552078-c814-4194-ad10-5170b3d76f76": "What are the key objectives of the PAVE Interagency Task Force on Property Appraisal and Valuation Equity?", "24d775f9-adea-4036-a91b-2b8dbdf09f8d": "How does the PAVE Action Plan aim to close the racial wealth gap?", "dbef7a7c-d59a-44a9-85d0-0922c437187c": "What are the main concerns addressed by the EEOC regarding the use of software, algorithms, and AI in assessing job applicants and employees?", "06d81d53-f1b8-45b1-9d99-aad6159cf2f1": "How does the Americans with Disabilities Act relate to the use of AI in hiring processes?", "3e1a2639-ad92-41c2-b64f-74852b3978d5": "What guidance has the US Department of Justice provided on algorithms, artificial intelligence, and disability discrimination in hiring?", "137541ed-d9cd-4d7e-b4eb-09e87ee778a6": "What are the potential risks of using AI and algorithms in employment decisions according to the EEOC?", "f54b5a57-e54a-4eb4-b5ea-3861f01c7a4a": "How does the PAVE Action Plan propose to address mis-valuations for families and communities of color?", "dc89246f-d70d-485b-a723-08770bd02f19": "What steps are being taken by the Justice Department to address redlining practices?", "9a719c6a-76c4-4af6-ae8c-1028bbe8568e": "How can employers ensure compliance with the ADA when using AI and algorithms in their hiring processes?", "2f7c682f-8e96-43da-8397-67ce42d16885": "What are the main concerns regarding the use of biometric technologies in the public sector?", "fdb90e56-c634-47ef-8f82-cf244064da4f": "How does the private sector utilize biometric technologies differently from the public sector?", "03bc26cf-d584-4f6c-952f-6da051e2ec27": "What were the key findings of the OSTP\u2019s Request for Information on biometric technologies?", "b36444b8-7e2e-4cc0-923b-d70acd084d36": "How does the National Artificial Intelligence Initiative Office contribute to the governance of biometric technologies?", "a8d11191-6908-46c0-9ccd-5526ac9ac777": "What are the potential privacy issues associated with biometric technologies?", "4e4d21bb-0a0d-49fd-948f-d1510ecdda24": "How can biometric technologies improve security in public and private sectors?", "4ba397c0-1b13-4613-9e30-01238dcdb761": "What are the ethical considerations in the deployment of biometric technologies?", "c38be416-9682-4d97-8adc-600dfa5d5218": "How do public opinions vary on the use of biometric technologies in different sectors?", "d8c53a02-255b-4261-813a-b50fa08cd969": "What are the recommendations from the Science and Technology Policy Institute regarding biometric technologies?", "7568d3e5-b407-4b82-a31a-2d7048871862": "How is the governance of biometric technologies evolving in response to public input?", "fe6be310-abb6-4d17-b332-42b573870741": "What are the key expectations for automated systems in terms of accessibility?", "4da20bc3-35b4-40d8-8699-3a01d413ac86": "How can organizations ensure that their automated systems are accessible to people with disabilities?", "e3b5fbce-4994-4bee-bfde-419e661a8a25": "What types of disabilities should be considered when designing automated systems?", "e6f6d4ff-5bc4-4809-aa55-4639adf8fbe5": "What are some relevant accessibility standards that should be adhered to during the development of automated systems?", "f4c81b62-7898-4380-bbe0-2e9ef2568424": "Why is user experience research important before and after deploying automated systems?", "1270cceb-5232-47d9-b785-280f19ce1fb4": "How can organizations identify and address accessibility barriers in automated systems?", "77d31311-acc9-4a0a-9ff7-8cff6cda43c8": "What is the importance of disparity assessment in automated systems?", "6409d026-b4de-4585-b70c-a6aa6203ecdb": "How should automated systems be tested to ensure they do not produce disparities?", "e6682ed3-e17b-47ae-9d07-f50e8f6c2df3": "What measures can be taken during pre-deployment testing to assess disparities in automated systems?", "13d62abf-9a46-4079-9a23-4ed18c3d22a9": "How can in-context deployment testing help in identifying disparities in automated systems?", "e4777246-3922-49ed-a2cb-5205495a2534": "What is the definition of equity in the context of fair treatment?", "0f7bdfbc-7ab6-4861-8efd-a3729e4128ad": "How does equity address the needs of underserved communities?", "3fbd4df7-eb9c-4760-afb0-2f341544e453": "Which groups are considered underserved communities in the context of equity?", "9861991b-cae5-4ecc-952d-0c2a6be10285": "How does equity ensure fair treatment for LGBTQI+ persons?", "4219fb8a-0ac8-4ecb-9d80-7ff321f4cd59": "What role does equity play in addressing systemic inequality?", "74b3d860-da7f-439b-8e61-5c69ac15c28b": "How are rural residents included in the concept of equity?", "bf920e1a-ff07-4d59-b892-8609aa91fdce": "What is meant by \"rights, opportunities, or access\" in this framework?", "19f1343a-292b-4bb5-8567-c39e272ec0ae": "How does equity relate to civil rights and civil liberties?", "8e6fc90c-607d-4e5f-8946-0f2b984a4975": "In what ways does equity impact older adults?", "e2f0625f-8931-45c4-b593-bb284f09ddd2": "How does the concept of equity address persistent poverty?", "7a5e1a08-397a-440e-8f6c-1af66ee702d0": "What are the key characteristics of trustworthy AI that should be integrated into organizational policies?", "75e53249-b463-44d5-83be-bdd902fc92ce": "How can organizations establish transparency policies for documenting the origin and history of training data in AI applications?", "aa76d60e-073a-408e-bf7f-44ee6a8d0a9b": "What are the risks associated with data privacy and information integrity in AI governance?", "66ee0108-3649-4abc-95cd-c102ba9c3451": "How can organizations balance the proprietary nature of training approaches with the need for digital content transparency?", "67c464c5-77f9-4875-8e31-8402a617f457": "What policies should be in place to evaluate the risk-relevant capabilities of AI before deployment?", "2b18ac77-f66e-449f-bb8c-641d6d6e522c": "How can organizations ensure the robustness of safety measures in AI applications through internal and external evaluations?", "a8055010-820e-4e2a-acbd-4363d93ffeef": "What are the specific risks related to CBRN information or capabilities in AI governance?", "b1c0e6a1-f07d-4e7e-a97c-2264522b8bcc": "How can organizations determine the needed level of risk management activities based on their risk tolerance?", "421c1f70-89d3-45a7-92c0-6b6fd7393f78": "What are the best practices for integrating trustworthy AI characteristics into organizational processes and procedures?", "41710f51-0c31-4835-a239-bba06e0b5003": "How can organizations manage intellectual property risks in the context of AI governance?", "e9ef61d9-acfb-4295-8166-81d2d8e29cd1": "What is the Department of Defense Responsible Artificial Intelligence Strategy and Implementation Pathway?", "63251280-da3b-4d49-9e3b-8b79726b8e55": "Where can I find the Department of Defense's AI strategy document released in June 2022?", "c739a52b-1410-4168-82eb-52163e1c9cc2": "What are the key principles of Artificial Intelligence ethics for the Intelligence Community according to the Director of National Intelligence?", "7da3dff9-04d3-4cea-814c-cd1c71e8f2fa": "How does the Department of Defense plan to implement responsible AI practices?", "70a71142-ccc1-46c3-85cb-f7e5573d1ea0": "What ethical guidelines has the Director of National Intelligence set for AI in the Intelligence Community?", "b1801b81-b269-4946-9f2f-f3bd71107763": "Can you provide a summary of the Department of Defense's AI strategy and implementation pathway?", "22b9c165-4460-449c-a296-6369c392e632": "What are the main objectives of the Department of Defense's AI strategy released in June 2022?", "f40a3247-588b-4f4a-8c27-0234b1af2a95": "How does the Intelligence Community ensure ethical use of AI according to the DNI's principles?", "55315bb2-f065-44ae-bc39-ffa0fe34eb65": "What are the challenges mentioned in the Department of Defense's AI strategy document?", "f2e63c22-7347-47c9-b0a7-ff7f363ad3c1": "How can I access the full text of the Department of Defense Responsible Artificial Intelligence Strategy and Implementation Pathway?", "9128749a-0d1d-42e5-94c3-9b820c40125b": "How does automated test proctoring software discriminate against disabled students?", "aab3924b-582c-4dc6-9118-49c1c8b51b5a": "What are the main findings of Ziad Obermeyer's study on racial bias in health management algorithms?", "aa7f061b-c839-40ea-ba44-f24f4ab55467": "What are some examples of discrimination faced by disabled students using automated test proctoring software?", "bd8aaa1f-1382-47e3-9ce1-09f9e7164ebc": "How can automated test proctoring software be improved to be more inclusive for disabled students?", "048678e4-9c45-4540-a0c6-72c404e2106b": "What impact does racial bias in health management algorithms have on patient care?", "51ba72f1-b32c-479c-820e-2d02252ecc21": "Are there any legal protections for disabled students against discrimination by automated test proctoring software?", "4ec83564-814d-4175-8f0f-704d3e58d2f7": "What methods were used in the study by Ziad Obermeyer to identify racial bias in health algorithms?", "3569ca2c-24e6-4785-ba6e-317a3d302202": "How prevalent is the issue of discrimination in automated test proctoring software?", "2869107a-ce0c-41b3-8508-c60d12c31fe7": "What are the ethical implications of using biased algorithms in healthcare management?", "cc253ba2-15d7-47dc-a233-8bc4a26cdedc": "What steps can educational institutions take to ensure fair testing conditions for disabled students using automated proctoring software?", "153cebaa-730a-43c5-99b7-10c18bec1538": "What are the best practices for managing risks associated with Generative AI (GAI)?", "dba1f4e2-98a6-4d42-b384-1a54e1d6ad1c": "How can organizations govern risks across various stages of the AI lifecycle?", "becc940f-e73e-4aa7-8581-f1ba6def41f0": "What are the common risks associated with the use of large language models (LLMs)?", "7a90fb5d-f437-4b59-9931-c0af0ec35339": "How can cross-sectoral profiles help in managing AI risks?", "43e9e772-adf1-40b7-9b1a-9fc44772e900": "What are some suggested actions for organizations to manage risks in AI?", "c2a5af10-b86f-4924-8010-b80c2782b006": "How does the AI RMF profile help in mapping and measuring AI risks?", "6e36882c-0b7c-4f22-a9d0-560ddc1859f5": "What are the novel risks introduced by Generative AI?", "7e0b3a69-208b-4140-8f56-b1041396d409": "How can cloud-based services impact AI risk management?", "7968a9ac-bfaf-4a59-bb35-1125136d6a96": "What are the risk management priorities for Generative AI?", "c942dcb0-ebf6-4dc8-aef1-d3b7642ef3c5": "How can organizations use AI RMF profiles to manage risks in business processes?", "aab11cf2-1200-420c-a291-040945c00aad": "What are the best techniques for managing statistical biases in GAI content provenance?", "96ade2c4-dc96-4d8d-ab36-a0860916d265": "How can re-sampling and re-weighting help in reducing biases in AI evaluations?", "1b1d4db6-e59f-4967-9a3b-17ad799ac4b4": "What is adversarial training and how does it mitigate biases in AI systems?", "ca0cdce9-6039-460a-8ebc-0d2da442b1a8": "How should content provenance data be documented to ensure privacy and security?", "0df51587-f84b-43eb-9c03-341d92892edd": "What are effective methods for anonymizing data to protect the privacy of human subjects in AI evaluations?", "add464c4-0e7d-4348-91dc-15a25c5a309d": "How can privacy output filters be leveraged to enhance data privacy in AI systems?", "36e32c02-9ee0-485c-8d4c-110273810e28": "What steps should be taken to remove personally identifiable information (PII) from AI datasets?", "877d24bb-418d-4075-b1e9-a626881ec675": "What are the risks associated with not managing statistical biases in AI content provenance?", "3da8d02e-d37f-4c4d-a06c-1f61edd78d4b": "How can human subjects withdraw their participation or revoke their consent in AI evaluations?", "841e4207-02f3-4f15-b3cc-0574eccf296b": "What are the potential harms of not protecting human subjects' privacy in AI evaluations?", "b4cfa32e-3647-4808-9718-9b77c8956ff5": "What is the importance of assessing notice clarity and timeliness in user notifications?", "34a1099f-5eb1-4cdb-bd14-0904a0d6883c": "How can the validity and accessibility of explanations be evaluated effectively?", "baf6bb09-9e41-48d9-b4c6-1d06d90b9bb2": "Why is it crucial to assess the level of risk in system impacts and inferences?", "fd7da839-a0e8-4f92-a7fd-2e894b6e5c04": "What are the best practices for tailoring explanations to different recipients and purposes?", "a81b08ef-f745-43dc-8405-02f77e2ebee0": "How can individualized profile information be made readily available to users?", "a3e89095-24b0-4e5b-957d-ac24b193a418": "What methods can be used to ensure that reporting is clear, plain, and machine-readable?", "bf278d53-8d4e-44d1-a215-6464076e0e89": "How does the assessment of notice clarity impact user trust and understanding?", "52b91d4f-d324-4333-8d00-e513e1af51b5": "What factors should be considered when evaluating the timeliness of notifications?", "e8955df1-dc4d-47af-b782-993b5b795595": "Why is it important to provide explanations for system impacts or inferences to users?", "5cbad06d-9274-443a-8465-7a7347fd1bb8": "How can organizations ensure that their explanations are tailored to the appropriate level of risk?", "098c6a18-502f-48ec-999e-13d995b28661": "What is the Blueprint for an AI Bill of Rights?", "699f9227-0a04-4b34-9fbb-bcdabe65806c": "How does the Blueprint for an AI Bill of Rights inform policy decisions?", "da24d51e-024a-422a-976c-cbe53754d0ff": "What is the role of the White House Office of Science and Technology Policy in the context of AI?", "d984a686-20d3-4998-bddb-d15ef2a55d67": "How does the national values statement and toolkit guide the responsible use of automated systems?", "7769d886-01e5-43d6-8808-a34ed6787c48": "What are the key principles and frameworks published by consortia for automated systems?", "3f2e20af-2d2f-40e2-9c9d-5f447f5fd470": "How does the framework address sector-specific privacy laws and oversight requirements?", "8cc369e6-5dbf-4195-bdc7-59d477935e01": "What kind of input has the White House Office of Science and Technology Policy sought from the public?", "2a846355-ce0a-4a42-bf39-c58e28255baf": "How are impacted communities and industry stakeholders involved in the process of addressing algorithmic harms?", "97341ca2-a8ed-46fd-8b73-27cf49a776db": "What are the potential remedies for algorithmic and data-driven harms discussed by the White House Office of Science and Technology Policy?", "ed70d285-bd85-4086-a63a-22c25a560082": "How can policymakers use the national values statement and toolkit in the technological design process?", "8c7fb32c-c935-4651-8283-e8c472a0b365": "What are the key civil rights and liberties protected under the Blueprint for an AI Bill of Rights?", "78c6ff01-8630-4cd4-a808-4a934eacb25f": "How does the Blueprint for an AI Bill of Rights address issues of unlawful surveillance?", "cd574726-80a1-47a9-b260-413ed3f52311": "What measures are suggested to ensure equitable access to education through automated systems?", "85722140-1b7b-46da-9ec6-432923b12175": "How does the Blueprint propose to protect individuals from discrimination in employment using AI?", "eded288b-f225-4e3b-be1d-6732eeceebb3": "What guidelines are provided for ensuring privacy in both public and private sector contexts?", "d91e1537-de8d-491c-b125-765de2f2afe8": "How does the Blueprint for an AI Bill of Rights ensure access to critical healthcare services?", "c91b6fc5-1d16-48e6-b88c-8dd1e3af6559": "What are the recommended practices for providing non-deceptive information about goods and services?", "3cd4fd6f-9208-4ceb-a69d-dc920993a98d": "How does the Blueprint address the issue of excessive punishment in the context of automated systems?", "e138b6b8-2968-4bab-8d4a-edca29460bcd": "What protections are in place for voting rights within the Blueprint for an AI Bill of Rights?", "1c59e241-7137-41cc-946d-c1cb0d30a4b1": "How does the Blueprint ensure fair access to financial services through automated systems?", "a4b6ef42-b7bd-444a-970f-c4708415a0ea": "What is NIST Dioptra and how is it used to evaluate GAI trustworthy characteristics?", "6b536f29-aa04-4434-b133-bb4e20ecd6f1": "How can data privacy be ensured when using AI systems in CBRN information or capabilities?", "bde91ad8-b00a-4c6b-ab35-cbc33641a8a4": "What are the risks associated with confabulation in AI systems?", "6fdb5ca1-7096-4613-ad70-ef413dcf51b2": "How can information integrity be maintained in AI deployments?", "5d29075f-46e0-4828-b712-657535007fca": "What measures can be taken to prevent harmful bias and homogenization in AI systems?", "3b68fd1d-60d7-4479-bc67-e72dc34b2baf": "What are the key tasks involved in AI deployment and TEVV (Test, Evaluation, Validation, and Verification)?", "b8bcfc18-dfb7-45f2-94fb-686ffb671400": "How can the limitations of generalizability of AI systems be documented effectively?", "448bc715-abc3-4d6f-a386-a2e6c48b434f": "Why is it important to avoid extrapolating GAI system performance from narrow assessments?", "35077bce-fc70-4f73-9e85-bd50ea0b4421": "How can human domain knowledge improve GAI system performance?", "b299ae9b-dd09-4132-a8d7-685ac966b912": "What are some methods to document the use of human domain knowledge in enhancing AI systems?", "26969f38-1ae0-4596-8d89-e2796ab42cc5": "What are the trade-offs involved in early-stage model decisions for AI systems?", "4fcf7347-858d-4761-95f8-19fb1af11339": "How does selecting a watermarking model for robustness impact computational complexity?", "589055f4-8d10-4b06-b68f-9cfd4048cefe": "What is the importance of tracking the provenance of training data in GAI systems?", "40defdf1-6880-44b7-a1ac-b88f466b074a": "How can documenting provenance data limitations benefit GAI systems?", "8f3e8e77-90af-4d0d-8dd3-5d5f2e614d74": "What are the cascading impacts of early-stage model decisions on downstream performance?", "ca4886da-af0a-420f-b881-1207c2a9181b": "Why is it important to manage organizational risk in enhancing content provenance?", "c13ec0d2-6f92-4b7d-8743-62c761213c6e": "How does prioritizing robustness in watermarking models affect other aspects of AI performance?", "b1ec710f-242e-4b53-a427-76970b24a311": "What methods can be used to track the provenance of metadata in GAI systems?", "edc582fd-2c53-4a88-ac44-3c229de7085a": "What are the potential risks of not documenting provenance data limitations in GAI systems?", "f9e0f746-0407-4024-882b-ca132aac8938": "How can organizations balance the trade-offs between robustness and computational complexity in AI models?", "547e953c-3c15-4ee0-b243-3c2761a19028": "What are the main civil rights concerns discussed in the Shared Statement Of Civil Rights Concerns document from July 30, 2018?", "8787fe19-eb36-4f63-8355-085d09e9c966": "What is the focus of Idaho Legislature's House Bill 118 passed on July 1, 2019?", "4558a005-edd2-4a8a-a3a1-96e8a91bdc99": "What are the key findings of the Executive Office of the President's report on Big Data and algorithmic systems from May 2016?", "905133de-f72a-42a8-9a2f-e194bee80d01": "What are the main arguments presented in Cathy O\u2019Neil's book \"Weapons of Math Destruction\"?", "0093d7ea-7e1a-4cad-a33f-26434d5e9417": "What is the central theme of Ruha Benjamin's book \"Race After Technology: Abolitionist Tools for the New Jim Code\"?", "d802150d-0458-44ad-94e6-d48a2bafddc7": "How has facial recognition technology led to wrongful arrests, as discussed by Kashmir Hill?", "3dec342d-89f1-48ea-b474-124dabac2778": "What are the potential civil rights implications of pretrial risk assessments?", "26e9fdf4-b265-44ac-aab5-a4811434f00b": "How does the use of big data in criminal justice impact civil rights, according to the 2016 report by the Executive Office of the President?", "e9a896b0-946f-4635-90a0-2abae8017e85": "What are some examples of algorithmic discrimination mentioned in the provided context?", "2a1a746c-d31f-4062-9339-f652ee1cd0fc": "How do the books \"Weapons of Math Destruction\" and \"Race After Technology\" address the issue of racial bias in technology?", "4adc70dc-e01b-4a8d-bd8c-adef4690717c": "What are the benefits of having a human fallback system in automated processes?", "81c46268-ad7f-45a4-ab44-b39eec645df2": "How can users with disabilities request reasonable accommodations in automated systems?", "6c21060a-4d83-46b3-a846-697b9a09c91b": "Why is it important to test automated systems for accessibility for users with disabilities?", "7753fc6c-a2dd-4e2f-9694-1ad7f0d6c64f": "What mechanisms can be implemented to ensure human fallback is not burdensome?", "ed7e713d-1382-464c-aaa9-eb64bdc88fbc": "How can companies ensure that their automated systems are accessible to all users?", "26951caa-8dbb-4149-81de-40d042c190ba": "What are some common issues users face with automated systems that require human assistance?", "19fd9fc0-5705-4c8f-9471-301741097255": "How can human consideration improve the user experience in automated systems?", "1d8d1efe-bee3-41c4-a9a1-549978df9821": "What steps can be taken to make human fallback mechanisms more convenient?", "c886eb12-d921-44b8-8452-f1f5bc1225f4": "How do automated systems typically handle requests for reasonable accommodations?", "0a84141f-d8b5-468a-a16b-93a9a0a47587": "What are the challenges in balancing automated systems with human fallback options?", "42804d52-5b54-4e4a-aa0b-0f295b8b73bb": "How can systems be tested to ensure they handle inappropriate or malicious queries effectively?", "beed6021-c77f-4dd5-b636-dddc90934522": "What are the best practices for evaluating AI system vulnerabilities regularly?", "7f734e3f-9eb5-4d60-99e6-c12b8c79fe06": "How can AI systems be protected from being used for extortion or targeted impersonation?", "b5c02363-613b-4083-a3a5-ae724917ecbb": "What methods can be used to prevent AI systems from facilitating cyber-attacks?", "84e252fa-dec3-4ec1-9b3d-a0e88f6a8b55": "How often should safety measures in AI systems be reviewed and updated?", "fd9556ae-448f-4d3d-af10-8089d6b043b8": "What role do domain experts play in the operation and monitoring of AI systems?", "e580a445-024f-4b81-a591-c79fa6f7fb0a": "How can AI deployment be managed to minimize the risk of illegal usage?", "ee7f5729-19f1-41d3-ba40-12390626207d": "What are the key components of an AI impact assessment?", "0b0819ad-858f-4cc2-9a1c-41f9c77d93d6": "How can TEVV (Test, Evaluation, Validation, and Verification) be applied to ensure AI system security?", "3850de5f-db60-43a0-94d4-63536424c707": "What strategies can be implemented to prevent the circumvention of safety measures in AI systems?", "dcec4fe7-764a-4c8a-b07f-90fcbb7708ba": "What are examples of time-critical systems in various industries?", "e9fb9f53-24c3-4408-8e9d-508409b7f92e": "How can organizations ensure that new decisions are effectively enacted in automated systems?", "1c6c655d-fa19-4fa2-8143-ea52a0a44611": "What safeguards can be put in place to prevent future errors in automated decision-making systems?", "97179ce5-9493-4f29-90be-01818f234c9c": "How do automated systems in healthcare impact patient safety and care?", "10be3d49-59a6-4675-8216-5d2a7bb76336": "What are the consequences of errors in automated systems that control financial penalties?", "1b29da2d-0fb6-41d6-8e7a-38493f5b169f": "How can voting-related systems be protected from errors and ensure accurate results?", "43d4dced-d40b-4a55-9481-6f383f7be02f": "What processes should be in place for human decision-makers to reassess and overrule automated decisions?", "5f442e2b-07cc-469f-ac6d-9e468c48364d": "How can automated building access systems be made more secure and reliable?", "ed225928-3594-4648-8270-ea357b99ac8f": "What are the best practices for maintaining human consideration and fallback processes in automated systems?", "2ac2ed73-c6e1-4af9-8a79-5c62a839798c": "How can organizations overturn previous repercussions from incorrect automated decisions?", "fb32bc70-21c5-4841-beea-62de5c884172": "What are the key components to include in a service level agreement (SLA) for GAI systems?", "a012d748-c92a-4b5c-ba2d-b54a3914756e": "How do you ensure content ownership and usage rights are clearly defined in contracts for GAI systems?", "37d2418c-90ce-43c2-809f-d6c0c96ef7c3": "What quality standards should be specified in SLAs for GAI systems?", "8af40417-015a-48e0-965b-fc636209e614": "How can security requirements be effectively integrated into contracts for GAI systems?", "805a7e12-3609-48b5-8320-157d4b583f8e": "What are the best practices for maintaining information integrity in GAI systems?", "baa6b25d-2b92-4536-9b88-465f65d6d2fe": "How do you address content provenance expectations in SLAs for GAI systems?", "4e4d7968-ecd4-4428-9b66-54567b3811a3": "What are the common challenges in drafting contracts for GAI systems?", "7e5eef6e-1818-4a3c-941b-7cbfd29ab0a4": "How can intellectual property rights be protected in GAI system agreements?", "4ed36e1b-43e7-48b4-a4cc-ef3087d2246b": "What role does information security play in the value chain of GAI systems?", "5d208543-8d35-4012-8c41-f13b2978eae6": "How do you ensure compliance with information integrity standards in GAI systems?", "a8dacfd0-ba17-40c9-b350-208d2e297cd2": "What are the best practices for conducting diligence on training data to assess intellectual property risks?", "32da3eaf-6181-4aab-a4f0-41e9f8e2c415": "How can AI actors ensure that the use of proprietary training data complies with applicable laws?", "f713140e-cb77-498a-b734-2e3226c38cfa": "What are the key considerations for assessing privacy risks in AI training data?", "5aa920d1-a55e-40d6-99a9-e31c968672cf": "How can organizations document the likelihood and magnitude of AI system impacts?", "3ebe14d9-c0f7-44b2-afb8-cd0da676e8be": "What methods can be used to gather feedback from external sources about AI system impacts?", "32b1ece3-14d1-4487-853e-c72b7d522734": "What are TEVV practices, and how do they apply to content provenance in AI systems?", "5dd34d24-f3ea-4aa7-b42b-0f26e197f095": "How can AI systems be probed for potential misuse or vulnerabilities in synthetic data generation?", "3f3496fe-0f67-405f-9bec-0181454b415d": "What are the governance and oversight tasks for AI actors in relation to training data use?", "98b6ca14-c6f1-4733-90a9-e8fcaac3e450": "How can past uses of AI systems inform the assessment of current AI system impacts?", "dd5071c9-0180-4916-b959-c6a07c56db03": "What are the risks associated with information integrity and security in AI systems?", "aa2070d5-b6bc-4073-a4cb-b2a83531da3c": "What is the role of the Office of Science and Technology Policy (OSTP) in coordinating science and technology policies?", "ca96d7d3-1320-4416-8cdd-7963833fa563": "How does the OSTP assist the Office of Management and Budget (OMB) with Federal research and development budgets?", "ab6fdd15-c2c9-4c64-9836-5410506b43a7": "What are the main topics covered by the OSTP in their policy coordination efforts?", "cc9ce0e0-cd3b-452e-97cd-67a557ba37e0": "What is the purpose of the Blueprint for an AI Bill of Rights published by the OSTP?", "31087be7-62d7-4c98-a630-dd1d81d1181b": "How does the Blueprint for an AI Bill of Rights aim to protect civil rights in the context of automated systems?", "8afd8443-7a29-410c-96b7-f41aea383947": "Is the Blueprint for an AI Bill of Rights considered US government policy?", "4a65f47c-1889-45a4-9ff3-a8bf32191dba": "What are the democratic values promoted by the Blueprint for an AI Bill of Rights in the governance of automated systems?", "8cda0b73-a4d4-4d29-9816-3f0cf0bbc8b4": "How does the OSTP provide scientific and technological analysis for the President?", "b25eb9c4-f4bf-4134-b0d3-e134b79ace2d": "What is the significance of the Blueprint for an AI Bill of Rights being non-binding?", "27b484ed-f229-4b08-be96-75c3abc5f8a3": "In what ways does the OSTP influence major policies, plans, and programs of the Federal Government?", "b3f70511-7f40-4e59-81c3-ea17760970fe": "What are the key characteristics of trustworthy AI?", "6541a0ad-b207-4b2d-a359-3650fafa8943": "How do energy and carbon emissions vary in GAI systems?", "669d0023-9a92-4a21-b449-8fa1a6af2b88": "What is the environmental impact of training a single transformer LLM?", "a31427f5-6815-40aa-9f6e-73e09d22a931": "How do generative tasks compare to discriminative tasks in terms of energy consumption and carbon emissions?", "7084c993-fcea-49d4-b9d7-2a857b9f45df": "What methods can be used to create smaller versions of trained AI models?", "e6cc306a-b275-43af-a0a7-799fe2f76eb9": "Why are generative tasks more energy- and carbon-intensive than non-generative tasks?", "f593dd60-a1e1-4ced-b812-c96907870b2a": "How does the hardware used affect the energy and carbon footprint of GAI systems?", "c8be6a16-64b0-4b54-98c7-079cb7ec7717": "What are the potential environmental impacts of maintaining and operating GAI systems?", "b5e8f4bf-d285-47ed-945d-af92d42d30ff": "How does the modality of content influence the energy consumption of GAI models?", "8e4c0306-cc08-4518-83d4-6f690dd17d67": "What is model distillation and how does it help in reducing the size of trained AI models?", "a380299e-40fa-430f-992f-328134b228ce": "What role do advisory boards play in ensuring the accountability of new technologies?", "7cfa0b20-7c5f-4732-bbfb-bb227472a8c9": "Why is transparency alone not sufficient to achieve accountability in technology development?", "fd5786c9-4268-4527-8e19-6afd150f1710": "How can compensated community input influence the design process of new technologies?", "2ce45131-027f-4fee-8260-1dc2b57ba04e": "What are some additional system needs for validity in technology development, according to panelists?", "8c04225d-b7a3-4ebc-825e-8b08770983d5": "Why is it important to include community input early in the design process of technology?", "e0ebe468-8026-4719-8e3c-8f244e4b01e9": "What types of regulations are necessary to limit the type and cost of new technologies?", "75212bde-5e1c-41e8-98c8-52a538a82b6a": "How can early community involvement impact the success of new technologies?", "e1c0318c-d858-4aed-b2c0-ef0e1203fda2": "What are the benefits of having advisory boards in the technology development process?", "a96ba846-68e3-499f-be1d-9a65c95f7103": "How can regulation help in achieving accountability in the use of new technologies?", "0ad0778a-9494-4e3e-af88-c4694c4eddcc": "What are the potential consequences of not including community input in the design process of technology?", "f974b90c-f825-4ac8-b640-a6316a1d595e": "What are the best practices for post-deployment AI system monitoring?", "1fbd890e-3037-4f08-8ca6-d2ccc5b997e6": "How can organizations effectively capture and evaluate input from AI system users?", "77cb5cc4-479c-46ed-b80f-f461753002f9": "What mechanisms are recommended for handling appeals and overrides in AI systems?", "6dba3c3f-8828-4ed8-a5aa-eacdf7a2c278": "What are the key considerations for decommissioning AI systems?", "d9669bfc-ca24-4606-a9da-8cdef4498029": "How should organizations prepare for incident response and recovery in AI systems?", "decf6dd1-9ab9-49ac-b195-232ac4b5b5fb": "What is the role of external researchers and industry experts in managing AI risks?", "e7207f21-6721-4ef3-9f8b-fcd88334e364": "How can harmful bias and homogenization be mitigated in AI systems?", "8db3af9c-f69b-43a8-8614-e16adacd3ea1": "What processes should be established for monitoring potential confabulation in AI systems?", "30fbacfb-b9b9-4404-99ca-aa7dd91fb39f": "How can sentiment analysis be used to gauge user sentiment regarding AI systems?", "491c9db9-eec0-45a7-8d35-3b865c6cf096": "What are the challenges in maintaining information security in post-deployment AI systems?", "d5096416-f388-46a8-ba7c-efe00591a79f": "What are some practical ways to reduce bias against Black patients in medical care?", "047f16f9-4bbb-46e2-bc04-02caae32fad3": "How does focusing on active chronic health conditions help reduce healthcare bias?", "cc1bd459-a505-4eb3-bb21-c7ab7b777125": "What are avoidable future costs related to emergency visits and hospitalization?", "6a4f1ce1-50e2-4a89-94f5-90f724c34e60": "What best practices have large employers developed to scrutinize hiring data and models?", "c758fef6-ab25-497e-8fcf-971551bff0b3": "What is the purpose of the Algorithmic Bias Safeguards for the Workforce initiative?", "a39fde86-c926-4df1-9cf1-2c15908c1429": "What specific technical questions are covered by the Algorithmic Bias Safeguards questionnaire?", "9c9c9015-c691-44e8-9284-f62ef5306243": "How can businesses proactively use the Algorithmic Bias Safeguards when procuring software?", "417326fd-a953-4bf5-a161-0e5892bb974e": "What are some biases that can be identified in the model training process?", "d89c4058-3ac5-421d-b581-879d16d5de44": "What mitigation steps can be employed to address biases in hiring algorithms?", "8e1c792b-4ced-4778-8949-6daa22e033fc": "How do standards organizations incorporate accessibility criteria into their guidelines?", "2ea244fd-8aca-4018-b8b0-223714fba699": "What are the key methods discussed in the Partnership on AI's glossary for synthetic media transparency?", "2fb245a9-6b49-454b-9ab8-d94912761aeb": "How does the paper \"Unsafe Diffusion\" address the generation of unsafe images and hateful memes from text-to-image models?", "dd48491b-a737-4616-be6a-745b00f5915b": "What strategies are proposed by Rafat et al (2023) to mitigate the carbon footprint in deep learning model compression?", "f027880e-a213-48a4-9139-9393e699642e": "What legal attitudes are explored in Said et al (2022) regarding the nonconsensual distribution of intimate images?", "c704d4cf-6b24-44ed-9113-aa42008d5f83": "How does the study by Sandbrink (2023) differentiate the risks of language models in the context of biological misuse?", "366bacdd-bb77-47f2-a39c-c7bf6169f8b7": "What are the main findings of Qu et al (2023) on the generation of unsafe images from text-to-image models?", "25533810-cb28-4c5b-9792-7183df9cc659": "How does the Partnership on AI suggest implementing indirect disclosure for synthetic media transparency?", "26e99d87-0a41-4952-ae1b-35a9302a5920": "What are the environmental implications of knowledge distillation in deep learning, according to Rafat et al (2023)?", "907ab49a-3d4c-4679-8038-f781b13ee780": "What role do legal attitudes play in the victimization and perpetration of nonconsensual distribution of intimate images, as discussed by Said et al (2022)?", "aaa30f81-e6c7-4103-8a63-152c74a2b091": "What are the potential risks associated with artificial intelligence in biological misuse, as highlighted by Sandbrink (2023)?", "b0182517-507f-402c-9d72-7b621f64e5b4": "What are the additional expectations for automated systems that handle sensitive data?", "1c9c675b-2d74-4673-9aa9-cb84ac14fa32": "How is sensitive data defined in the context of automated systems?", "6d42e83b-e788-4ab9-a002-cd545c1513d7": "What types of data are considered sensitive according to the provided context?", "b6530c27-37b3-4728-bac0-f9d4473dbdbf": "Why is it important for automated systems to meet additional expectations when dealing with sensitive data?", "9179505b-25f1-43ea-8329-1f120ce64c61": "How can sensitive data expose individuals to meaningful harm?", "d7d542fb-ce5a-4048-8f5f-b650b4c35bb2": "What are some examples of sensitive data mentioned in the context?", "e1052cc7-4c2d-41cb-92c3-998f3211584f": "How can automated systems infer sensitive data about an individual?", "f0f3d3f7-c4a4-4fb7-acfc-b992f475242a": "What are the potential risks associated with the misuse of sensitive data?", "235fe3e8-a203-480d-b7b7-9f411ea2d613": "How does the context define sensitive domains?", "46d01f66-a474-4e8e-ac51-c8d522ef006c": "What measures can be taken to protect sensitive data in automated systems?", "874107ea-6ed8-441f-968f-3704b981bf64": "What are the key capabilities and limitations of GAI systems in terms of digital content transparency?", "2cdd6080-bdc8-4e6c-b474-90b02b47b693": "How can training materials be developed to educate AI Actors and the public about the societal impacts of AI?", "a0fb147c-38c0-4fef-9b75-18e76cf8a420": "What role does diverse and inclusive content generation play in the context of AI systems?", "df1759f8-c9a0-4abf-9108-e0f81494dbaf": "How can feedback from operators, users, and impacted communities be effectively recorded and integrated?", "1cfd9941-237a-46a0-be9f-b60e2511126e": "What methods can be used to gather structured feedback about content provenance?", "4d85eb98-cd48-4fdc-80d4-2923f78551af": "How can user research studies, focus groups, or community forums be utilized to assess content quality and biases?", "3e96a9b6-2c8d-490f-906a-bf61de6087dd": "What are the best practices for seeking feedback on generated content quality and potential biases?", "55df2562-e98c-4baf-a911-341e5304f4a6": "How can the general awareness among end users and impacted communities about feedback channels be assessed?", "364d50e7-0d67-4aee-b2a4-4e278b9be1a9": "What are the implications of harmful bias and homogenization in AI-generated content?", "759c5df7-8c61-4805-b255-184f63b68e04": "How can AI deployment and monitoring be improved to address issues related to information integrity and harmful bias?", "cf41653e-3c18-45ed-a00a-19afbd790804": "What are the potential risks of insurers collecting data from social media for determining life insurance rates?", "8ae367c1-1ed9-4fe1-b0c5-25212e409675": "How can data breaches by data brokers lead to identity theft?", "624e6325-9549-4672-912d-2863775ecf64": "What are the privacy concerns associated with facial recognition systems in public housing authorities?", "c0e48c62-1775-4503-bc52-2b14d98033f4": "How does surveillance software used by companies to track employee discussions about union activity impact data privacy?", "8c95bd57-9819-4866-946c-34d2b7751cb5": "What measures can be taken to protect personal data from being harvested and exposed by data brokers?", "9134a063-6c7d-43f6-b9f4-d7e0712c9e59": "How does the use of facial recognition software by law enforcement affect community trust and privacy?", "afa24cd5-0d80-4e11-bb7f-28b1ef159c0d": "What are the ethical implications of insurers using social media data to determine insurance rates?", "07d3959c-fd15-441f-a064-d94b454936be": "How can individuals protect their personal data from being collected and misused by companies?", "accc5413-f9c8-492e-954c-db2935a83a8d": "What are the legal protections in place to prevent misuse of surveillance software in the workplace?", "154a4887-57d4-48b2-a0e2-f01ef4a05f25": "How can public housing authorities balance security needs with residents' privacy rights when using facial recognition technology?", "51d26025-f397-4282-ab4c-e614b1909136": "What are the key considerations when integrating third-party GAI models into an organization?", "e8ca0409-014b-43ca-aa66-18baf30c5856": "How can organizations manage the risks associated with using third-party GAI tools?", "618930f7-ea49-4631-8ec5-748399ab123e": "What are the implications of using third-party GAI systems for data privacy?", "0e830dc5-978e-40ef-b148-0701cdbac3f2": "How should organizations address intellectual property concerns with third-party GAI integrations?", "82ab0ec3-0073-41f1-a863-66c4ff3d8b4b": "What guidelines should be established for transparency in third-party GAI data usage?", "e774a66c-375b-45ad-8d72-28706054193e": "What risk controls are necessary for foundation models versus fine-tuned models in third-party GAI?", "babb4c10-950c-47c0-8a65-383a64edc068": "How can enhanced processes improve the management of third-party GAI tools?", "30032779-8c22-4bdf-9a98-a280bd457baa": "What are the legal implications of incorporating third-party GAI systems in an enterprise?", "490002ec-c8f2-49a0-aca4-451a75374463": "How can organizations ensure compliance when using third-party GAI-generated data?", "b9f8fe8e-7ff3-4431-89f5-73948788cb99": "What role does IT services play in managing third-party GAI integrations?", "787f8222-d352-49ea-b919-7db70989aa72": "What are the consequences of not providing explanations for errors?", "4172ceb7-f347-40ad-8c68-0fe2cc0a23e7": "How does the lack of explanation affect error correction?", "f4bfb069-4ab5-4b30-81a1-2ec30f5ec8ac": "Why is it important to explain errors when they occur?", "b419532f-ec57-4460-bf35-fcdb757ee380": "What are some methods to ensure timely error correction?", "a3239f78-3895-4866-83da-fa3a4f26ff43": "How can the absence of explanations impact overall productivity?", "a349e851-d625-49e2-a919-8040f988ec05": "What strategies can be implemented to improve error correction processes?", "055cba72-28db-40d2-99ce-d761f2ee85b1": "How does the lack of explanation for errors affect team communication?", "2bc860b5-65ed-47ff-800d-bace4aa01b70": "What are the best practices for documenting errors and their corrections?", "4b57ffb5-80b3-461f-a283-70e5cf3971bd": "How can organizations ensure that errors are corrected promptly?", "cbad517a-de7d-4da6-9786-47e6dd684d94": "What role does transparency play in error correction and prevention?", "2d9f919a-f792-4b1b-a10e-a0f578dfc7cf": "What are the main findings of Epstein et al (2023) in \"Art and the science of generative AI\"?", "476325e4-24b4-429b-9788-e84684fab8a1": "How does Feffer et al (2024) evaluate the effectiveness of red-teaming in generative AI?", "6d1dbac6-21e1-487b-b666-a788c3d485db": "What offensive security capabilities of large language models are discussed in Glazunov et al (2024) \"Project Naptime\"?", "58543296-0157-4a5a-9ddc-522f60ee6867": "What are the potential risks of indirect prompt injection in LLM-integrated applications according to Greshake et al (2023)?", "e9b7254b-b94e-4e18-a453-c58d8436079a": "How does Hagan (2024) propose to establish quality standards for AI legal help?", "6a69d169-7541-4d51-93a8-35fb4587ee8e": "What strategies does Haran (2023) suggest for securing LLM systems against prompt injection?", "ccca527c-b69c-4c41-b2ea-9aff9b44255f": "How does the study by Feffer et al (2024) contribute to the debate on whether red-teaming is a silver bullet or security theater?", "c66d08da-f096-41ae-8483-61507f48f6c0": "What are the implications of the findings in \"Not what you've signed up for\" by Greshake et al (2023) for real-world applications?", "a2e8cb0d-b35c-4690-bb95-38babd0775ce": "What methodologies were used in Glazunov et al (2024) to evaluate the offensive security capabilities of large language models?", "087fbc2e-973a-4823-936b-0d0243f5c688": "How does the research by Hagan (2024) differentiate between good and bad AI legal help?", "3bcb7050-a5e3-4025-86e9-b9c7a3eb2196": "What are the key responsibilities of AI Actors in monitoring reported issues in GAI systems?", "0bc4535d-2b67-4804-be77-c8734789e122": "How can AI Actors effectively evaluate GAI system performance using content provenance data tracking techniques?", "c73bd3d7-f752-4f5f-9676-e8acebd65d4c": "What steps should be taken to ensure prompt escalation of issues by AI Actors?", "fdd55fcd-d79b-4a87-ae51-09c717172f37": "What are the measurable activities for continual improvements in AI system updates?", "3102119a-0e38-44ee-bcfc-a58a411db0ef": "How often should regular engagement with interested parties, including relevant AI Actors, be conducted?", "7b74d871-b727-476b-99de-f23821860093": "What are the suggested actions for managing GAI risks related to harmful bias and homogenization?", "5ef4015c-16b3-4fc4-983b-5266130165bd": "How should regular monitoring of GAI systems be conducted and what should be included in the published reports?", "e587f1fa-cbd2-454a-85bb-44b757a0046f": "What are the best practices for following incident response plans for inappropriate or harmful content generation?", "48910454-45b0-4445-9366-f056ee60b60b": "How can processes be adapted based on findings from incident response plans in GAI systems?", "7c2d9a6a-5497-4fdd-a880-598d0303db6e": "What roles do human factors play in the operation and monitoring of AI systems?", "b252c530-ffef-4684-adb9-1fadc10df9a1": "What is a use-case based supplier risk assessment framework?", "0c235183-3b08-4ff7-9116-62f623af1175": "How can organizations monitor third-party entities' adherence to content provenance standards?", "3d779012-1e50-47b9-a393-b2536d277ca6": "What are the key components of value chain risk management?", "bb8eff08-42f2-4110-a840-121f230e4c81": "Why is it important to include clauses in contracts for evaluating third-party GAI processes?", "7dd59eab-597e-4402-bbde-5219259f1663": "How can organizations ensure information integrity when dealing with third-party entities?", "8a1a0e9b-c1d6-43a4-b808-6de57e66e46e": "What steps should be taken to inventory all third-party entities with access to organizational content?", "044efb34-2fe0-49fe-8893-7ccb84e34d86": "What are the benefits of establishing approved GAI technology and service provider lists?", "a3484e6b-9afe-4e3d-9b40-45c9b71a39f0": "How can maintaining records of changes to content by third parties promote content provenance?", "8fdd2306-5671-47b8-a6a4-613dcd55f9fd": "What types of metadata should be recorded to ensure content provenance?", "319e4f98-b5a8-4b4e-968d-98c42d92e7b2": "How does intellectual property relate to third-party content changes and provenance?", "76e21c77-5abd-4e59-8638-acbbb4e196f2": "What are the best practices for obtaining consent for the use of data in GAI applications?", "e92011ba-08e3-4f27-8a90-097f25c195ee": "How can anonymization help in protecting data privacy in AI applications?", "a127a266-08a2-4440-ad55-820b622a4116": "What is differential privacy and how does it enhance data security in AI systems?", "036f4f23-f219-4b3c-a996-f38ce4a3735b": "What are some privacy-enhancing technologies that can minimize risks in AI-generated content?", "b59f0589-8212-4bea-bd66-233cd0e150df": "How can AI developers ensure information integrity when using human data?", "4e38d0ae-2d12-48c0-b6ef-a1288551e7f3": "What are the key factors to consider in human-AI configuration for data privacy?", "b035b709-5421-4c16-9588-36f6df6dd376": "How should AI system performance be measured to ensure it meets deployment conditions?", "3e8e3d35-e9b4-4d82-8549-e0076fb93944": "What are the risks associated with linking AI-generated content back to individual human subjects?", "ac6ecaeb-d774-42e9-a706-23571e9ca244": "How can baseline model performance be used to improve AI systems with retrieval-augmented generation?", "642dbeb3-b3f9-425b-adf3-f3fd7101c7f2": "What methods can be used to empirically validate claims of AI model capabilities?", "41b113fc-3f56-4b6a-b606-bacc03b2a8b9": "What are the key differences between data privacy and intellectual property?", "95092336-d112-46e6-822a-88f81d722e72": "How can companies ensure data privacy while protecting their intellectual property?", "4b019b57-09a1-4397-af47-7cf29ee23a69": "What are the legal implications of data privacy breaches on intellectual property?", "1411f491-e75f-4111-a9e7-b927c26b8c3b": "How does GDPR impact intellectual property rights?", "7caa53ec-adf7-4bd5-b0d6-16e1ec9de7af": "What are some best practices for maintaining data privacy in intellectual property management?", "724b5a82-32f3-49fd-8271-505c3b2a5866": "Can intellectual property be compromised through data privacy violations?", "1bba92c8-2cf6-481c-a916-e2b90863ada9": "How do data privacy laws affect the sharing of intellectual property across borders?", "b57dc1d4-b29e-4d1f-81d7-93ab353d2990": "What role does encryption play in protecting both data privacy and intellectual property?", "241527a6-6383-42f6-80ad-d47448a4e5de": "How can businesses balance the need for data privacy with the need to share intellectual property for collaboration?", "03c92229-db55-4afa-8ac5-34de6b0a3b79": "What are the consequences of failing to protect data privacy in the context of intellectual property?", "abaa83aa-555a-4d21-acf1-7c73b0d057ff": "What is the risk-based pricing rule in lending?", "073ea355-2455-462d-8d7b-c26913cb9ef8": "How does the risk-based pricing rule affect borrowers?", "17d41936-ead2-475b-b785-6dd826930ae7": "What rights do consumers have if their credit application is denied?", "f99de0df-3a30-4c03-be26-e66bce9f385a": "What information must lenders provide to borrowers under the risk-based pricing rule?", "7b39da4e-33ab-41c7-826b-5d251d01cc39": "How does the CFPB protect consumers' rights regarding credit applications?", "4c661a4d-46b0-4361-881d-a2e3bfffc226": "What are the requirements for warehousing employers in California regarding quotas?", "f95da55e-afa4-49de-aabe-bcc697b0c48a": "How do algorithmic monitoring systems impact warehouse employees in California?", "7654615f-4130-42ba-ab22-d08da8a0d3b5": "What must California warehousing employers include in the written description of quotas?", "154ad3bc-8ed0-45e4-9156-62d7e04da73f": "Why is it important for certain decisions to be explained to consumers?", "c8c67888-5617-4df8-aa80-597113c355ee": "How does California law ensure transparency in quota systems for warehouse employees?", "e593b5e5-80a5-4368-8044-4401253e2242": "What are the unique risks associated with General Artificial Intelligence (GAI)?", "58567b4a-dad8-4564-bb4b-78ed4e066585": "How can organizations manage the risks posed by GAI?", "980286b9-57b1-41cb-be5b-1c92d2cade95": "What actions are suggested to mitigate GAI risks?", "c4dd04c4-3824-49be-bbb2-28e519e680e2": "What are the primary considerations for GAI mentioned in the appendix?", "710a2983-1bea-4763-b367-819eea4ef3bc": "Where can I find references related to GAI risks and management?", "91a4617d-ae27-46d6-967d-0120e9f36b4d": "What is covered in the introduction of the document on GAI risks?", "33034f48-184c-4594-80d2-8996aa2b9d20": "How does the document suggest handling risks that are exacerbated by GAI?", "fa471afa-5001-4d53-b1fc-23f57e65bb99": "What are some examples of risks unique to GAI?", "71a166e6-1296-4706-9677-80a0a0a51341": "What page contains the suggested actions to manage GAI risks?", "70bebbf1-bde6-4150-b4ef-a9a63f9f8a4c": "How comprehensive is the overview of GAI risks in the document?", "d01efaa2-b7e6-48c4-9117-00d808d80d03": "How can organizations ensure that notices and explanations are accessible to users with disabilities?", "c50f5c77-e898-4823-a5d9-6ead49445ebe": "What are the best practices for making notices available in multiple forms, such as on paper, physical signs, or online?", "7216a1fd-492e-4455-9b1c-87127423efe4": "Why is it important for notices and explanations to be available in multiple languages and reading levels?", "c4b916ed-6f69-42b4-a36d-b4b84b300ab8": "How should explanations be tailored to the specific purpose for which they are intended?", "e7b46646-126f-461b-8c4a-db9cd8cff6c2": "What are the key differences between an informational explanation and one provided for recourse or appeal?", "d67307ed-cd5b-4202-b68c-269b3cb7e195": "How can automated systems provide clear explanations for their decisions or actions?", "8185582a-dc07-4b2e-b832-9e3abf2e271b": "What steps can be taken to ensure that explanations are understandable and actionable by the intended audience?", "655c7548-ad98-400b-a65a-0d9b4aebe77d": "Why is it necessary to provide explanations in the context of a dispute or contestation process?", "8024511f-e7d3-4a95-83f6-e77cedb7f0f5": "How can organizations balance the need for detailed explanations with the need for simplicity and clarity?", "a6cf7580-b17b-496c-a7cf-7bdb4ad5cec8": "What are the challenges in making notices and explanations accessible to the American public, and how can they be addressed?", "1b8b06c4-65a8-4291-8125-da58b1a2fcf2": "What are the main flaws identified in the tool meant to help low-risk federal prisoners win early release?", "86c6a713-18f3-4788-94d7-798e37572f76": "How is the Justice Department working to curb racial bias in deciding who gets released from prison?", "3b3ac587-1908-4993-ad69-1d204707f0ba": "What were the key findings of the 2021 Review and Revalidation of the First Step Act Risk Assessment Tool by the National Institute of Justice?", "161b4640-9926-4d54-b332-3ae24fe928a1": "How does Google's Sentiment Analyzer exhibit bias against the LGBTQ+ community?", "5ef48cd2-e223-4cc4-935f-7b59b03953aa": "What are the implications of Google's Sentiment Analyzer thinking that being gay is bad?", "36ac78ac-c399-4cc2-bba8-b4c88049ba0b": "What is the Jigsaw Unintended Bias in Toxicity Classification project on Kaggle about?", "5e6dc05e-c94a-440c-badd-059d28a98ecf": "How does the First Step Act Risk Assessment Tool impact federal prisoners?", "b801b3ed-2645-4ab7-8eab-5f44c53f7cbf": "What steps are being taken to address the flaws in the tool for early release of low-risk federal prisoners?", "953c7a65-0054-4509-b437-2ee2f041e51e": "How significant is the issue of racial bias in the context of prison releases according to the NPR articles?", "48e496f1-8380-4006-9052-8e63ea4fdc38": "What are the potential consequences of bias in artificial intelligence tools like Google's Sentiment Analyzer?", "2bd65018-80f1-4a1e-8ff0-c03d11d2f9ac": "How can I opt-out of an automated system and what are the steps involved?", "4eafde78-6428-426b-85a5-fd83ddfc8a8e": "What are the criteria for assessing the clarity and accessibility of opt-out instructions?", "123f10a6-afad-4ad0-990c-17f252217093": "Are there any user experience research studies on the effectiveness of opt-out notices?", "f3cfe9a7-ea97-4243-a8c0-5cb436fb9198": "What are some examples of human alternatives provided when opting out of automated systems?", "3b9d6877-d127-4076-bbd6-390afed34038": "How quickly should a human alternative be provided after opting out of an automated system?", "f239aa99-3443-48c5-8df4-e7d753f4d1f7": "What makes an opt-out process unreasonably burdensome?", "b7ddcdb9-2b6d-4546-a92a-711d76916a7f": "How can organizations ensure that their opt-out instructions are easily findable?", "7baa6242-7aa9-410d-998c-d8d113ee3ed9": "What are the common challenges faced by users when opting out of automated systems?", "5bcd97f0-208e-48bf-b9c3-85ecfdd844d9": "How can the brevity of opt-out notices impact user decisions?", "ffaea519-7960-4f2b-ade8-290a2a8dfeee": "What are the best practices for providing timely human-driven alternatives in automated systems?", "7f2aa8e1-d759-4d16-835a-7d25726466be": "What is the main argument presented by Angela Chen in her article on The Verge about life insurance and online presence?", "5f1f09e0-afde-4833-8819-12492a28f526": "How might social media activity impact life insurance policies according to the 2019 article by Angela Chen?", "7e7ae934-b104-42e1-a4ec-88b2b1c55cd0": "What are the potential risks of using big data and algorithms in life insurance as discussed by Angela Chen?", "4c2801a4-a960-4bb9-bb30-91106cebe0b1": "How does Angela Chen suggest life insurance companies might use online records in the future?", "2bc6c92b-c94f-406c-97c3-94ff5221a4a7": "What are some concerns about discrimination in life insurance based on online presence mentioned in the article?", "f15e8ee8-6df9-4c38-a7a7-724b35d7266e": "How could life insurance companies benefit from analyzing social media data, according to Angela Chen?", "1a097e10-917a-47d2-bbd0-f888b755d76e": "What examples does Angela Chen provide to illustrate the impact of online presence on life insurance?", "83ce9f99-21b4-47f0-bf69-a1bdc6c6943f": "How does the use of big data in life insurance raise ethical questions, as per Angela Chen's article?", "c0058a46-7dfe-4578-a952-21be6f9e70dc": "What are the implications of Angela Chen's findings for consumers of life insurance?", "6d0329dc-668d-490c-8c24-42c4b1e1311b": "How might regulatory bodies respond to the use of online data in life insurance, based on Angela Chen's insights?", "2f8589f2-71e9-45f2-ae32-f28ec7bf2c4b": "What is the purpose of the technical companion in relation to automated systems?", "8cbfa2ab-0832-4346-ac20-86d72deba93e": "Who can benefit from using the technical companion as a reference?", "0424821d-48cd-42b3-a821-45f2d9a02ee4": "What are the three supplemental sections that accompany each principle in the technical companion?", "fc1f5d65-4b48-44ba-bbc9-d567cad9bf4e": "Why is the \"WHY THIS PRINCIPLE IS IMPORTANT\" section included in the technical companion?", "2bac89ba-56e9-4237-bbb9-2b5879e79287": "What kind of problems does the \"WHY THIS PRINCIPLE IS IMPORTANT\" section aim to address?", "dbd6b39e-eb46-4dcc-ae55-b3268513bb63": "What is the goal of the \"WHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\" section?", "2a6d8358-e27e-4c93-986f-95adb301ee63": "How can the expectations for automated systems serve as a blueprint for development?", "8cdabbb1-82d4-4201-914a-3a873fbcf68b": "What practical steps are outlined in the \"WHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\" section?", "95cd7988-3d70-4b9a-9079-383a78c28a45": "How do the expectations for automated systems mirror existing technology development practices?", "679bc28a-263c-454f-b2f4-3c5ccf1ae00f": "What is the vision of the Blueprint for an AI Bill of Rights?", "e4229b12-3425-4bac-9532-22a0fd43652e": "What are the key capabilities and competencies required for effective risk measurement and management in an enterprise?", "03a02bfa-6e55-4dd0-a51f-edce76b48834": "How can diverse demographic groups contribute to better risk management functions?", "825dd8bf-7c6c-4446-8011-c25d6f557389": "Why is it important to consider educational backgrounds in risk measurement and management?", "e2909c32-1244-4a0a-a3fd-cf8797be04ac": "How do lived experiences influence risk management practices?", "af541196-0d8c-497e-a398-c3c9253cfec4": "What role do different professions play in the risk management process?", "2855bf3c-9555-42a9-9e98-d7eda34003a7": "How can domain expertise enhance the effectiveness of risk measurement and management?", "5ac3f009-0665-4ce4-bcca-3c6faa028116": "What are the potential risks of harmful bias and homogenization in AI configurations?", "ba3a4a1d-711b-402c-bc07-9ec87c5389cb": "How can enterprises ensure that their data and benchmarks are representative of diverse user populations?", "a75d2170-8371-41de-9317-9b80e2823d28": "What are the best practices for involving diverse participants in structured GAI public feedback exercises?", "eefc16a2-a6f8-499e-a2f7-12e4df65614d": "What tasks are involved in AI deployment to mitigate harmful bias and ensure diverse representation?", "f5398e05-e48c-4721-b625-1d00761faddf": "What are the best practices for ensuring information integrity in data systems?", "7683e79a-d55d-446d-b33d-e51f78b017da": "How does human oversight contribute to the evaluation of information integrity?", "ed4ea430-7625-4ff5-96fb-d43600713d35": "What are some proven cryptographic techniques used to maintain information integrity?", "77d696c3-d291-4500-99d5-f940800f82f6": "How can automated evaluation methods help in maintaining information integrity?", "a3938f64-6ba3-4182-ad9a-f0a734f44349": "What role does the review of content inputs play in ensuring information integrity?", "65e0271e-8df4-4d79-b667-eb66dbe7884a": "Can you provide examples of automated tools used for evaluating information integrity?", "64ee0887-641a-423f-b769-1ceb31077cfc": "How effective is human oversight compared to automated evaluation in maintaining information integrity?", "8ca7525d-cf25-49cf-b7f2-3c8e0c68c8fd": "What are the challenges associated with using cryptographic techniques for information integrity?", "fbce740c-e2f8-4a6a-b5cb-b8e609d9628b": "How do organizations balance between human oversight and automated evaluation for information integrity?", "a19e1eab-0f2e-4afa-8fe7-df69b9bee656": "What are the key components of a robust information integrity evaluation framework?", "95c335f7-1eae-4090-bbd3-d200657a199b": "What are the implications of the data leak involving 235 million social media profiles exposed by a major data broker?", "d4722ec4-cde6-4b3f-a742-a10c5e340440": "How did the exposure of 12 billion records online occur, and what were the consequences?", "f313296f-4197-4b95-a34f-da79b135a5ab": "What are the main concerns surrounding the use of facial recognition technology in public housing?", "8a1416c4-b1bc-4eec-84af-787a472e11f5": "How have Amazon and Walmart used surveillance technology in their efforts to prevent unionization?", "c1dddd25-fdcc-449b-8e21-263bfadff302": "What enforcement actions has the FTC taken against the photo storage app Everalbaum?", "0ddce7bb-a5c7-4fa6-bea6-da3737420a35": "What measures can social media users take to protect their profiles from being scraped without permission?", "7acd2768-ac2c-4dbe-9c92-a27dcf7be867": "How has the public responded to the use of facial recognition technology in public housing?", "0c799549-781b-482b-9074-635d45590cea": "What are the potential privacy risks associated with large-scale data leaks like the one involving 12 billion records?", "24353569-a8b5-4fbb-b2d8-0e04fd061aa6": "In what ways have companies like Amazon and Walmart been accused of spying on their employees?", "cbda8aeb-bccf-46df-ba9f-12a9fc01b0b8": "What are the legal and ethical considerations of using surveillance technology to monitor union activities?", "1e6a21b9-e745-404b-be65-8c7b9e4b0bd7": "What are the key performance expectations for the system?", "a0c122d2-8188-4702-8b56-6d423c5f74d3": "How are human-run procedures integrated into the system?", "a2d4766b-5e37-4f46-adac-a62b1c427c78": "What types of data were used to train the machine learning models?", "1e2f5c68-7e0e-479e-a952-e3d1c6caf4f7": "How were the data sources processed and interpreted for the system?", "63d84cc6-9adb-40a1-896f-b2e6034c339b": "What steps are taken to identify and manage risks in the system?", "b66070c1-0ec6-46ae-9fab-b4445a76fc1c": "How does the organization address missing, incomplete, or erroneous data?", "fbe83be2-10ab-40ca-806f-d957f742ed90": "What concerns were raised during public consultation, and how were they addressed?", "24efaac2-edc5-4a7e-a8a9-2786e4c966e4": "What are the results of the performance testing in terms of accuracy and error rates?", "e9460513-d9f4-4ee8-a89e-9acdf8fdf716": "How does the system's performance compare to previously deployed systems?", "6fff7468-40e8-4590-9f72-615e77d43bc3": "What are the ongoing monitoring procedures and how frequently is performance tested?", "deabd138-adc2-44f5-98ee-322a39c17a98": "What are the best practices for re-evaluating risks when adapting GAI models to new domains?", "ee75ad83-a0d7-4713-99c1-7720e8e912b6": "How can warning systems be established to detect the use of GAI systems in new domains?", "39d5c426-28b0-44e6-9fff-8fb668122c5c": "What are the key risks to consider when adapting GAI models to new domains?", "70c28c2d-9d3b-4641-974e-a1804938ca0c": "How can one ensure that previous assumptions about security and safety hold in new domains for GAI systems?", "adf119f1-b069-4a65-87cd-ad53e5c43a5a": "What methods can be used to detect the presence of PII in generated output text?", "dd282118-49ce-47dd-87c2-d4156e944523": "How can sensitive data be identified in generated images, videos, or audio?", "d771683d-c686-4a52-81ee-292ea31f22d4": "What are the potential risks of harmful bias and homogenization in GAI models?", "f49bb512-05ef-4e2c-b6a6-091cbb905329": "How can GAI systems be protected from generating dangerous, violent, or hateful content?", "f863d5ef-78f1-4960-a14d-66a66caa16f6": "What strategies can be employed to ensure data privacy in GAI-generated outputs?", "828a7539-87cf-49c4-a17e-7be3ed25bfea": "How can intellectual property be safeguarded when using GAI models?", "56a2f1d9-fc30-46e6-9705-569c76ebb6c7": "What are the main ethical and social risks of harm from language models as discussed by Weidinger et al (2021)?", "ae85135f-051c-4806-95a0-2cfaeb1b3924": "How do trolls use AI to create fake images of celebrities like Taylor Swift, according to Weatherbed (2024)?", "6ee2f972-193a-4bfb-bd19-604bde142dc1": "What is the focus of the paper \"Long Form Factuality in Large Language Models\" by Wei et al (2024)?", "941d29d9-1e5b-4e48-add3-1024903e747a": "Can you explain the concept of \"Information Disorder\" as outlined by Wardle et al (2017)?", "cd19f434-9802-45cd-9417-bf530750bf85": "What are the key points in the \"Sociotechnical Safety Evaluation of Generative AI Systems\" by Weidinger et al (2023)?", "17234b23-05e3-4796-9357-c3255713355b": "How does the \"Taxonomy of Risks posed by Language Models\" by Weidinger et al (2022) categorize different risks?", "2d3d1d60-0258-4016-b2e7-21895ee3da0d": "What interdisciplinary framework for research and policy making is proposed by Wardle et al (2017) in their study on information disorder?", "b95decfd-0e22-427d-9a93-294412eab257": "What are the implications of the findings in \"Ethical and social risks of harm from Language Models\" by Weidinger et al (2021)?", "858d0487-9ef0-41bd-beb3-28e4bf4dbd52": "How does the paper by Wei et al (2024) address the issue of factuality in large language models?", "58dd02ef-48f3-4312-83e5-1fb54e25c2cc": "What are the recommendations for mitigating the risks posed by language models as discussed in Weidinger et al (2022)?", "2d3012f3-7feb-48d4-b54c-5107353c03d0": "What are the best practices for documenting AI model details, including data provenance and quality?", "93acef7c-f3cf-4bda-848d-c79f08fefdcb": "How can counterfactual prompts be used to explain machine learning models?", "efa2b789-a244-4680-af19-b891e4c72987": "What are gradient-based attributions, and how do they help in interpreting AI models?", "7173f456-fedc-440d-b22f-efa9cf4e85f1": "Why is it important to document the assumptions and limitations of an AI model?", "5d764367-0f8d-4efd-976f-e89b2c8f684c": "How does model compression or surrogate models contribute to AI model explanation?", "95643527-800b-404a-a62c-a3f7390fbdf9": "What are the ethical considerations to keep in mind when documenting AI models?", "694a90b5-31cd-4f46-b221-2bbccbf2ea0d": "How can occlusion or term reduction techniques be applied to explain AI models?", "0697ed1f-3d26-439c-9818-2971e3df5158": "What role do RLHF approaches play in the training of AI models?", "171d3b23-4f45-49d6-a317-a5fe6cf4016a": "How can organizations ensure the responsible use and governance of AI systems?", "dc38fdd2-c4f6-490f-a7e5-5c3751e542f2": "What are the potential risks of confabulation in AI models, and how can they be mitigated?", "13d44da0-2fef-4c2f-b4ff-19599f9b2afb": "What are the main issues that the principle of safe and effective systems aims to address?", "fe155026-d872-40e9-8736-9e9a69d08e1f": "How can reliance on unproven technology lead to problems?", "d4c4faa8-502a-4bf2-b182-7aa689ad6ae4": "What are some examples of technologies causing substantial and unjustified harm?", "46c0dbae-a959-405b-b3f9-8c2e83761656": "How can historical data negatively impact automated decision-making systems?", "116fa31d-f588-49de-8ed4-d15b3ba118e5": "What are the risks associated with using technology that has not been proven to work within an acceptable range of error?", "fc759a44-cbe0-404c-83b8-dcb5b364028c": "How can technologies be designed to violate the safety of others?", "4ee837f4-d5a5-4d90-a40a-019addf10b09": "What are some unintended harms that can result from the use of certain technologies?", "c824ae9c-741c-4730-a945-d591f13e0967": "Why is it important to ensure that technologies work as intended and as promised?", "472d7e59-379f-4fa7-9356-fe2608a2ee59": "How can irrelevant information from past decisions affect current decision-making in automated systems?", "079cadfe-b827-4d8b-8847-ce41fba6094c": "What measures can be taken to prevent technologies from causing unjustified harm?", "01e765c9-5aef-4c7c-bca4-d9b4b94e54fd": "What is the purpose of the Technical Companion in the context of developing technical standards and practices?", "33df19f9-df9a-4d75-b8cf-7b262bf4f8b3": "How does the Blueprint for an AI Bill of Rights relate to existing laws?", "c702da49-cb6a-498c-b6c2-a377e4973503": "What sectors and contexts should the technical standards and practices be tailored for?", "2f16d6ca-6f2d-4da2-8d77-9da96198f0aa": "How does the framework aim to impact rights, opportunities, or access through automated systems?", "c5ff5f27-e556-4207-8151-5519b2fe84a6": "Does the framework provide detailed analysis of existing laws?", "9ec597d8-9559-44a5-b175-db525d6f9e63": "What is the broad vision shared by the framework for automated system development and use?", "f6dcae70-8e0a-4f47-9c30-589ffa82d968": "How does the framework inform private and public involvement with automated systems?", "d6cc4e55-78e6-4d3b-9425-9f0e1ffa648c": "Does the framework take a position on legislative and regulatory proposals?", "7ac7defe-9d7c-4996-bda6-56a4fe59a5c9": "Are there examples of existing protective measures mentioned in the framework?", "bb7c4021-0d4e-4b15-b28e-1d9d6664c577": "What is the significance of not analyzing legislative and regulatory proposals in the framework?", "e1aec18d-e71a-4d28-be59-e5be3881d70e": "What are the key components of effective monitoring and governance structures for automated systems?", "b2ab71bb-0a72-4068-b1c1-505a308496ea": "How can unmet needs for change in automated systems be identified and addressed?", "eb859b33-b604-4d38-9b9c-36c1c453a82b": "What are the expectations for reporting by entities developing or using automated systems?", "057efbeb-09ad-4580-a430-acb50a9681a6": "Who should the resulting reports from automated systems be provided to?", "94f7d7a1-6947-4bd2-b4fa-6d8db3896c41": "Why is it important for reports on automated systems to be made public?", "c4bcd7fc-8a32-4295-a4f2-b6da221f7546": "What considerations might prevent the public release of reports on automated systems?", "4d3140c8-cffd-4c71-ab31-dfbc34b26f50": "How should information be handled when public reports on automated systems are not possible?", "7b4e0c55-fcda-4bcb-ab4a-e2333b46c568": "What role do oversight bodies and ethics officers play in safeguarding individuals' rights in the context of automated systems?", "fbd293d5-2f7d-46ba-8a9d-ba56d3e2690b": "Why is transparency important in the reporting of automated systems?", "82a4bddf-bde1-4da4-8597-af2b5f75319f": "How can the American people benefit from transparency in automated systems reporting?", "c8815a76-b3d3-4150-9fc2-ffeca9946282": "How do GAI systems contribute to the spread of misinformation?", "e6706517-19c4-47c4-9d33-e88aaa79be85": "What is the difference between misinformation and disinformation in the context of GAI systems?", "c1f9af22-5965-4be1-86a3-e4a301b6af2f": "How can subtle changes in text or images by GAI systems manipulate perception?", "551ffc98-e117-4c8c-aabd-84102ffaa8f7": "What are deepfakes and how are they related to GAI systems?", "5b9a4026-4170-4739-aa59-a82371bcde95": "How can GAI systems be used to target specific demographics with disinformation?", "3a57b342-f32d-4571-bf11-0fd968d2f12b": "What are the potential future threats posed by GAI models trained on new data modalities?", "bdc49d2f-f75f-409c-a019-6bd6e720673b": "How do multimodal models enhance the capabilities of GAI systems in generating disinformation?", "e354dc4e-3651-464a-85e7-a02d6e8c6fe5": "What measures can be taken to mitigate the risks of GAI systems spreading false information?", "e0faed04-d3ac-4ffd-847b-0eb7570099b0": "How do malicious actors use GAI systems to create sophisticated disinformation?", "25e2dfeb-bd2e-4183-bd34-d7a9fb889f4b": "What role do confabulations play in the production of misinformation by GAI systems?", "9d781fd4-80b1-415f-bdc0-cb99a0ad57aa": "What are the key policies and procedures to address AI risks associated with third-party entities?", "5ab4424c-a307-47e8-9524-720e346f1103": "How can organizations categorize different types of GAI content with associated third-party rights?", "3749d629-316f-4418-9f81-884d7050c768": "What are the best practices for managing GAI risks in collaboration with third parties?", "76664a25-080a-4041-947e-a87349ea3aa4": "How can joint educational activities with third parties help in managing AI risks?", "a3d40842-deb4-459e-b156-f9ef4c243572": "What approaches can be developed to measure the success of content provenance management efforts with third parties?", "9ec62f10-d33b-4bcd-a708-9a6b8f4f52b7": "How can organizations ensure data privacy and intellectual property rights when dealing with third-party AI content?", "0e343257-054b-4912-83af-419e09f10542": "What are the common risks of infringement of third-party intellectual property in AI projects?", "8d5d823e-8af6-4d8b-b8f1-c68b7d439a22": "How can value chain and component integration be managed to mitigate AI risks?", "2521694f-ca6a-4805-97d6-166beb459f2c": "What metrics can be used to validate the effectiveness of content provenance management with third parties?", "5985031f-49b1-44cb-9355-1cbdf90a9ec8": "How can incidents related to AI content provenance be detected and responded to efficiently?", "c5db5bcc-a2bf-498d-92ab-5bb0db131203": "What should be included in a report about data collected from individuals?", "46b110ea-13a4-41c5-be85-368d573b2111": "How quickly should an entity respond to a public request for data usage information?", "634c0a75-d94b-4dc9-9e9c-ecb9cfb11231": "What format should the data report be in to ensure it is understandable by most users?", "08fdf655-f40d-4a7d-8eec-5c6ca9a4754b": "What information about data collection should be included in the report?", "c63e76ef-0b53-439a-871d-3b04064a5530": "Who should have access to the data and metadata collected from individuals?", "9bdf0a7c-cc20-4518-b935-616a80516ebd": "What steps should be taken if a user login is not available for identity verification?", "3fd33ba3-95e9-4be2-87dd-1dbcf4afee88": "What is the purpose of summary reporting in the context of data usage?", "04331b6c-1532-4bcc-9a9a-f12352764d7f": "How should summary reporting be made available to the public?", "18215d4a-212f-4664-a6f7-f25e3fa46f80": "What are the legal limitations on the data and metadata that can be included in the report?", "c9685d0b-7fe3-47f6-a4b5-99d6cf0b3123": "Why is it important to include time limitations in the data report?", "313a9213-5dd4-4fd0-b6cc-5649c4da50f7": "What is algorithmic discrimination in the context of AI systems?", "36918793-5d0e-48bd-b045-f8ff83ea055d": "How does algorithmic discrimination impact different protected classes?", "664af71b-506c-4536-aa63-5a4c95942aa3": "What legal protections exist against algorithmic discrimination?", "0f5c4986-db15-4307-9880-e51f3bd60751": "Can algorithmic discrimination occur based on gender identity or sexual orientation?", "5dd96edd-ff11-42e1-8ea9-f87e9ae4b2de": "How do automated systems contribute to algorithmic discrimination?", "a14927ac-5614-423d-a8f9-5c0853bab534": "What are some examples of algorithmic discrimination in automated systems?", "67b571d8-1ebc-4a74-bc63-de217aebedd1": "How can organizations prevent algorithmic discrimination in their AI systems?", "176842e4-195d-47ea-bb47-4747e05ce154": "What role does computation play in automated systems?", "d7798ca6-fc5a-4819-813f-1d68a7715e00": "How can algorithmic discrimination affect policy implementation?", "12f7ff31-5e11-4d2c-bedc-26c5cc7322d9": "What measures can be taken to ensure automated systems do not violate legal protections?", "c21ceaec-63ff-45ce-a1c8-4c954a4d0cba": "What are the risks associated with GAI models synthesizing NCII and CSAM?", "c6cf6391-dc4d-4c46-b3b5-fb5a40f28726": "How have websites and mobile apps that generate synthetic NCII evolved over time?", "01e4a6f5-a4f4-4957-9cdc-2aaba3491a36": "What are the characteristics of trustworthy AI in managing harmful bias and ensuring safety?", "241aa1b9-216b-43a4-9f90-6610fe5c28b2": "How do third-party components in GAI value chains affect transparency and accountability?", "2a49cfa9-6bbd-43ad-bea4-28427449269d": "Why is the risk of improperly vetted components higher for GAI compared to traditional AI systems?", "72445f3e-2877-4f4b-9192-ba572bcdb530": "What challenges are associated with vetting large-scale training data for GAI models?", "422aafdb-ec57-4340-bd89-2fc20e3b0da0": "How do pre-trained models and software libraries contribute to the risks in GAI value chains?", "30ac0cae-4e18-4ad7-bb21-0e34d9b27082": "What measures can be taken to enhance privacy in GAI systems?", "d14ef51f-6a7d-4b9b-8c2c-7ba562b3d774": "How does the difficulty of training foundation models impact the development of GAI?", "d716e7c9-5860-48e4-914a-8c72625fdbbf": "What are the implications of automated and scaled online businesses generating synthetic NCII?", "407a7ba6-d65a-4a11-afa4-c6ea6e4c2736": "What are TEVV metrics and processes in the context of AI deployment?", "436567b2-4a53-418b-8002-08cb30c28f31": "How can measurement error models improve the validity of pre-deployment metrics?", "d6bd80dd-1e24-488d-a6e5-eb5aa8895943": "What is the importance of documenting biases or statistical variance in applied metrics?", "84eeb2b5-483b-4794-8d69-a1fb7ca5b57a": "How can domain expertise be leveraged when modeling complex societal constructs like hateful content?", "1149e1f0-19fe-4af1-b052-9c5b0bf7b453": "What are the risks associated with confabulation, information integrity, harmful bias, and homogenization in AI?", "3e72a6bd-6a5a-4b12-8156-069a0f9382be": "What tasks are involved in AI deployment, operation, and monitoring according to the provided context?", "1e55727a-0e04-4def-9388-239c06d052dc": "Why is it important to evaluate and document the effectiveness of TEVV metrics and processes?", "a76bd5b4-7983-42f7-98f1-6cf2180a7448": "What challenges exist in assessing AI risks using currently available measurement techniques?", "5bcfbe76-4c4e-4bf9-8a09-cd1dc9eb77c3": "How can risk tracking approaches be improved for settings where AI risks are difficult to assess?", "f8f78806-13b8-4acb-9826-c4408a3c523c": "What are some suggested actions for improving the measurement and evaluation of AI metrics?", "0e48d737-5d25-4c14-94d4-f0be919145c3": "What are the best practices for conducting post-mortem analyses of AI incidents?", "ee67a49d-fa40-4f72-bc61-a39c2144d958": "How can visualizations help non-technical stakeholders understand GAI system functionality?", "963ca3e1-2fd0-4a20-85c7-d1bfe31c0bd9": "What methods can be used to represent GAI model behavior effectively?", "133585cd-97fd-4343-9627-bfa3bdcaee9b": "Who are considered relevant AI Actors in the context of AI deployment and development?", "37f44acd-e83a-4327-9d26-ac7ce250879c": "How should incidents and errors be communicated to affected communities in AI systems?", "44946c07-c978-408b-9b84-a5fd16194ca2": "What processes should be followed for tracking and responding to AI system incidents?", "20bc157a-c8bb-4ff2-9003-6f475b0d145a": "How can after-action assessments verify the effectiveness of incident response and recovery processes in AI systems?", "bc817926-284f-402f-a8b4-8016544b7436": "What are the key components of a Human-AI configuration for managing dangerous or hateful content?", "757d49ae-2c4c-4dda-b834-35d68feba859": "How can AI deployment and development tasks be effectively managed to prevent future incidents?", "ec4a9dd4-cf97-4b49-8736-19a432697eef": "What are the suggested actions for managing GAI risks in AI systems?", "5dc1404b-b9d5-4165-bfba-5ae18b4ef0a8": "What is the Blueprint for an AI Bill of Rights?", "1b4835f2-59c4-4255-a964-61969ea8863e": "How does the Blueprint for an AI Bill of Rights address law enforcement activities?", "8f94848b-91d1-4bd4-9095-8fab3fe85de3": "Why might notice not be appropriate in certain law enforcement contexts according to the Blueprint for an AI Bill of Rights?", "be1037b8-1682-4b8b-ab5b-6bad9c9018d7": "What are some examples of automated systems that might require sector-specific guidance?", "adb12b37-a721-476a-817d-6ae9d45f34bd": "How does Executive Order 13960 relate to the use of automated systems in federal agencies?", "d9941951-34e0-4599-ba08-82c1823f7557": "What are the potential challenges of using AI systems in school building security?", "800426c1-0a93-4185-b638-fc754e6a3feb": "What safeguards are in place for federal departments and agencies using automated systems?", "6cf609a1-e1ab-4388-9eee-76603f895da4": "How does the Blueprint for an AI Bill of Rights balance the protection of sensitive law enforcement information with the principle of notice?", "03ffb16c-be24-46fd-a594-205d9e68e49f": "Why is future sector-specific guidance important for the use of automated systems?", "6ff903dc-0e95-45b1-b7ba-5147dcdd7088": "What oversight mechanisms exist for federal agencies using automated systems?", "90935253-ff29-43e9-9473-f71036e4e5f8": "What are the main security concerns associated with generative AI as discussed by Burgess in WIRED?", "a87294ca-3f18-46f9-921e-10e6fa956d49": "How does prompt injection hacking pose a threat to generative AI systems?", "16605b19-6407-427d-8ad6-0bd123fef5ef": "What are the key takeaways from the Canadian Centre for Cyber Security's guidance on generative AI?", "5cd233c2-fb54-486b-bec3-6c406a216562": "How can training data be extracted from large language models according to Carlini et al (2021)?", "799db38e-e7df-45c2-af2e-701b12bdbee5": "What methods are suggested for securing AI pipelines as per the Mandiant blog?", "7b243fdf-3ecd-4747-87fd-c6c9860cb3ae": "What is the significance of next word prediction in large language models as explained by Burtell et al?", "d623ee79-0c8b-4ee4-a9ce-edbf633b20de": "How does the memorization of data in neural language models impact their security, based on Carlini et al (2023)?", "fe664b26-b505-4d49-b30f-fe252750d38f": "What are the potential risks of generative AI highlighted by the Canadian Centre for Cyber Security?", "d5d0438c-36f6-4328-90cb-4baa96b6a1bc": "How does the Georgetown Center for Security and Emerging Technology explain the power of next word prediction in AI?", "466b29fa-ac89-4e2a-8791-cfe170592641": "What strategies are recommended to mitigate the security flaws in generative AI systems?", "39725f9a-68c2-4fe9-aa8d-9a4f08d023ae": "How are AI systems being used to limit access to equal opportunities in education?", "ca7c2204-b6f5-4781-bf3b-8d9f02540ffd": "What are the concerns related to the use of remote proctoring systems in education?", "f43c197c-7302-4f65-a850-8d1592d44eee": "How does facial recognition tracking impact students in educational settings?", "6d8e2c0e-e4cf-4ebb-a417-815a64668c79": "What are the potential issues with automated tenant background screening in housing?", "14c91abd-8d01-4cf0-8523-0812a5c1c840": "How does facial recognition-based control affect residents in housing complexes?", "68d008be-5997-4d96-96e0-731c60a6c09e": "What are the risks associated with discrimination in automated hiring screening?", "cc4bb020-b92c-4f19-adc2-06b98ff1da33": "How does workplace surveillance impact employee privacy and opportunities?", "e63cb0d8-46ce-4928-aef8-ccd1f1693044": "What limitations of existing privacy laws were discussed by the panelists?", "6f3c8f9d-9bbc-44cd-92a3-95215c3cfee5": "Why is it important for students to have the ability to reinvent themselves in terms of privacy?", "2f47fea5-c195-4bb6-889a-3d498268e761": "What are the concerns related to the use of robot teachers in education?", "b23c2ac0-3c8d-418f-9d3a-4d355510c475": "What are the key components of an incident response plan for third-party GAI technologies?", "e341d43e-c5cf-470a-9937-1a0522709924": "How often should third-party GAI incident response plans be rehearsed?", "d32de1da-1496-480e-bfcb-a256b5aa2656": "What are the best practices for aligning incident response plans with relevant breach reporting and data protection laws?", "0fc878ed-8fa8-46f3-a457-943aac86deb4": "How can organizations ensure effective communication of third-party GAI incident response plans to all relevant AI actors?", "62ea75e9-a1f9-482e-b748-93e00e24299b": "What steps should be taken to define ownership of GAI incident response functions?", "d326718b-3c54-47fe-b90b-e026762b440d": "How can retrospective learning be used to improve incident response plans for third-party GAI technologies?", "8113c5c3-1121-4595-b984-3595f621efb3": "What policies and procedures are recommended for continuous monitoring of third-party GAI systems in deployment?", "1f685537-4d22-4888-90a8-cf32f7774031": "How can organizations address data redundancy in GAI systems, including model weights and other system artifacts?", "32b71e7d-ef8b-49de-a3f8-f906cd313fe2": "What are the potential impacts of harmful bias and homogenization in GAI systems, and how can they be mitigated?", "0ee66a25-f2c4-434c-b514-7affa3493429": "How should organizations integrate value chain and component integration considerations into their GAI incident response plans?", "f150a1c8-dad3-432e-91e2-c40098a5ebd7": "How can LLMs deceive humans into believing they are speaking with another human?", "1d4e22f5-8de7-4f07-9526-61c7936f9459": "What are the potential risks of adversarial prompting in LLMs?", "7c6bd923-b691-426e-beb9-67b46c185a03": "How do researchers study the extent to which humans can be deceived by LLMs?", "04d3f9c8-515a-4f01-8cae-62fb636fd1cc": "What are the characteristics of trustworthy AI?", "b4f47764-9f91-49f1-88a2-221cc0e06715": "How can GAI systems produce inciting or radicalizing content?", "3e394353-4b52-4a52-af48-562eea9f2152": "What mechanisms allow LLMs to generate dangerous or violent recommendations?", "36aee960-dcad-4e5c-97d0-05f4fc62b815": "How can harmful bias in AI be managed to ensure fairness?", "a4b69757-7dcd-4eff-90eb-a30ced99f719": "What makes AI systems safe, valid, and reliable?", "72048f3a-c23d-42a8-8194-a14c109a5af2": "Why is it important for AI to be explainable and interpretable?", "2047cc7b-4522-4ef9-93de-8bc09531f843": "What are the potential downstream impacts of confabulations in GAI systems?", "ab3b72f8-672c-486e-bc6b-9461baa761da": "What is a pre-deployment assessment in the context of surveillance?", "8e05f5b4-738f-4015-9698-0d841d8727cf": "How is a disparity assessment conducted in real-world surveillance deployment?", "e41871e4-fd71-4858-9f31-90e4bce717ba": "What are the specific goals of data collection in surveillance systems?", "0aee33e7-9f19-42ba-9f6f-020edc4551d5": "How can one ensure that only the minimum required data is collected during surveillance?", "780e0590-0606-443d-a7e8-2891d967ee16": "What are scope limit assessments in surveillance data collection?", "85dfacbf-8094-47ad-80dc-7bbcc46712ca": "How are data retention timelines determined and justified in surveillance systems?", "6c98830e-c446-42a8-ac57-f8f46ee0a255": "What is the impact of surveillance on individual rights and opportunities?", "7abcd464-ee77-4ce1-8d41-57315a78fed9": "Why is it important to have an independent party assess the impact of surveillance?", "cc012aac-5ce3-434c-8e51-35c1e8338ce4": "How should surveillance reporting be provided to ensure clarity and machine-readability?", "51e0fc29-06be-4a85-a0ae-1fa144bff1cc": "What are the best practices for documenting the impact of surveillance on access and rights?", "b74eff6f-0348-4f4d-8455-ec94c409abc3": "What are the best practices for obtaining user consent for data collection?", "0db718f0-8251-47d3-83c0-f9a203c06084": "How can companies make consent requests more understandable for users?", "84f786f2-b45d-4028-8864-a9c521374ba4": "What are the current issues with notice-and-choice practices for data use?", "39695c7a-9723-424f-a040-717c4cadc993": "What enhanced protections should be in place for data related to health and finance?", "48492acb-3e38-45a7-bcde-061e9fcbb695": "How should data pertaining to youth be handled to ensure their protection?", "64e6cef4-2fdf-4121-b410-fc7168f68289": "What are the necessary functions for which sensitive data can be used?", "71ec2ac9-cc52-4831-a314-2f92000494e4": "What ethical reviews should be conducted before using sensitive data?", "8dd38cfb-46a6-4d54-9560-fa7036a393c5": "How can communities protect themselves from unchecked surveillance?", "40a38d86-7774-4a05-b3ec-46ee736efe3f": "What kind of oversight should surveillance technologies be subject to?", "5303236e-9b24-4300-a6eb-71fd2660ba8e": "What are the potential harms of continuous surveillance and monitoring?", "68145309-ec97-431b-a2e4-ff7c84ae2b92": "How can I opt out of an automated system in favor of a human alternative?", "bc2c2f00-164e-4fb2-b04f-0a8e11a127b2": "What are the criteria for determining the appropriateness of opting out of an automated system?", "99c78782-3873-4806-b67a-5057aee1fe94": "Are there any laws that require a human alternative to automated systems?", "f1218cc9-8cf6-492a-87b4-e7e2b34939a8": "What should I do if an automated system produces an error?", "550182c7-921f-4b50-a93a-089c2d1e4f06": "How can I appeal or contest the impacts of an automated system on me?", "38276fcb-783d-4a66-b4ab-96d3654c9707": "What is the process for accessing human consideration and remedy if an automated system fails?", "64350a23-d7dc-4a12-b082-a57617fd4d14": "What kind of training should operators of fallback and escalation processes receive?", "db717bad-ccdd-4097-a630-6459902c89c3": "How can I ensure that the fallback and escalation process is equitable and effective?", "bb183df4-5c49-4847-b777-9b605daaec7d": "What are the reasonable expectations for opting out of automated systems in different contexts?", "126df14a-0e79-4f7b-9ba1-5cb3197cef81": "How can I access timely human consideration if I encounter problems with an automated system?", "bb600a12-cf3e-430f-aeac-ffb55080bc75": "What are biological design tools?", "ab0afd54-b8f3-4255-bcea-00d7f469fa4d": "How can I access the paper on biological design tools on arXiv?", "4b17bc0d-84c9-44ce-b287-5873628bcb88": "What is the significance of the paper \"230613952\" on arXiv?", "d8711a1f-0375-405e-88fb-47084c2dd456": "How do biological design tools impact scientific research?", "4e3d1faf-aaf7-4382-bfdb-f07986da3774": "Can you explain the main findings of the paper \"230613952\" on arXiv?", "01016449-dd51-43e2-8064-6163d76960ca": "What are some examples of biological design tools mentioned in the arXiv paper?", "96010c49-fead-4764-a1cf-52f08f825c94": "How do I cite the paper \"230613952\" from arXiv in my research?", "1a7dc66f-7d3c-449a-91a8-730ae4fbf5e0": "What are the applications of biological design tools in biotechnology?", "618088f5-7d87-423c-94f7-092dad08e9de": "How do biological design tools contribute to advancements in synthetic biology?", "7a5bd3f1-0117-49f5-847a-c98c3e1ed923": "Are there any limitations discussed in the arXiv paper \"230613952\" regarding biological design tools?", "396fdf65-f8c8-44af-b354-a6a3a8080cf4": "What are some effective mitigation procedures to address algorithmic discrimination?", "53b2c06d-8db2-4193-bad2-2cabf8dd64af": "How can organizations ensure ongoing monitoring of automated systems to prevent algorithmic discrimination?", "33223652-33b9-477b-a3f2-76a8fd138783": "What are the best practices for performing disparity assessments on automated systems?", "669ee0bf-cd38-407d-a36e-b02d7efaeba6": "How often should automated systems be monitored for algorithmic discrimination?", "ba748242-63e0-4e5f-9536-5e37095f34d7": "What approaches can be used to assess whether an automated system has led to algorithmic discrimination?", "369d0faf-1db8-4137-8253-078bff29bf59": "How can changes to the context of use or associated data impact algorithmic discrimination in automated systems?", "177fe09a-b7d7-45cf-a228-70fe1d4708d3": "What role does demographic information play in monitoring and mitigating algorithmic discrimination?", "74ec3300-8c0b-4be9-9382-88a845824eef": "How can organizations identify patterns of unusual results in automated systems?", "5cf0dfa4-8cc2-49d6-a074-c9d97d87b51e": "What are the challenges in performing regular assessments of algorithmic discrimination?", "77d5bb4a-5a5b-46c2-987e-911e1f0d76e7": "How can testing with a sample of users help in identifying algorithmic discrimination in automated systems?", "269c41f4-2524-4d35-9147-09e322f2504d": "What is model collapse in the context of AI and synthetic data?", "53226a81-7a32-4f91-a589-46450a0b7283": "How can overly homogenized outputs lead to unreliable decision-making?", "0d9724ae-bfe2-47f4-a021-1296db5dd676": "What are the risks associated with foundation models acting as bottlenecks?", "db9015f0-bda2-4f91-9808-19738ae88078": "How does model collapse threaten the robustness of AI models?", "b87fc7dd-8992-4529-85cb-066cbde37dcc": "What does it mean for AI to be \"Fair with Harmful Bias Managed\"?", "eecaaa8a-3251-4874-9a51-cd62286c5095": "How can synthetic data contribute to model collapse?", "bfb13ae7-473a-4caa-968a-c783c333b1e6": "What are the potential consequences of overly homogenized content in AI systems?", "030514da-a5fd-4a1f-ac10-cf8922a6150f": "How can foundation models amplify harmful biases in downstream systems?", "43d3ae5b-1657-46fb-920d-87bbf081d086": "What are the characteristics of trustworthy AI?", "40e129bc-068b-44de-942b-641c29a2983a": "What risks are involved in human-AI configuration and interactions?", "3eda549a-f514-4a5a-8cef-68367b00516e": "What are some real-life examples of laws and policies that protect rights and opportunities in AI systems?", "4359e62b-013c-45a6-b540-f16600b3d7c0": "How does the Department of Energy's AI Advancement Council contribute to ethical AI use?", "f8696290-800f-4952-81bc-3020e6f11c09": "What are the key components of the Department of Defense's Artificial Intelligence Ethical Principles?", "38c06f0b-84d5-48fa-ab9f-4a53a84e8916": "How does the US Intelligence Community ensure ethical use of AI systems?", "b81f442e-1b5f-43da-8261-9b2c1363ea3d": "What practical technical approaches are being used to protect rights in AI systems?", "dba6ad78-0e3e-4068-a3b5-38c5ab583a94": "How do sociotechnical approaches help in the ethical development of AI systems?", "4b849fa7-2c5a-41a5-b197-62210fadaf66": "What issues does the DOE AI Advancement Council address regarding AI systems?", "6f3964c4-6694-4977-976d-770e0175af87": "How do the AI ethical principles of the Department of Defense differ from those of other agencies?", "34e35d11-aa65-49a1-92b2-ab8eb6f362e6": "What role do US government agencies play in the ethical implementation of AI systems?", "77bca3a1-9687-4e84-8144-d0e76454c55c": "How can policies ensure the responsible use of AI in national security and defense activities?", "adb044f3-b06c-4147-b270-388aa7ce28a1": "How can AI potentially enable malicious actors to access CBRN weapons?", "2cc96dd4-379c-4ea0-8aab-bf6fcb0ee94c": "What are the risks associated with LLMs in the context of CBRN information?", "6b0d4619-0b82-4e50-9d25-50215d1b4223": "How might LLMs facilitate the misuse of biological and chemical threat knowledge?", "7f729371-7c4c-40c9-9651-c84ceaf4ab59": "What did recent research find about LLM outputs related to biological threat creation?", "4bcda5c2-bc2c-4f9b-a31e-c90c1bffe24b": "Are LLMs more effective than traditional search engines in providing information on CBRN threats?", "eab83c61-d25e-47e3-bf55-cec2cf22dd7d": "What are the implications of LLMs for individuals without formal scientific training?", "80e574c2-a56c-4ade-b455-0eca52117b22": "How can transparency and accountability be maintained in the AI lifecycle concerning CBRN threats?", "7af58ef3-a1c9-420e-9eec-b2eecfc7ba18": "What measures can be taken to prevent the misuse of AI in the development of CBRN weapons?", "cb512b7c-e79e-479d-9557-8757c4fda4ed": "How does the accessibility of biological and chemical threat knowledge impact security?", "16c95e95-db9f-48d8-9c3f-fbf32e49bf92": "What are the potential dangers of AI in the context of CBRN information and capabilities?", "34bbf002-cd8d-4886-a398-74853f3697c0": "What are the regulatory safety requirements for medical devices in relation to AI?", "332c9a40-a1fb-448d-9067-d81497b47a04": "How do sector-specific privacy protections impact the implementation of the AI Bill of Rights?", "05415269-22c9-4836-aceb-97f1c11d2051": "What new laws might be needed to ensure the protections proposed in the AI Bill of Rights?", "ac4195ce-e0d5-4720-a4ce-5bcc8078b64c": "Are there any exceptions to the principles in the AI Bill of Rights for law enforcement?", "05f22b03-2ba9-4910-8467-4cb79c9a8206": "How can existing laws be balanced with the new principles in the AI Bill of Rights?", "d202eb6e-03df-49f4-88d4-b160a4626fcf": "What are the practical challenges in applying the AI Bill of Rights to specific use cases?", "02abe32e-eeca-4b60-9b32-22ae7ce787a5": "How does the AI Bill of Rights propose to protect civil rights and civil liberties?", "8afa840c-a2a0-42cb-95b1-8f1b404515e3": "What role does the private sector play in implementing the AI Bill of Rights?", "a0f7a50f-5987-4c5c-98a6-36316797bea8": "How might new policies be adopted to support the AI Bill of Rights?", "817d708c-fe29-43ce-9478-5bc616838321": "What are the competing public interests that might affect the application of the AI Bill of Rights?", "9cb6e467-ad95-44c0-841b-777832cfa4aa": "What are the safety implications of automated traffic control systems in smart cities?", "eb391602-3d68-4cb9-a04a-29b9595203c3": "How do electrical grid controls contribute to community safety?", "c3b9539e-277f-4737-9e5e-e386eeebd7a7": "What role do industrial emissions control algorithms play in environmental protection?", "73302da7-3bef-402f-9bf6-f12df15c536e": "How do smart city technologies impact the safety and efficiency of urban areas?", "58e6a606-3cd6-48fc-9dad-9c6fdc181f83": "What are the ethical considerations of using algorithms to adjudicate benefits and 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"329c3806-ac7f-48ea-8945-74a6f91b5d0f": "Why is content provenance important in the context of generative AI?", "5a1e1ec3-fda4-453e-ab8e-ce1d9faad797": "What is the importance of pre-deployment testing for generative AI systems?", "5e8537e8-4e6c-41f2-9b53-2a9692305988": "How does incident disclosure contribute to the management of GAI risks?", "5c7e3648-de65-4b1e-b755-1e099598c19f": "What are the key strategies proposed by the Information Technology Industry Council for authenticating AI-generated content?", "d119441d-bce2-47b9-9924-dbf87e4cc817": "How does the concept of algorithmic pluralism aim to promote equal opportunity according to Jain et al (2023)?", "22519aa4-4650-4092-b1b5-e3ac5d8f725f": "What are the main findings of Ji et al (2023) regarding hallucination in natural language generation?", "48b1844d-583d-4e62-908d-889b415b5c31": "How do people typically react to AI failures, based on the study by Jones-Jang et al (2022)?", "cfb67ae3-43b1-4450-9bb3-d7f29aa0e86f": "What 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time-critical systems have a human fallback option?", "15bda80e-6fb3-4e9e-b3aa-343fbfc57016": "Why might an automated system fail despite rigorous testing?", "b17b2a91-c2f2-421a-9161-f577f4f49902": "What is the AI Bill of Rights released by the White House Office of Science and Technology Policy?", "1c591402-7c09-4342-9a4c-3e447029fa73": "When was the Blueprint for an AI Bill of Rights published?", "3f4d1548-89ee-4941-adf0-70889cee50a0": "What is the purpose of the AI Bill of Rights framework?", "3451f2b4-c2cf-4c53-979c-50973acbb1bd": "How can I access the Blueprint for an AI Bill of Rights online?", "d0bc240e-3df8-4e3c-91e6-826ec2f75c9a": "What is the role of the Office of Science and Technology Policy (OSTP)?", "7edebb20-1da2-49a3-b7c1-035d6f51e95c": "When was the Office of Science and Technology Policy (OSTP) established?", "8aeea347-cc31-433e-b950-82f344182a53": "What prompted the development of the AI Bill of Rights?", "e6649708-a5e7-4253-873b-745f594a79a0": "How did public engagement contribute to the AI Bill of Rights initiative?", "550ed3d0-68d5-4c20-9af9-61b217f9c8ec": "What are the main goals of the National Science and Technology Policy, Organization, and Priorities Act of 1976?", "a1df848c-b03a-406d-a467-61ee5c89957f": "Who benefits from the advice provided by the Office of Science and Technology Policy?", "50365036-5406-482d-a4f4-64f43b779b3a": "What is continuous monitoring in the context of GAI systems?", "fe6f7ccc-7cd6-4b50-8a46-8aba632ecc48": "How can feedback from affected communities improve GAI outputs?", "608884ac-731d-4bfa-b339-8c8d39749dd9": "What are some techniques used to evaluate the quality and integrity of data in AI training?", "2372552e-4f0d-4f62-8715-f7845287595c": "What is chaos engineering and how is it applied in AI systems?", "b404ae73-34eb-4434-82b9-0e2c6ab3bf2e": "Why is stakeholder feedback important in evaluating AI-generated content?", "fdc418c4-4bca-46d6-95b4-c7d346c634ca": "What are the benefits of structured human 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content contribute to dangerous or violent behaviors?", "63ef9f64-d9a2-4b88-9c2f-0c99870fc0e5": "In what ways can the spread of denigrating or stereotypical content exacerbate representational harms?", "ab431b98-c209-4dcd-a050-4a14e1bdb05b": "What characteristics make AI systems trustworthy, particularly in terms of safety, security, and resilience?", "802de2ca-5fa0-4365-94c2-2f48d2551dc3": "What are the privacy risks associated with the training of GAI systems?", "a7780055-4593-4371-baf2-0854c10b4668": "How does the use of personal data in GAI training conflict with widely accepted privacy principles?", "2eb881cb-2d98-4856-b5d4-062d6a883283": "What are the key privacy principles that might be at risk due to GAI system training?", "1835f2f8-1619-4637-a8a9-fb620ed7cb26": "How important is transparency and individual participation (including consent) in the context of GAI system training?", "a5a1e993-48c9-46ea-8808-a32d93da94aa": "What are the ethical considerations for using sensitive 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"43a76af4-542c-499e-81e3-23edeecb1692": "How does bias in artificial intelligence affect public trust?", "f2963ebd-4268-48bc-99ef-b385c395b833": "What are the three categories of bias in AI identified by NIST?", "6007e7be-7afe-475c-8f2c-d189608a35f8": "How do systemic biases contribute to harms in AI?", "873995b6-97c4-4fbf-9d84-aafae525c908": "What are some examples of statistical bias in artificial intelligence?", "6106aef5-150e-4d9f-b12d-839a1bc64d5e": "How can human bias impact artificial intelligence systems?", "5d31f548-e180-4961-b02c-1026476307a5": "What is provenance data tracking and how does it help in detecting synthetic content?", "41737fda-7f5e-4526-8ecb-d8a560682739": "How can provenance data tracking improve the trustworthiness of AI systems?", "759a70d7-6d44-4ebd-b51f-264e7fd500c6": "What types of metadata are included in provenance data tracking for GAI content?", "10bbc39b-cae2-4ff4-b61a-2c7fa87c5fd4": "How does synthetic content detection contribute to GAI risk management efforts?", "cf616e2b-26ef-43e4-9dc4-b7b9569b9f8a": "What are the benefits of combining digital content transparency with organizational accountability mechanisms?", "9b2af444-94eb-4943-808d-8a01c74a7860": "How can provenance data tracking help trace negative outcomes back to their source?", "110eb68c-1767-4f4d-ba87-2028a2a1105c": "What role does provenance metadata play in improving information integrity?", "1a06806d-fb35-4c87-8809-da5a08874714": "How can provenance data tracking be implemented for different types of content like text, images, and videos?", "5296dde2-bf5c-4f7d-b712-62c552801ef5": "What information can provenance metadata provide about GAI model developers or content creators?", "5b028681-df5b-4e75-a745-ef99535810a3": "How does digital content transparency uphold public trust in AI systems?", "273f9105-5fd9-4850-ad10-dd9a9b8cc778": "What are some potential risks unique to the development and use of GAI systems?", "f2015027-8be4-41af-9324-6b28bc14ba10": "How can organizations identify and manage risks associated with GAI?", "1c39f437-06bb-4fe4-9973-5e2bdc4a8cb2": "What does it mean for a risk to be labeled according to the outcome, object, or source of the risk in GAI?", "1e85d184-b2c1-4ff6-af08-8ea57ec19ad9": "How are the risks of GAI mapped to Trustworthy AI Characteristics in the AI RMF?", "e0add861-37cb-4915-902c-04c52bc85356": "What are some examples of risks \"to\" a subject or domain in the context of GAI?", "b2c9c8be-32f2-487a-8dcc-b0edbbaec345": "What are some examples of risks \"of\" or \"from\" an issue or theme in the context of GAI?", "553df791-945d-4f86-8985-dd794f43f520": "How can future updates help in managing the risks associated with GAI?", "39d40845-848b-4f07-ac52-444d6f6dc6e4": "What role do Trustworthy AI Characteristics play in managing GAI risks?", "d8eb671f-52dc-4612-9671-cf9c05b5beae": "How can organizations categorize risks based on their unique approaches to risk definition?", "6d2fc2bb-39a1-4e50-b2f9-1579f87f3239": "What is the significance of Appendix B in the context of GAI risk management?", "295453ca-009a-489b-9a3b-7f39d0aede8a": "What is the NIST Privacy Framework and how does it help organizations manage privacy risks?", "8a36fef4-811b-4fdd-80eb-a3d79e7b5155": "How can organizations use the NIST Privacy Framework to support ethical decision-making?", "417512e6-a1fb-48c7-b125-859ffc865ba6": "What are some benefits of adopting the NIST Privacy Framework for managing privacy risks?", "39ea0fdf-a276-42b5-911b-4ec55c6e14c9": "Why did the school board's surveillance attempt in Lockport, New York, lead to a state-wide biometrics moratorium?", "2d51294e-3f63-42ce-b8e7-80d8791bacfc": "What are the implications of the biometrics moratorium in New York schools?", "28211d1f-6063-4fe9-8a8f-56d2e0c9bd80": "How does the NIST Privacy Framework help organizations demonstrate compliance with privacy laws and regulations?", "ffd0d540-b753-4764-918d-866af54215a0": "What sectors have voluntarily adopted the NIST Privacy Framework?", "a4e0cabf-38aa-4b49-920c-c6d52520a8fa": "What measures are included in the NIST Privacy Framework to identify and communicate privacy risks?", "c63477fe-7ddc-4df4-8341-f70bcccc16f6": "What was the community's reaction to the school board's surveillance plan in Lockport, New York?", "916eda70-3efa-4870-9261-7badb6422454": "What is the significance of the July 1, 2022, deadline in the New York biometrics moratorium law?", "5928ad96-89e5-4214-a148-421437e5e16a": "What does it mean when a document does not supersede existing statutes or regulations?", "ccf1c7b4-aec1-4f63-b6b5-ee4c5681bfdd": "How does this white paper affect the interpretation of international instruments?", "3320cd92-d86b-448f-aca0-3a32e873afe7": "Are Federal agencies required to comply with the principles described in this document?", "eee8169c-4314-45e2-88bc-1d4fe146f56b": "Can the principles in this white paper influence the US government's position in international negotiations?", "8a46d200-e514-4172-a7b4-199a50cfb153": "What are the implications if the principles in this document do not meet existing regulatory requirements?", "4e95d3b7-08c9-4644-87d2-e0c03b0312ea": "How do these principles impact lawful activities of government agencies, such as law enforcement or national security?", "de79da97-0834-4ee6-b1f4-eb364ebbe1ac": "In what ways does the context of automated systems usage affect the application of these principles?", "ef810a8b-abbe-45ac-b82f-47d20dc71885": "What should be considered when applying the principles of this white paper to automated systems?", "b0f0f94e-aa95-48c9-8e54-5d27b11c1ddd": "How might the principles in this document interact with existing policies and regulations?", "a5863708-81c6-4a01-a207-62001c6f482f": "What are the limitations of the principles outlined in this white paper regarding government agency activities?", "b613cee8-31a4-4979-8cd1-7547aef01a05": "What are the benefits of using technology to push benefits to those in need?", "93e8f04f-3a3f-4daa-8c55-9a697403cf18": "How can automated decision-making systems ensure positive outcomes in benefit distribution?", "4d63f90f-ffcf-461e-b0b2-d7443e9e0e53": "Why is it important to provide clear notice and explanations about the use of technology in benefit systems?", "87ebbea1-b1c2-4928-8cc9-72bec3599f01": "What are the potential risks of using technology to take supports away from people who need them?", "383af2c3-7350-4f63-b41b-480703a2f318": "How can human-driven mechanisms ensure the timeliness of benefit payments?", "db698d0d-61cc-4055-82ba-9e9f070b90a0": "What emerging technologies are being used in the healthcare system?", "864c0429-b586-4dfb-9fd9-1122c038f71f": "How can consumer products related to health benefit from current technological advancements?", "512bfcf4-61ac-46a5-bc16-91f0073ecef3": "What role does the White House Office of Science and Technology Policy play in healthcare technology?", "cf6c1f99-aa2f-4487-bf62-4d84073869b1": "How does the Center for American Progress contribute to the discussion on healthcare technology?", "3ab8040e-18b6-4400-94bc-7f7d0d4b1b2b": "What are the responsibilities of the National Coordinator for Health Information Technology in the US Department of Health and Human Services?", "789a4e6b-1b5f-4a2e-be70-4c60b2e169ef": "What are the key expectations for automated systems in terms of technical standards and practices?", "d904c6a8-b7ae-43d7-8287-35c070601ea2": "How should derived data sources be tracked and reviewed in automated systems?", "b604912b-4408-4b2b-8eb6-c1c90a9637c8": "Why is it important to identify and track data derived from algorithms in automated systems?", "17717bc2-52ea-4d65-b273-956e440e43ef": "What are the potential risks associated with derived data in automated systems?", "26da822d-31fe-48b3-9ca8-50155d6fa977": "How can feedback loops and compounded harm be prevented in the use of derived data?", "c5d39949-dbb6-4c5e-b00a-b6fd7788ae1d": "What measures should be taken to validate derived data against collateral consequences?", "cfea209a-9830-4e58-b251-1f70f42f93f1": "Why are data reuse limits important in sensitive domains like criminal justice?", "7a516f8b-a3c1-4579-a094-1302e810e841": "How can data reuse in new contexts lead to the spreading and scaling of harms?", "acc90406-7fa4-487f-a601-6e3dc23145a9": "What are some examples of sensitive domains where data reuse should be limited?", "3a91cd21-aa78-4c15-a216-a24057643605": "What practices should be implemented to ensure the safe and effective use of automated systems?", "8363b99c-85ab-4773-86a2-f63cac3d051a": "What are the key responsibilities defined for periodic review of content provenance in GAI systems?", "f87db50c-422f-4529-a21c-78abd2d10fab": "How often should the periodic review of the risk management process be conducted for GAI systems?", "34ed1fca-1d3e-4fdc-b3a4-9281c24dd99e": "What organizational roles are involved in the incident monitoring for GAI systems?", "4d916dd9-762b-4031-b912-5fc4222557c2": "What are the suggested actions for improving information integrity in GAI systems?", "cb1a51e1-502e-4c12-b98b-10353458c6e6": "How can organizations establish effective policies for after-action reviews of GAI system incidents?", "09aabd10-bf20-4e36-a1af-b2389c95fefe": "What is the importance of maintaining a document retention policy for TEVV in GAI systems?", "16ef8d11-a13c-44d4-a88e-868f36377f22": "How do after-action reviews help in identifying gaps in GAI system incident response?", "abb1af0f-005f-408f-aa68-27d64a96a71e": "What are the procedures for updating incident response and disclosure processes in GAI systems?", "681af4b6-c008-47ac-87ac-859d9849d77d": "Why is it important to have digital content transparency methods for GAI systems?", "c32d437f-b5b4-4d28-b7f8-1a2de95eb23b": "What tasks are associated with governance and oversight in the context of GAI systems?", "2792f4ff-31f6-48c7-9b05-a903e1fa4fdf": "What is the NIST AI Risk Management Framework?", "b4374d8c-f461-4c57-8c4e-4d9975359384": "How does the NIST framework aim to manage AI risks?", "cd79ee78-f93f-4750-875f-33a59251f574": "What are the key characteristics of trustworthiness in AI according to the NIST framework?", "0135028f-ffa7-4189-92d1-0888059657c4": "How is the NIST AI Risk Management Framework being developed?", "7c54c8a4-972c-48f7-9388-9640bbc920ce": "What role does Congress play in the development of the NIST AI Risk Management Framework?", "7ab73fee-d39b-41c6-8cd8-222b44049d82": "How can organizations incorporate the NIST framework into their AI systems?", "579d7a98-c43c-4d11-b24e-6d7275e820fa": "What are the benefits of using the NIST AI Risk Management Framework?", "427a0cc8-5c14-4b43-bcd0-372317b5a8e7": "How does the NIST framework address privacy concerns in AI?", "e7555614-9fb9-4861-b164-85033e7aeace": "What opportunities are available for providing input into the NIST AI Risk Management Framework?", "5c5b27b8-e80f-4e87-80a8-dda89bca7b12": "How does the NIST framework ensure the explainability and interpretability of AI systems?", "4436c96e-b176-4846-b3be-120e574bbaae": "What are some examples of unintended harms caused by automated systems?", "53134aa2-f21c-4ea7-be6f-6b32937c51f0": "How can companies ensure that their development decisions are ethically vetted?", "89297186-beb5-4d42-b727-46821b71a4e0": "What are the benefits of pre-deployment testing and ongoing monitoring for automated systems?", "ae608ad7-1d56-4091-a89f-36c7c99c6c23": "How do public consultation processes help in the deployment of new automated systems?", "666e61ac-70db-4dc3-8657-e4c29d144123": "What existing practices protect the American public from potential harms of new technologies?", "98137aae-d585-4b93-b931-6c0f0a022772": "Why are proactive protections important for the use of automated systems?", "18d231da-3925-4aa0-8358-ad67f4ce8c1e": "How can expanded protections increase public confidence in automated systems?", "9f500df2-ad6b-42ed-8645-8a9e917bdf80": "What role do ethics reviews play in preventing harm from automated systems?", "8d4c69ae-abc4-4f4b-961e-5d0f8194de75": "How can governments improve their consultation processes for new technologies?", "4097b122-a3b3-4718-8577-48d550199b62": "What are the challenges in implementing safeguards for automated systems?", "1a442f2d-3986-4d5f-ab68-0ad589163a65": "What is AI-enabled \"nudification\" technology?", "d1108cc8-95d4-4e06-83da-0a5667e1679b": "How does AI-enabled \"nudification\" technology impact women disproportionately?", "0141b7f8-c7ab-497a-af5e-f0ad4e4ff34e": "Why is it difficult for both humans and AI to detect inauthentic images created by \"nudification\" technology?", "04c27c24-9db1-48ea-9b81-876c36344898": "What are the potential personal and professional consequences for victims of non-consensual intimate images?", "e6564ab8-5109-4a91-9546-08eef6406338": "How does the proliferation of AI-enabled \"nudification\" technology contribute to image-based abuse?", "6c438bca-254b-4856-9607-ce37450c6154": "What measures can be taken to protect individuals from AI-enabled \"nudification\" technology?", "b754ed6a-d92e-4edb-a8bc-d0eea1d29626": "How does the experience of harm from non-consensual intimate images affect victims' mental health?", "56c9eed6-f23c-499e-8bc0-52b33a7b3e1b": "What are some examples of apps that enable non-technical users to create or alter images without consent?", "6f321352-c8fc-4909-9996-33dc8382f6aa": "How can the authenticity of altered images be verified to prevent image-based abuse?", "5398f151-8b5f-42f5-b601-0b47b2d7ba49": "What steps can be taken to make AI systems safer and more effective in preventing image-based abuse?", "57eb4cf6-01d6-4cae-b638-975a2a0f2656": "What are the key findings of Virginia Doellgast and Sean O'Brady's report on call center jobs and worker stress?", "8a32a722-7f7e-40c1-967a-6c5bd05a1c88": "How do management practices impact worker stress in call centers according to the CWA report?", "e1b53808-6b10-44e0-882d-ba92d299d675": "What recommendations does the Federal Trade Commission make in their 2014 report on data brokers?", "cad08b72-46c0-40b7-bbf7-613ff0ab5f7f": "What are the main arguments presented in Cathy O'Neil's \"Weapons of Math Destruction\"?", "4da03091-d495-4661-9c76-eca9b1c37a74": "How does the US government use social media surveillance according to the Brennan Center for Justice report?", "53d8542f-d4e3-4349-bb91-b058abf20736": "What are the implications of Shoshana Zuboff's \"The Age of Surveillance Capitalism\" for privacy and human rights?", "08b49066-3db9-4bb5-97a1-46a2adb0324f": "How does the Brennan Center for Justice report describe the extent of social media surveillance by the US government?", "ded819f0-0467-4497-a257-4b727219d0dd": "What are the potential risks associated with data brokers as highlighted by the Federal Trade Commission?", "51e0e9cc-e3b9-47a7-8bf8-405f02fa04e6": "How does \"Weapons of Math Destruction\" address the issue of algorithmic bias?", "aec903ac-6dcb-450f-ad0d-c664a413a4b9": "What solutions does Shoshana Zuboff propose to combat surveillance capitalism?", "8d838d90-aa87-4ecc-9abc-0fcfa5a4d35d": "How can we protect the public from algorithmic discrimination in a proactive manner?", "a4c16234-c64d-454b-98d2-55d8906e1040": "What is a proactive equity assessment in the design phase of technology?", "33c734e9-1fa0-4bd1-b225-487ee53c2b33": "Why is it important to review potential input data and historical context during the development of automated systems?", "da018beb-b83d-4eaf-8c14-30d735aac789": "How can we ensure accessibility for people with disabilities in automated systems?", "93044246-0649-4ba3-b8b1-355b186025a1": "What societal goals should be considered to identify potential discrimination in technology?", "df01e2f4-1283-4220-9353-4573fe7a1203": "Who should be included in the equity assessments for automated systems?", "98fd7a77-ecb9-40ff-b731-37710588af27": "How can we address potential discrimination against Black, Latino, and Indigenous communities in technology?", "37017d6c-9757-463e-b5e4-7df7f5a6a2cc": "What steps can be taken to ensure equity for Asian Americans and Pacific Islanders in automated systems?", "cc45a9c2-e146-4637-ae51-762e5cf9a713": "How can we support members of religious minorities in the design of automated systems?", "a04f1bd4-fb2f-4020-a56f-07c5d12ee11c": "What measures can be implemented to protect women, girls, and non-binary people from algorithmic discrimination?", "21b9f512-20cd-4b96-a8e5-824c5d788b9e": "How can continuous surveillance systems impact civil liberties and rights?", "cbc08ff9-844c-48d2-bd2f-d965463662ff": "What are the risks of using identity-related information in surveillance systems?", "62b31c74-49b3-45d8-958c-175dffe5e8da": "Why should continuous surveillance not be used in public educational institutions?", "2eba3ccc-3d6a-46ae-bebc-6cf52aea05da": "How can algorithmic discrimination be avoided in surveillance systems?", "a81db3fd-a4bb-4dd0-a446-4b3c34313263": "What are the potential consequences of using biometrics in surveillance?", "cc016098-a84b-4347-a791-d173694b1fd8": "Why is it important to limit the use of location-based inferences in surveillance?", "61262c75-27f1-4742-a14d-7dfbb43c1f6b": "How does continuous monitoring in workplaces affect employees' rights?", "48be4dc1-8648-4ae2-b813-f08d7321d697": "What measures can be taken to prevent surveillance from limiting access to critical resources?", "d3c26eb4-5404-4906-8f26-12a930b32e4b": "How can social network data be misused in surveillance systems?", "5cd15272-af41-4e9c-aa26-42043ce6088c": "What are the ethical considerations of using surveillance in public accommodations?", "7869bc66-d4ef-4fc7-9897-351302b9eae5": "How can automated systems impact the eligibility for Medicaid-funded home health-care assistance?", "c13ee199-2840-46a1-ab92-c45e02f2f6b6": "What are the potential issues with using algorithms to determine eligibility for social services?", "d612ed72-1fb8-4bca-9b74-b5243bf640ca": "How can the lack of transparency in algorithmic decisions affect legal cases?", "bbecd72d-7534-478d-a686-94b4ed9cb7c8": "What are the challenges faced by lawyers when contesting decisions made by automated systems?", "68914712-215e-4582-8129-f1f7db119cc4": "How can individuals be informed about data collection and algorithmic assessments in child welfare cases?", "5f684140-09b8-47a2-8459-aa9c40072ce2": "What are the ethical concerns surrounding the use of algorithms in child maltreatment risk assessments?", "b0deab21-1ef7-4bb8-bb66-bd0567448753": "How can the use of algorithms in social services be made more transparent and understandable?", "e6417fe3-22a8-4536-89de-555e6a9a171f": "What steps can be taken to ensure fairness in algorithmic decision-making for vulnerable populations?", "12de6c9e-e24e-4576-9d3c-1fcbd6ccc54b": "How can parents contest decisions made by algorithms in child welfare investigations?", "522de666-2af7-4927-bf75-9d3efd25b34d": "What are the legal implications of using algorithms without notifying the affected individuals?", "fe8e6e24-ac4f-4570-bb59-e53149f51c49": "What is the purpose of the overlapping framework of rights mentioned in the context?", "07b9522e-0eac-4459-85e1-b511e6b00056": "How does the Blueprint for an AI Bill of Rights aim to protect the American public?", "55277100-414c-49c6-84ac-e6a011795719": "What are some examples of protections already required by the US Constitution mentioned in the context?", "d6a87b9f-e5f6-44ac-bc18-b4f1bc5515a9": "How should measures be taken to realize the vision of the rights framework?", "fc2524b6-ed78-43d5-b6fe-a01bdd53e031": "What is the relationship between the Blueprint for an AI Bill of Rights and existing US laws?", "fd764fa7-268d-48fb-9ec7-3be9aa2eb183": "How does the context describe the role of judicial oversight in government surveillance?", "202fc607-7128-470f-aed2-e848351cae24": "What does the context suggest about the proportionality of measures taken to protect rights?", "e5097d86-a6bc-49d4-86a4-d058c5b193a1": "How does the Blueprint for an AI Bill of Rights envision the future use of automated systems?", "e633d508-d253-4b7f-bec5-75b11962e65e": "What are the principles described in the Blueprint for an AI Bill of Rights meant to ensure?", "742f04aa-415c-4e14-98b9-5298de43c47d": "How does the context relate to the protection of opportunities and access for people?", "e1fd4aa1-c10d-4f71-bf77-b4cca9a6e0ed": "What are the best practices for regularly assessing and verifying the effectiveness of security measures in AI systems?", "9fbe4be3-06da-42bf-a241-95fc342604db": "How can organizations ensure that their AI security measures have not been compromised?", "f1082088-e78b-42d5-9285-ae15731354be": "What methods can be used to compile statistics on policy violations and intellectual property infringement in AI systems?", "e6f71c20-417c-46ac-8a42-10c97c50760f": "How should transparency reports be analyzed across different demographic and language groups?", "2f6a4b04-9c59-4bad-8823-c165db75adf3": "What are the key components to document when giving instructions to data annotators or AI red-teamers?", "a64475ac-8c2d-48af-b278-eb91c933268d": "What digital content transparency solutions are recommended for documenting instances of content generation, modification, or sharing?", "0d873b42-d24d-4da1-89ff-6ccc15e84b6b": "How can organizations address risks associated with transparency and accountability in AI systems?", "97de1dbe-9a2c-4a3a-9a0d-842bf1c1ad55": "What are the common risks related to intellectual property and harmful bias in AI systems?", "7e629132-bcc2-46fa-9815-95ccd889c845": "How can the effectiveness of AI deployment and impact assessment be monitored?", "070a1044-27d3-4b31-aa33-23e39882c9ab": "What role do domain experts play in the operation and monitoring of AI systems?", "10ecba85-50b5-466c-92fc-326759a2a5ee": "What are formal methods in the context of automated systems and machine learning?", "43072003-14fe-4f66-94c2-9ac121ef7717": "How does the Designing Accountable Software Systems program ensure legal and regulatory compliance?", "98486804-fb18-4583-ab43-67b07b08efa6": "What are the transparency and validity requirements placed by state legislatures on pretrial risk assessments?", "54358f22-1102-42f3-b0f2-7227b0a0f0c2": "Why are civil rights groups concerned about the use of algorithmic pretrial risk assessments?", "ffba1d9d-ebb6-4955-a4fa-839e180301ef": "What does Idaho Code Section 19-1910 require for pretrial risk assessments before they can be used in the state?", "99d80794-a2ea-449b-9af4-62646f316051": "How can a pretrial risk assessment be shown to be free of bias according to Idaho Code Section 19-1910?", "07f00fa3-c821-41ec-9ff1-a781bd1bd55d": "What steps must a locality take to validate a pretrial risk assessment as free of bias?", "e9dee9ec-012d-4ba0-a878-5dec4184c9a2": "What are the implications of the requirement for all documents and records related to pretrial risk assessments to be transparent?", "b922e48a-8d8e-4ae8-807f-5bb7477dd82d": "How do formal verification and analysis contribute to the reliability of automated systems?", "75050f5f-7cfc-4adf-a91a-1d7fb4185c7c": "What methodologies are considered rigorous and reproducible for developing accountable software systems?", "6b983f53-78fb-4bd3-be9a-cb6deb436d63": "What are the key components of a certification program for managing GAI risks and interpreting content provenance?", "550b57aa-5cc7-44ec-b07d-c62cd7dd4668": "How can existing training programs be adapted to include modules on digital content transparency?", "65a3901b-9b76-4dcd-b3ba-d04968302b14": "What methods can be used to evaluate whether GAI operators and end-users understand content lineage and origin?", "fe52b3aa-3245-48cc-86da-8f3f3225b4cf": "Why is it important to delineate human proficiency tests from tests of GAI capabilities?", "b3b5db46-0009-42b6-9465-4b5f30fbe624": "What systems can be implemented to monitor and track the outcomes of human-GAI configurations?", "530d41df-1d98-428a-9449-1e199472e781": "How can end-users, practitioners, and operators be effectively involved in the prototyping of GAI systems?", "68889efa-4505-424f-ae65-dc462fc55044": "What are the risks associated with human-AI configuration and information integrity in GAI systems?", "5149446a-0fef-433d-a2ae-bfa7865ae0d0": "How can proficiency in managing GAI risks be tested and certified for specific industries?", "0fba5c84-2bcf-4be8-9684-d1904eb861bc": "What are the benefits of continually refining and improving human-GAI configurations?", "5634f37b-9702-4b53-8dce-bfb21a101d03": "How can information integrity be maintained in the context of GAI systems?", "8eb9d5d5-af51-4376-9b9d-1297edd11496": "What are the potential risks of using biometric markers in school exams?", "eaf23276-45c4-465b-a0a1-c347a8fc5b76": "How might biometric systems in schools affect students with disabilities?", "451adf54-6336-4465-b4de-b6390b383b02": "Can location data from data brokers be used to track visits to sensitive places like abortion clinics?", "f2489a19-b9ce-4941-a3e9-154a0ecad928": "What kind of student data do companies collect to forecast student success?", "317d1c65-7185-452c-878a-1b16e14d3e4d": "Why are parents concerned about the collection of sensitive student data without consent?", "474c5dc3-a92f-40c7-b290-7529f751d77b": "What are the transparency issues related to the use of collected student data?", "2e297de2-2657-4560-9b39-b6316e39d5b4": "How can the collection of demographic information and other sensitive data lead to discrimination in schools?", "38c93c3c-8f95-4361-80e3-d401cdfb7a38": "What are the implications of employers transferring employee data to third-party job verification services?", "7a8d09ca-630b-49f2-921f-eb1e2dffc47c": "How do schools use data on free or reduced lunch status in their assessments?", "2b74ec7f-f8f1-40ba-b970-2b4fbc944395": "What are the ethical concerns surrounding the use of student data for predictive analytics?", "839d62aa-6521-47db-b195-5f55f3715e07": "What mechanisms can be used to sustain the value of deployed AI systems?", "8c59f600-8f81-40e2-8f76-cad08254ac3a": "How can organizations compare AI system outputs against predefined risk tolerance guidelines?", "5a461ec3-611e-43f6-af2a-7a7f88454170": "What are the risks associated with AI-generated content, such as CBRN information or capabilities?", "16e67bb6-1d80-4b1d-b60d-cda158c2d378": "Why is it important to document training data sources for AI systems?", "ddf72159-1801-49ab-a221-531088d69221": "How can feedback loops between AI content provenance and human reviewers be evaluated?", "f24bf2cd-d91c-4662-bfd9-31b03791b58e": "What are the benefits of implementing real-time monitoring systems for AI content provenance?", "c0e0ee49-2ab6-4eab-bafe-fec66c3023af": "How can organizations ensure that AI-generated content does not include obscene, degrading, or abusive material?", "c7548d81-fe0d-4316-a260-2d342818a5c6": "What steps can be taken to prevent harmful bias and homogenization in AI systems?", "91e539e0-ee4e-4e3b-bc8d-b3794ca3798a": "How can dangerous, violent, or hateful content generated by AI be managed?", "4c18144e-d6a3-4d13-a836-e55c43d2c5e2": "What is the role of information integrity in the context of AI development and deployment?", "18472313-2f95-4239-88f3-4a75df9cf246": "What are Model Cards for Model Reporting and why are they important?", "18e201b7-192f-4ea2-934b-df1184862535": "How do adverse action notice requirements under the ECOA and the FCRA impact consumers?", "07cfac24-a2ea-4bef-b577-15ed4935a4bd": "What information is provided in the FTC's guidance on using consumer reports for credit decisions?", "86d77516-8a49-4005-97e2-fef5020a40b3": "How does the CFPB act to protect the public from black-box credit models using complex algorithms?", "b2ac04a5-d89c-4fc8-8023-6bb6b8a814ab": "What are the key takeaways from the Conference on Fairness, Accountability, and Transparency (FAT* '19)?", "03bc6211-f0ad-4a75-b7aa-92f96064ce4b": "What are the adverse action notice requirements under the ECOA and the FCRA?", "75513281-57cf-4e3f-8495-cafc4e79d242": "How does risk-based pricing affect consumers according to the FTC?", "28e98921-df31-486e-a4bf-cd2a8f018ee4": "What measures has the CFPB implemented to address issues with black-box credit models?", "1942efe7-0de7-42dd-9f0b-23cdddc6969d": "Why is transparency important in credit decision algorithms?", "ba2751db-a092-4455-89ce-60ce0f2e5ff0": "How can businesses ensure compliance with adverse action notice requirements?", "43ab2e49-8484-42a0-b907-a326016b5fba": "What are the potential risks during the design stage of the AI lifecycle?", "71c80195-c590-4a6a-8455-cc14b7d76775": "How can risks during the deployment stage of AI be mitigated?", "bac1fcc0-33c2-4bd1-bcae-206282b1aebf": "What is meant by \"algorithmic monocultures\" in the context of AI risks?", "ded49efb-8ec5-43c7-90a3-414f486b61aa": "How do risks at the ecosystem level differ from those at the individual model level?", "aa5a5372-d095-4583-8dd2-04b30b8d377b": "What are some examples of risks that can arise during the operation of AI systems?", "d364a35e-d9b1-4892-aeee-562d6fe3fb16": "How can human behavior contribute to the risks associated with AI systems?", "8e058945-6592-48f2-a7c0-b29f59239765": "What are the implications of repeated use of the same AI model on labor markets?", "0586fc63-c513-4afc-a447-0f010dfa2c07": "How can the decommissioning stage of AI systems pose risks?", "5723f355-fc6d-4188-a997-6fc9df87d7e0": "What are the potential impacts of AI on access to opportunity and the creative economies?", "b1450fe5-2a1b-49c3-8181-b0908b22ec94": "How can risks from GAI system outputs be identified and managed?", "d6dc8fa5-06dd-4cb6-b9e1-3d99509fd36f": "What are the standard risk controls that can be applied to proprietary GAI technologies?", "43f41ff8-54b8-405b-97e6-387ac8c232c9": "How can organizations ensure third-party transparency when using GAI systems?", "def9231f-04c4-40b3-a87d-4a5d13f4664e": "What is the role of software bills of materials (SBOMs) in managing GAI system risks?", "0abe2ec1-662d-4cd9-8f9a-28ce9be69bbc": "How do service level agreements (SLAs) contribute to risk management in GAI systems?", "36dbeaca-841b-42b4-a5fc-2f1795f02564": "What is the importance of statement on standards for attestation engagement (SSAE) reports in GAI systems?", "e49097b7-7ffa-4581-8515-1b30cfa7d7b0": "What are the challenges in risk mapping and pre-deployment measurement for GAI systems?", "f51fa6cc-e9f9-4425-b85d-44db74827ce4": "How can robust test, evaluation, validation, and verification (TEVV) processes be applied to GAI systems?", "b85af260-3cfa-4a9c-bc21-802cd691f871": "Why is it important to document TEVV processes in the early stages of the AI lifecycle?", "7444a8c8-575f-4345-84f3-0124561379dd": "How can acquisition and procurement due diligence help in managing risks associated with GAI technologies?", "84e38c59-60d0-4319-81ad-3888d9b12506": "What are the benefits of involving representative AI Actors in the TEVV processes for GAI systems?", "80255fc3-d877-468b-97e9-7be818ed20da": "What is the AI Risk Management Framework (AI RMF) 10 for Generative AI?", "9516ed5a-2087-413e-925b-26135b0f5d06": "How does the AI RMF 10 aim to improve the trustworthiness of AI products and services?", "6fab3d01-f156-429d-831e-4ea194ff08bf": "What is the purpose of President Biden\u2019s Executive Order 14110 on AI?", "91adbba6-9d02-4f12-8ca2-25bf46b3776b": "When was the AI RMF 10 released?", "bbdcadfc-3db1-46fa-85d2-e443a126d455": "Is the use of the AI RMF 10 mandatory for organizations?", "36c3329b-2a66-4361-b5f7-7ce8ade47cec": "How can organizations benefit from using the AI RMF 10?", "aae224f2-ef20-4cd2-8f53-3e748c2dac1e": "What are the main components of an AI RMF profile?", "150d6339-723a-443d-bc9f-4b1be5ba3fb1": "How does the AI RMF 10 help in managing AI risks?", "3779173f-0285-4630-b333-78420055bd18": "What considerations are taken into account in the AI RMF 10 for Generative AI?", "2a0ab6da-3f10-4297-bb6a-887732c4d6be": "How does the AI RMF 10 align with legal and regulatory requirements?", "66823427-2ffd-4c77-909f-5289272bdb4c": "What is algorithmic discrimination and why is it a concern?", "0ab73255-60d0-4d92-ac1c-3d0c7a6949a9": "How can automated systems amplify existing inequities?", "feeecc56-069d-45a3-88eb-3f4d74890fcb": "What are some examples of algorithmic discrimination in facial recognition technology?", "88d366bd-b700-4c98-a848-aedce1be01ee": "How do hiring algorithms contribute to discriminatory decisions?", "00fc2bf2-fbad-4580-bd4a-05669d18fc7c": "In what ways can healthcare algorithms be biased against Black Americans?", "2844838c-8c42-4c48-a44f-63715f685e1d": "What are the potential consequences of data that fails to account for systemic biases?", "36ef20ee-eb6e-4f4e-9d65-e279ee7920d6": "How prevalent is algorithmic discrimination across different industries?", "3302a720-0035-40c3-a9b6-017c0952d77d": "What protections are in place to address algorithmic discrimination?", "1a75a965-db4c-48cc-a1ac-7e4bcb22e7a6": "How can we ensure that automated systems do not perpetuate existing biases?", "0e9714b8-1ef7-4875-9d9f-858297cad936": "What steps can be taken to mitigate the risks of algorithmic discrimination?", "69b6d24d-4f77-4453-bd79-e8af8137c7e1": "What are healthcare navigators and how do they assist people in obtaining health coverage?", "d3ffb77a-2b83-4c99-9923-bd42f0684d90": "How did the Biden-Harris Administration support healthcare navigators in 2022?", "575075f0-9aa1-4135-87b7-2b392d2cda2b": "What kind of training do healthcare navigators receive to help consumers with health coverage?", "c53668a5-710d-4526-98b9-af2788d4b125": "How do healthcare navigators help small businesses and their employees with health coverage options?", "84bee82d-ff9b-4d9e-8a7a-b6cbcb4db569": "What are some real-life examples of laws and policies that protect rights and access to healthcare?", "d74ae40a-97e3-4c00-bef1-b09032380ffd": "How do practical technical approaches help in protecting opportunities and access to healthcare?", "7b48a310-6aed-4f43-a279-f37e09939bba": "What is the role of sociotechnical approaches in ensuring healthcare access?", "3db05dac-a97a-4b1e-9652-d76803a23c04": "How can increased funding for healthcare navigators impact uninsured consumers?", "984009d5-34ae-416b-b936-3f783743a025": "What are the benefits of having more trained and certified healthcare navigators?", "1fcf65a3-0d6b-4145-99cc-0bf2c3235ad1": "How do healthcare navigators assist with completing eligibility and enrollment forms for health coverage?", "66fd1727-6e57-49a1-ae65-9fdb471abd5a": "What is the role of the National Science Foundation (NSF) in AI research?", "4d10f264-ec1c-496e-8dbb-69f985ae5cf1": "How does the National AI Research Institutes contribute to the development of safe and trustworthy AI?", "4f34a0ae-db65-487e-8242-a6f5458fa9de": "What are the key principles of the AI Ethics Framework for the Intelligence Community?", "4c4c9829-d71f-4438-a202-eaef5533887c": "How does the Cyber Physical Systems program support AI research?", "90a56106-7089-4755-973a-da4912ed88d1": "What kind of research is funded by the Secure and Trustworthy Cyberspace program?", "0a37c463-1465-453d-bbbe-74e8a11fe10f": "How does the AI Ethics Framework help implement ethical principles in AI development?", "bc9e1c96-6a89-4d9b-b96c-71acb36031e0": "What are the main goals of the National AI Research Institutes?", "037f5eee-4dd0-4bed-9151-ef0be3018604": "How does the NSF ensure the safety and security of AI systems?", "06f79190-3996-4bfd-86e5-6065a4dc96ee": "What is the importance of explainable AI algorithms in the context of the Intelligence Community?", "3df54901-e507-45fe-bd82-154e2d31aae0": "How do privacy-enhancing technologies contribute to the security of automated systems?", "c4da0ee6-b97a-4cac-839c-667bdb97a9d0": "What are the key expectations for automated systems to ensure they remain safe and effective?", "37843ed7-8a1c-4d60-818a-72b161e25abf": "How important is ongoing monitoring for the performance of automated systems?", "0944ea5d-dbdd-4f95-829a-6caacde3bed0": "What procedures should be in place for recalibrating automated systems?", "12d5b6aa-803b-4df4-8a6d-4fce86fdf65e": "How can automated systems be continuously evaluated for performance metrics and harm assessments?", "643c631e-a495-4f76-ac44-fc0226061601": "What steps should be taken to update and retrain machine learning models in automated systems?", "6fbfb445-cd6f-4999-b0b3-48d65d58c0e6": "Why is it necessary to have fallback mechanisms in automated systems?", "9c0537b0-0ed3-4084-aefd-70d1001d512a": "How do changing real-world conditions affect the performance of automated systems?", "379808b9-e51a-42f1-b658-7f085dd496a5": "What are the best practices for post-deployment modification of automated systems?", "f9ec3773-dc0b-474f-8e19-10f71c543467": "How can unexpected conditions be managed in the deployment of automated systems?", "caf8112e-e9f3-4acd-81fb-c3b49486c424": "What role does continuous evaluation play in maintaining the effectiveness of automated systems?", "581a5da7-213e-4a7d-9f8d-d4133dd57842": "How does harmful bias in GAI models affect different racial and gender groups?", "9d4abb67-4cfb-4342-9757-6880500e5378": "What are the potential consequences of GAI systems performing poorly for non-English languages?", "6c77fa09-63b8-42b1-ab8c-8a0878fe99b4": "How can GAI models perpetuate or exacerbate existing societal biases?", "a46e5b14-4ca5-47eb-b330-0d94b8f9f326": "Why might GAI systems be inappropriately trusted to perform equally across all subgroups?", "7fabb17d-bead-4be0-a042-a82244952276": "What are representational harms in the context of GAI models?", "b6bddb5b-9792-4d2b-8ddc-6bd3455e5a52": "How can disparities in GAI model performance lead to discriminatory decision-making?", "93e73653-3778-45ec-8b88-83ef0cee390f": "What are the risks of using GAI systems for lower-resource languages?", "0ce84b04-c919-4d13-a642-1c811d94eb54": "How can training data contribute to harmful bias in GAI models?", "8b538c35-c3ca-4876-93d6-3a9de1887248": "What steps can be taken to mitigate bias in GAI systems?", "07203f30-4f7f-4aca-8eca-7c309b4986f2": "How does the underperformance of GAI systems for certain subgroups compare to not using GAI systems at all?", "b3dc9b16-8ecb-4c62-ab68-b96bed0dfc8d": "What are the challenges faced by people without smartphones in accessing unemployment benefits?", "02ced4ba-2675-4cba-9819-e8e00d3cd558": "How does the digital divide impact the ability to claim unemployment benefits?", "98bb75ed-7a8c-4dce-86df-07d671be2a37": "What are the implications of the UIA lawsuit on the perception of unemployment in the state?", "da95bf2a-175f-49d9-b8a6-280808d008cc": "How does the state criminalize the unemployed according to the Detroit Metro-Times article?", "f6187e72-cd60-47bf-8a65-87c6ff917a35": "Why are doctors turning away patients with unbearable pain, as discussed in the Wired article?", "14dd793d-1318-45e0-bf65-ae5c770cde2a": "What role do algorithms play in the treatment of chronic pain and opioid addiction?", "d3a655b7-63e1-43d6-a477-2241c65e6d0a": "How does Amazon's use of bots for firing employees affect workers?", "777e4f21-26bb-4162-81e1-25f943df9293": "What are the consequences of being fired by a bot at Amazon?", "d4ec38ed-55a8-425e-af0d-8589faeb46ba": "How do machine managers at Amazon impact the worker experience?", "2a40a8e1-c0b7-4eac-a84a-5d63fbdb6c9a": "Where can I find the definitions of \u2018equity\u2019 and \u2018underserved communities\u2019?", "c54055bd-b859-4846-856f-3208fb311b0f": "What are the specific criteria for deactivating a GAI system according to MG-24-002?", "6f0ae6ac-c093-4863-8cf2-4ada7f9d42e7": "How should organizations escalate GAI system incidents to the risk management authority?", "b4852e25-ec60-482f-a671-b99fc5379d18": "What procedures should be established for the remediation of issues triggering incident response processes in GAI systems?", "0d20124d-250f-42b7-a215-c52597d6ff03": "How often should the criteria for deactivating GAI systems be reviewed according to MG-24-004?", "477cd099-57f2-473f-9e76-397ae38e415a": "What are the key tasks involved in AI Deployment, Governance and Oversight, Operation and Monitoring?", "dcf15838-d29f-4e4a-843a-165bf83a1bfe": "How can organizations ensure that AI risks and benefits from third-party resources are regularly monitored?", "9d4de1d9-a66b-4c82-935a-f7e97333ed5c": "What are the risk controls that should be applied and documented for third-party AI resources?", "070ee859-7379-4692-a8af-44336782308e": "What timelines should be provided to stakeholders for the remediation plan of GAI system issues?", "639643b4-60e7-474d-aee6-3ee349564306": "What is the role of the organizational risk management authority in managing GAI system incidents?", "acb51a42-9248-4132-bcd5-aa4101f783dd": "How should organizations document the risk controls applied to third-party AI resources?", "507836ec-d203-47f8-a680-09f83fa2a01f": "What is the Responsible AI Resource Center (AIRC)?", "0712927b-b14b-48bd-8873-1773a4748151": "What is the purpose of The Language of Trustworthy AI: An In-Depth Glossary of Terms?", "5a1bdd93-7277-481d-9646-c6981146f8d6": "How were public comments and consultations used in the creation of the document?", "4ce4e9f4-b9b5-4632-a08b-c5e41c2f4b8a": "What does risk refer to in the context of the AI RMF?", "d4e55ebe-4671-4b95-9b07-c9e5e246be26": "How can AI risks differ from traditional software risks?", "8b4d8ad8-933b-4290-9fb2-14ecdde49db9": "What are some examples of risks that are likely to materialize in a given context?", "04d3166e-c3f8-442a-a5a4-36726190ef49": "What are some examples of risks that are more speculative and uncertain?", "da1e7ff4-4699-42f3-b32e-97305e4b357a": "How can GAI exacerbate existing AI risks?", "81f01fdb-f899-4475-8c04-9e7fe197e698": "What are some unique risks created by GAI?", "88a166d0-e31c-43cf-8f58-baefce9d284f": "How can the magnitude or degree of the consequences of an event be measured in AI risk assessment?", "9ed882bf-45cd-4218-a475-bb18625ade4c": "What are the main ways hiring algorithms can introduce bias according to Miranda Bogen's article in the Harvard Business Review?", "56adf753-40ac-4593-bb8a-832feec13d31": "How is the TSA making flying easier for transgender people, as discussed by Arli Christian in the ACLU article?", "19cd8cd2-a1f6-479e-8713-95e8683eee7f": "What specific measures has the TSA implemented to accommodate transgender, non-binary, and gender nonconforming passengers?", "3e165023-0718-43ed-99b9-10cbcee9f4e1": "What are the concerns raised by the National Disabled Law Students Association regarding the online administration of bar exams?", "dfad7b64-3277-4f06-af37-d85af7857c4e": "How does automated test proctoring software discriminate against disabled students, according to Lydia X Z Brown?", "a41d0161-4967-4046-9c48-e87cea7d5bf8": "What are some examples of bias in hiring algorithms mentioned in the Harvard Business Review article by Miranda Bogen?", "bf872985-a9f6-4c68-ac13-c3442a951f5a": "Can you provide a summary of the four ways the TSA is improving the flying experience for transgender individuals?", "f53a3ba9-3917-4f06-a722-e4d54d8119c2": "What resources are available on the TSA website for transgender passengers?", "6fa39a37-eeaf-4520-b9bd-162fce45ab8c": "What are the key points in the NDLSA's report on online bar exam administration concerns?", "f4bf60dd-02c3-4248-bed1-4831c9772821": "How does the Center for Democracy and Technology describe the impact of automated test proctoring on disabled students?", "63eb9983-de78-4519-b2c8-f22b454ee053": "What are the legal and regulatory requirements for AI development and deployment?", "267043c7-c798-4c11-b2d1-9c33ddd4fb4e": "How can AI development be aligned with data privacy laws?", "d30f4bc2-2f5f-41a6-b0ca-38e7382ef444": "What are the implications of copyright and intellectual property laws on AI?", "fc798bdd-e26e-4ed1-8142-e17cd09368df": "How can organizations manage and document legal requirements for AI?", "1fc3dca0-6426-432e-bf6d-db436aa4dfd0": "What are the risks associated with data privacy in AI systems?", "3eb7529c-01dd-46f1-ba24-c428f4b98cbf": "How can harmful bias in AI be mitigated according to regulatory requirements?", "10147097-3b5f-4390-8fdb-61a55029b730": "What is the role of governance and oversight in AI development?", "b73e2ec4-11cf-4e83-9ef8-b0612a7df8b7": "Who are considered AI Actors according to the OECD?", "3f2795a8-623f-4759-be58-bac1f301777a": "What tasks are involved in the governance and oversight of AI systems?", "1dacc26f-f637-4f67-b91a-d11102d1bb85": "How can organizations ensure compliance with intellectual property laws in AI development?", "b5373d9d-ce4e-40bc-bcbc-4f675f59d1a8": "What are the disproportionate risks that AI poses to women according to the Brookings article by D West?", "029ed6d6-5b8c-45f2-8690-d47dc48f8232": "How do large language models (LLMs) perform in citing relevant medical references as discussed by Wu et al?", "3dd37534-24da-494e-b97b-5e3890f7f13e": "What evaluation framework did Wu et al propose for assessing the citation accuracy of LLMs in medical contexts?", "a89ead0f-a8bc-4db8-adae-b72aa1d2c3c5": "What evidence of racial bias was found in OpenAI\u2019s GPT when used as a recruitment tool, according to Yin et al?", "3babea8f-5928-47f3-962e-9b283207ab3e": "How can jailbreak prompts affect the behavior of large language models, based on the research by Yu et al?", "0af422b3-b85e-4b51-94fa-71fc9ab1d8fa": "What are some examples of digitally-disadvantaged languages mentioned in the Policy Review by Zaugg et al?", "1c9b32d4-4ae7-4a96-a889-035f67276bb2": "What are the potential implications of AI-induced racial bias in hiring practices as highlighted by Yin et al?", "9b7725c9-7b92-4fdd-a10f-8ec1530b228d": "How does the article by D West suggest mitigating the risks AI poses to women?", "649f7414-376a-4e58-8d1e-23d5e7ed9d6a": "What methods did Yu et al use to explore and understand jailbreak prompts in large language models?", "e78a0693-7005-4bea-89f2-c3ea112bce08": "What policy recommendations are made by Zaugg et al to support digitally-disadvantaged languages?", "9db21a04-c438-4476-ac0a-82338eae49b2": "What are participatory engagement methods and how are they used in AI development?", "97081408-da30-4645-9afe-f3307ed6cdc7": "How can field testing improve the usability of AI-generated information?", "289db7b2-4d79-467d-a5d9-9d5b231a0264": "What is AI red-teaming and why is it important for identifying system vulnerabilities?", "2d57ed17-a6f7-46f9-81ca-95cb462059cb": "How does feedback from civil society groups influence AI system design and implementation?", "4922c3b7-23a1-4ecb-9156-b04943f93fab": "What are the benefits of using focus groups in participatory engagement methods?", "f2e88045-e05b-41dc-8cec-46bbf532cb91": "How do structured, randomized experiments contribute to understanding AI interactions?", "8e4237f7-4dab-4b3e-872c-636b750a8551": "In what ways can AI red-teaming help in preventing discriminatory outputs?", "6a0cc42b-ef86-4bfe-8697-1dafa8d40ca3": "How can surveys be effectively used to gather feedback from affected communities regarding AI systems?", "a27db742-1147-4e73-b8f8-fb28f863182a": "What role does public feedback play in the maintenance or decommissioning of AI systems?", "1da6cbec-681b-41b5-8fdd-7e46b4b39a69": "How can insights from field testing be used to improve data quality and preprocessing in AI systems?", "dc7b408c-d2a4-440a-8bd3-382b37949adc": "How can I find out if my personal information is stored in a federal system of records?", "12c4f43b-f79c-40bf-89c5-5de9f0101a4f": "What steps do I need to take to contest the contents of a federal record about me?", "928f7047-c52c-49a0-aad2-2d36efcef6dc": "Are there any exemptions under the Privacy Act that would prevent me from accessing my records?", "8ee048c2-ac9d-46c0-8558-0d5e5e8a8743": "What legal actions can I take if a federal agency does not comply with the Privacy Act?", "7785c38a-a968-421a-b0d8-c15fe4003fa3": "How can I request a federal agency to amend or correct my personal information in their records?", "5af5e28f-c346-483e-8b52-dabdb08f98cf": "What kind of monetary damages can I seek if an inaccurate federal record affects my opportunities or benefits?", "6eec9174-86c8-46fc-84dc-0a9dadffd18c": "What are the procedures for accessing my individual information stored in a federal system of records?", "d9e3443e-a2be-4b7f-9ead-f1b68a8decec": "How does the Privacy Act protect my personal information stored by federal agencies?", "ed5ff628-1277-45a4-a100-1c1d064b76a6": "What qualifies as an adverse determination under the Privacy Act?", "29499a6f-b07f-4cba-b4bf-90e40d038c36": "Can I seek legal relief if a federal agency maintains an incomplete or untimely record about me?", "dd201fcb-d5b4-47aa-9fa7-584fdc9a91d0": "How do GAI systems impact the preservation of endangered languages?", "f95cd300-7368-4898-875c-8a16e2699308": "What challenges do GAI systems present to model adoption and inclusion?", "08be409c-62b9-4046-a4e5-41f7aef94b1e": "How can the use of GAI systems lead to undesired homogenization in outputs?", "165031b8-01ee-4b7e-a254-95b7729cbac2": "In what ways might GAI systems make it more difficult to use endangered languages in everyday processes?", "77d2f46d-9e77-41fd-8367-3d123120a90e": "What are the potential biases associated with GAI systems?", "41496cd8-8df9-4ece-9b75-799e48764e3d": "How can repetitive aesthetic styles in GAI outputs affect cultural diversity?", "8e9ba476-d233-4ed8-8772-0fbd52872bb3": "What steps can be taken to ensure GAI systems do not contribute to the loss of endangered languages?", "10c840b0-30ab-46e2-9109-d9b669bd57ac": "How does bias in GAI systems reinforce the problem of homogenization?", "6e44c18a-5777-4822-9e66-8bc1a5a2f194": "What are the implications of overly uniform outputs produced by GAI systems?", "85eab450-b260-459c-acfc-4403ea487fee": "How can we address the challenges of inclusion and accessibility in GAI systems?", "93694198-599c-4796-8cf1-d528b4f3fb10": "How can organizations ensure that automated systems are kept up-to-date?", "2c321c09-c163-4b0c-81f8-f536580d0caa": "What are the best practices for notifying people about significant changes in automated systems?", "65b87922-c4d3-45bc-b744-c2b89f7b4788": "Why is it important to understand how an outcome was determined by an automated system?", "cffd7b3d-0081-4a33-80e6-28b3fbf26823": "How can automated systems provide explanations that are technically valid and meaningful?", "20e03c70-f24d-4dba-9cb5-042b4cba722d": "What factors should be considered when calibrating explanations based on the level of risk?", "760cfb81-f3c9-4194-a7d3-602f41fab3e8": "How can summary information about automated systems be effectively communicated in plain language?", "f709685b-47a6-44a7-8f9e-3aa0df73870e": "What methods can be used to assess the clarity and quality of notices and explanations from automated systems?", "16141df8-9867-4de3-bcb0-a2b9fac32680": "Why should assessments of automated systems' notices and explanations be made public?", "a44f2530-9479-450c-9cfd-272c1f2071d6": "How can operators and others who need to understand automated systems be supported?", "38270bdb-0dd7-458c-b93a-daebec80be45": "What are the challenges in ensuring that automated systems provide useful explanations to users?", "c699565e-04ef-419e-94cb-1b796a737007": "What is the AI Bill of Rights and how does it relate to Executive Order 13985?", "547dfa62-9140-4639-82df-a9142ce5286b": "How do the Fair Information Practice Principles (FIPPs) influence data privacy laws globally?", "9af0586d-74db-446b-8e26-38be4dd9afc6": "What are the core principles of the Fair Information Practice Principles (FIPPs)?", "eccf5725-f424-4268-b727-1f1a40978434": "How does the Blueprint for an AI Bill of Rights incorporate elements of the FIPPs?", "abeee4d7-e9fd-4575-a169-f5d27f7e36bb": "What is the significance of the 1973 report by the advisory committee to the US Department of Health, Education, and Welfare?", "66addcfc-c316-415e-b410-381db4715a69": "How does the AI Bill of Rights support racial equity and underserved communities?", "a172a3a2-d810-4b13-909a-903ececb2cd1": "What are the key elements of the Fair Information Practice Principles (FIPPs) relevant to automated systems?", "a5209e31-d0db-40ff-9bb4-1750d45a7717": "How do the principles of the AI Bill of Rights align with civil rights and civil liberties?", "8ed364a4-97b6-4794-a155-78239f56aa6b": "What role does the Federal Government play in advancing racial equity through the AI Bill of Rights?", "cf81588a-da58-41b7-8f19-e0ed9fa5cd06": "How are the Fair Information Practice Principles (FIPPs) applied in different domains like privacy and civil liberties?", "20cc838f-302b-4a97-b9c0-048b821e21d7": "What is an algorithmic impact assessment?", "11441d7e-f3c5-47eb-9661-dc9501b61db8": "Who is responsible for performing an algorithmic impact assessment?", "96391b37-e002-4444-bc88-af07e80d1be7": "How are corrective actions taken in response to an algorithmic impact assessment?", "f173dfc5-537c-4934-943f-6a4a8209556a": "What should be included in an algorithmic impact assessment?", "adb72817-95df-4fe7-be09-43be351339a0": "Why is it important to make algorithmic impact assessments public?", "98945bdc-d7f5-48af-828b-72fdff9b0735": "How can algorithmic impact assessments help in addressing algorithmic discrimination?", "ce1d92ca-dd4d-4c46-a861-5f738828da2a": "What is the role of disparity testing in an algorithmic impact assessment?", "6739f71c-fbe1-4126-86a2-75deefb42217": "How should the results of an algorithmic impact assessment be reported?", "b3952c44-c80c-4aa5-b364-771c28f8d963": "What are design stage equity assessments in the context of algorithmic impact assessments?", "ab8785d8-fdea-42dd-9207-1331f4d206dd": "Why is it important for algorithmic impact assessments to be machine-readable and in plain language?", "ad91ce86-6dec-4abb-97c6-044f2e6af46d": "What are some examples of issues caused by the lack of human alternatives in automated systems?", "2a47278f-8456-435f-a92f-ad1569f822a9": "How did the unemployment benefits system in Colorado fail applicants without smartphones?", "4baeb7cc-0f63-4432-a61e-2cca08742d2c": "What problems can arise from not having a human review option in fraud detection systems?", "7229c62f-af34-49e6-a1b2-244381296eaa": "Why is it important to have human alternatives in systems that distribute unemployment insurance?", "a551e275-7aaf-4936-8b4a-335333fd8c65": "How can automated systems incorrectly flag entries as fraudulent?", "3185d577-2897-470b-b66d-2b878c1635f3": "What are the consequences of not providing a human fallback in automated systems?", "6b956523-9518-4fff-b4c4-3cb46fe34560": "How did the hospital software error affect a patient's access to pain medication?", "f829362b-3144-4e70-9964-54ff3cf5f3c8": "What are the risks of relying solely on automated systems for critical services?", "04775f45-fc8c-47ae-a74f-788e790dbb7f": "How can the lack of human intervention in automated systems impact people's lives?", "ff3d43c5-1076-4f90-9595-d7507024df5f": "What measures can be taken to ensure that automated systems have adequate human alternatives?", "7a87b77e-ba2b-4a75-85d3-eff3e7a4f1b3": "What are the potential harms of inaccurate inferences made by AI models?", "2af440c3-e3bc-417b-9229-b989c418f726": "How can wrong inferences of PII lead to secondary harmful impacts?", "f9ad7469-3e3c-4909-8679-251103726804": "What is the impact of predictive inferences based on PII or protected attributes?", "94623f99-aa39-458d-bf0c-452bdeae335c": "How can AI models contribute to representational or allocative harms?", "a18f484d-0c10-474e-b56a-fc1b92977406": "What are some examples of dignitary harm caused by information exposure?", "caabe18b-3881-404c-bba9-113c918db0f3": "How can extortion result from the exposure of sensitive information?", "6cb41015-478f-4102-8f71-ca101130bef4": "What are the risks associated with confabulations in AI inferences?", "b45acd2b-d605-4e83-8246-a99cd8d2ffff": "How can adverse decisions arise from predictive inferences made by AI models?", "4f89b591-6f2b-4813-bd57-b6ee9e7cd684": "What is the relationship between harmful bias and homogenization in AI models?", "259e3515-ab8c-4f3d-8cbe-178ee51a7ff6": "How can inappropriate inferences of PII disadvantage individuals or groups?", "f7f7c66a-12a1-4a76-88e9-6719de9f8272": "What are the main problems that the principle seeks to address regarding automated systems?", "0404c1f3-7897-4222-838e-d468ed48b862": "How do automated systems impact employment opportunities?", "da09c33c-a2d1-4eba-b8bb-9cadf83a607a": "In what ways do automated systems shape experiences in the courtroom?", "84e11e40-3503-4afa-9c0b-3bd17751dc5f": "Why is the impact of automated systems often not visible to the public?", "fb6baf2b-0c39-43c6-8a23-5a6286b57d3c": "How can an applicant determine if a hiring algorithm affected their job application?", "5ae8a14f-7af5-4fe1-ad8d-daa3b64b7412": "What are the potential consequences of a judge using an automated system to make bail decisions?", "b86dc33e-c44f-40f8-9201-6e77c52b2d3e": "How can individuals correct errors made by automated systems?", "44365a55-f06d-44c0-86f8-5e766884f298": "What steps can people take to contest decisions made by automated systems?", "cb8c33b7-5edf-4f02-827c-e51d99fe8c20": "Why is it important for people to have knowledge about the impact of automated systems on their lives?", "57d78d01-d80c-4a0d-bffe-90e8c5435146": "What are some illustrative examples of the issues caused by automated systems in various sectors?", "a7190971-83cc-4e5b-ad51-d097c2d2416f": "What is automation bias and how does it affect human interaction with GAI systems?", "31534a0f-52cf-452d-9a29-f8ac561198f7": "How can human experts overcome their aversion to GAI systems?", "2c413bc7-6f0c-41fa-ac50-d2f146083ecb": "What are the potential psychological impacts of emotional entanglement with GAI systems?", "f493ae8c-e533-406a-8fc5-5c6bdaad070b": "How can over-reliance on GAI systems be prevented?", "589fdab2-8712-4a25-9c59-8f26e281a6dc": "What are the risks associated with confabulation in GAI systems?", "3f801419-15e7-46cf-8d7a-d2709b6b5792": "How does automation bias contribute to the homogenization of information?", "2acf1a52-6ed2-4c87-9d62-518df86733d3": "What strategies can be implemented to mitigate the risks of bias in GAI systems?", "68b6149d-8a90-4b40-b32e-6e844ff70543": "How can humans balance their expertise with the use of GAI systems?", "bfe3017a-f8b1-49b4-8022-1d6c6b18b595": "What are the benefits of using GAI systems despite the potential risks?", "66d721dd-e056-41a0-9177-35ec1a02f2a3": "How can emotional entanglement with GAI systems be managed to avoid negative impacts?", "7994cad7-21e2-4e09-aca5-f56ef1ae8a5a": "What are the ethical considerations for developing automated systems that could potentially violate safety?", "47e3ea93-fd88-4971-8203-e36fc3545d64": "How can unintended safety violations in automated systems be identified and mitigated?", "de90f1a6-2df7-4240-944b-87dad8ddb4c3": "What steps should be taken if an automated system is found to have safety violations after its launch?", "b0f19328-390f-4526-9bd5-58e3217d2939": "Are there any guidelines for rolling back or modifying automated systems with safety risks?", "3a98c1d4-e98a-4339-a8d8-666a62f395d1": "How can developers ensure that automated systems do not have unintended harmful consequences?", "3e20c7ee-70ab-4ad1-b14f-32dfe44d0c85": "What are the best practices for ongoing risk mitigation in automated systems?", "a13b0ccd-e3a9-4ab3-afc9-d9c863fbeb66": "How should companies handle automated systems that have been found to violate safety standards?", "d904e7ea-ad3b-4610-ab7e-0e02f95f7b78": "What are the potential risks of using automated systems without proper safety checks?", "2fbedd50-8ea8-4da8-a425-802da3096391": "How can the safety of automated systems be continuously monitored after deployment?", "1ec42e53-7159-49a1-9293-810d7a184a7f": "What measures can be taken to prevent the development of automated systems intended to violate safety?", "a0842cf3-00a4-4746-87d9-6ac45ada3ebd": "What are built-in protections for data privacy?", "b76e72b6-358d-4943-98de-cad3c4c392ea": "How can I ensure that my data is only used in ways I approve?", "4f6747b8-9ad2-45ed-8979-f605d5765654": "What are some examples of abusive data practices?", "8effaebc-2db1-4d37-852d-5b080b55344a": "How do design choices impact data privacy?", "ba664a46-2556-466b-94a9-e6c9881f6bc5": "What does \"privacy by design\" mean in the context of data collection?", "412a6863-0745-4d66-8b48-137fc5c03a6e": "How can I verify that a system respects my data privacy decisions?", "a96cda8b-8d4a-4085-b297-fbf4fc69d244": "What are alternative privacy safeguards if consent is not possible?", "c4c103d2-5129-4be7-bf42-4971da92e49a": "Why is it important for data collection to conform to reasonable expectations?", "4a2850be-c31b-461e-9165-f82e606b10ff": "How can I identify if a system is using privacy-invasive defaults?", "398d3a34-f7cf-44c4-81ea-d314e9f92196": "What should I do if I feel my data privacy has been violated?", "9b1e7e8a-3e78-4c98-a0df-24b37ca791cf": "What techniques can be used to mitigate biases in GAI content and data?", "0a69cf57-ac9d-423f-896d-b9e4e02f762a": "How does re-sampling help in reducing representational biases in generated content?", "164c840b-8cfa-4c20-a441-123e95824ffb": "What is adversarial training, and how does it mitigate biases in GAI content?", "e20bd84c-d838-4049-a2df-fba4b9d06ea1": "Why is it important to evaluate GAI content for representational biases?", "387e47d4-c086-4a07-aee6-28a9fa60cad7": "What are the potential risks of not addressing harmful biases in GAI output?", "3700f1e4-cf35-4c27-b2c3-9101bf5d8dfd": "How can re-ranking be employed to address biases in generated content?", "8c76e76d-83c9-4a57-a7df-b1c0e035ef8b": "What steps should be taken to analyze GAI output for harmful content?", "7d2386c3-a371-45d9-965f-2c7a9c11567e": "What types of harmful content should be checked for in GAI output?", "badd4da0-e5f0-426d-ab2a-1019b483cc97": "How can due diligence help in identifying potential misinformation in GAI content?", "4da36b86-9edb-4192-abf8-385aa94c36e8": "What are CBRN-related or NCII content, and why is it important to monitor them in GAI output?", "f377e766-01de-4a90-9986-ecb3ee8d61a9": "What are the best practices for designing consent requests that are easy to understand?", "4490f651-668a-4e60-9931-3c6e393d09b8": "How can user experience research improve the readability of consent requests?", "68e419bb-fa35-4890-98c7-4c8a11d9c78e": "What methods can be used to ensure consent requests are accessible to users with disabilities?", "838be5c8-7e39-41a0-8cc2-5d54526523b5": "Why is it important to avoid \"dark patterns\" in user experience design for consent requests?", "8540243f-924a-413c-bdad-29d5f1240c58": "How can consent requests be tailored to different languages and reading levels?", "c05097c0-b8be-4d9f-94ad-f28a74c0bbf6": "What are \"dark patterns\" in user experience design, and why should they be avoided?", "ed30f33c-f72f-4ca9-a986-e78ea5a84f34": "How can we ensure that users understand the contexts, time span, and entities involved in their data consent?", "078872ce-c620-44bc-b9d9-715ca524c82e": "What are some effective ways to test the comprehension of consent requests among users?", "c9c8531a-c33d-47fb-9c20-0a74872c9cd3": "How can user experience design improve the transparency of data and metadata consent requests?", "bd0d1036-d121-46a7-a63d-633b1fe52539": "What role does user experience research play in making consent requests more accessible and understandable?", "64ded336-d26a-4bba-9264-29a782f46b17": "What are the potential risks associated with the misuse of AI systems by humans?", "a1524a0a-e5c7-4b05-9291-a9f012c2f8a7": "How can the distribution of harmful deepfake images impact physical safety?", "69cb94c7-5d81-4222-9d53-052f0edd2720": "What are the long-term effects of disinformation on societal trust in public institutions?", "10493f76-3a15-41b8-a590-28e28ca5d22f": "How do the characteristics of a GAI model influence the presence of risks?", "0aa175b1-cf6c-4db9-95ae-790c02ed0420": "What factors should organizations consider when measuring GAI risks?", "e8a86a82-58ef-4852-8a9f-46998fe000e6": "How can the architecture of a GAI system affect its risk profile?", "e0c9a867-2ae3-4d5e-b74c-b2145e48b693": "What role do training mechanisms and libraries play in the safety of GAI systems?", "f497ff9f-1f6b-49ff-92b7-b97bbf4e0d33": "How does the availability of model weights impact the security of GAI systems?", "82c14235-06d7-4a04-8d16-eefd798350a9": "What are the implications of using different data types for training GAI models?", "6e3592cd-fc1e-495d-9976-3cea02adf35a": "How can organizations tailor their risk measurement strategies for GAI systems?", "bb8fd71c-8305-452b-bcbf-823fa999f419": "What are the Department of Defense (DOD) AI Ethical Principles?", "84ddfcae-5a84-4ca2-b23f-9f2993a78864": "How does the Intelligence Community (IC) AI Ethics Principles and Framework guide AI use in national security?", "6afc1f62-ea09-46aa-a9b2-a2231efa41db": "What is the Blueprint for an AI Bill of Rights?", "50dbd6b6-2f67-425a-8549-e938e1e443c4": "How can the Blueprint for an AI Bill of Rights inform national security and defense activities?", "33c03e38-7064-41dd-8c15-2570eff220f3": "What are the special requirements for AI in national security and defense activities?", "c062971a-0cf8-4ef1-93b3-5fca436d15d4": "How does the federal government ensure the use of trustworthy AI in law enforcement?", "3664af6f-9a6b-4750-9157-5b8c10c049bf": "What safeguards are in place for AI systems handling classified information?", "57f12af2-eace-4916-bf6c-caa521375c02": "How does the Responsible AI Implementation Pathway impact defense activities?", "3421dbb5-bc3b-4a71-9aba-9794e6c02c61": "What role does the Blueprint for an AI Bill of Rights play in the implementation of AI policies?", "1ea5b81c-aa5d-4fad-851a-f32df353f699": "How are existing policies governing automated systems applied to national security activities?", "bb9c137b-e957-4d1b-b681-1150450070b8": "What are the potential harms of using AI to generate non-consensual intimate imagery (NCII)?", "b0543347-b171-470d-ad58-452023d32540": "How can AI-generated content be managed to prevent the creation of child sexual abuse material (CSAM)?", "420598ea-3a86-4086-a5a1-8ca8b6a218a1": "What are the characteristics of trustworthy AI in terms of accountability and transparency?", "b2067f9b-b092-45f0-9fef-ed8c776f2ec2": "How does AI-generated obscene content impact privacy and psychological well-being?", "9d318383-e177-487e-b4cc-8d2e8e8fcc13": "What measures can be taken to ensure AI-generated content is fair and free from harmful bias?", "78e29c0f-c807-43a5-87c1-f4c5adab2595": "How can the spread of AI-generated deepfakes be controlled to protect individuals' likeness and voice?", "1d9240a9-0d09-4243-869a-45ed6bd3e9db": "What are the legal implications of generating explicit or obscene AI content?", "0dd67cb2-1fd7-4f2a-8672-8384a5b08a73": "How can AI be used responsibly to avoid creating degrading or abusive content?", "558abc03-0ada-41ab-b040-b6a193e5b238": "What are the downstream negative consequences of AI-generated CSAM on law enforcement efforts?", "a03bd0ad-5366-46e0-b712-e2748c71adf5": "How can privacy be enhanced in the development and deployment of AI technologies?", "7d190ccc-08eb-4795-975a-b70b5b5615ec": "How does surveillance impact student expression in educational settings?", "36548052-71c8-4515-ac0b-ad22a66ff05f": "What are the potential negative effects of surveillance on tenants?", "9ac8b717-1ae9-40dd-a3f6-5d158e342089": "In what ways does surveillance blur the boundary between work and personal life for workers?", "6b5a119e-29e8-4818-8d39-1e9518975f3e": "How can surveillance exert damaging control over workers' lives?", "5a0058ad-c9e9-4177-8811-35405c083ed1": "Why is the misapplication of data from criminal justice settings problematic for housing access?", "a1134775-18f2-4e09-af57-88092617afdc": "How does surveillance technology shift the burden of oversight from employers to workers?", "1dc6b0e5-60ff-4939-b09e-5d09b8373385": "What are the concerns regarding the use of surveillance in schools?", "b0b4a730-7836-419d-9d06-8a4e167aa24e": "How does surveillance technology affect equality of opportunity for tenants?", "3e475a7b-f183-48f1-9831-ecd371bfa399": "What are the chilling effects of surveillance on student behavior?", "91cdf914-e675-47bf-93d5-c257b52a9a51": "How should the assessment of surveillance technologies be conducted to ensure fairness?", "2e1a0ef5-cf28-488d-8c12-76d6037e5541": "What is the process for a human review of criminal investigative matters?", "ea3e3a56-e8b5-4d12-9369-363db39673a1": "What are the statutory requirements for judicial review in criminal cases?", "dfaba32e-19b0-4171-9fff-cc08fe20d751": "How do civil rights laws protect against discrimination?", "399b8802-887c-4184-b0f2-1a2bb5d07543": "What role does judicial review play in protecting civil rights?", "9dd9b476-9945-476b-9194-d8c83c4f9121": "What are the key elements of civil rights laws in the United States?", "3ed61f5b-fb54-4c4c-b6e5-0883b23b939d": "How does the judicial system ensure compliance with civil rights laws?", "dc4b76d1-b12c-4871-9175-8b56b5ad43ec": "What are the common types of discrimination covered under civil rights laws?", "a2334897-6fd9-497a-98b9-6686d453c2ad": "How can individuals seek judicial review if they believe their civil rights have been violated?", "0c5ef9a5-ec71-4016-8ae6-d82d2f95a1c5": "What is the importance of human review in criminal investigations?", "7a2b2ba9-a488-4c90-b169-70168efcc780": "How do statutory requirements influence the judicial review process?", "3fd5f3df-b1eb-4d8b-ab8d-07dddcc7fb48": "What are some effective strategies for testing AI in crisis situations?", "3be1b1c1-3098-49a5-b204-34bfa97d73b3": "How can we ensure information integrity in AI systems?", "7a009e96-556c-4842-92a2-a7b32f8146b7": "What methods can be used to identify and mitigate harmful bias in AI?", "25fac591-48bb-4ed2-bded-de52900f6c77": "How do we address the issue of homogenization in AI content?", "ec3564d2-3ce8-4426-b4d7-b66f34d730e8": "What are the best practices for handling dangerous, violent, or hateful content in AI?", "8e35ecf3-062b-4a03-810e-8eae31b35e67": "What roles do domain experts play in AI design and development?", "a0f073dc-3521-48db-9264-58f3bd671c3a": "How can end-users be effectively involved in the AI development process?", "29b2f6cc-206a-4bd6-98c7-e2c851e3a8b2": "What human factors should be considered during AI operation and monitoring?", "a86dc0bf-80f8-4a7b-969d-cf58b6502c4d": "How can AI systems be configured to handle ethically sensitive contexts?", "481d542a-46dc-4b5e-8bbc-a6e1094820a1": "What are the key tasks for AI actors in ensuring safe and ethical AI deployment?", "4a6050b2-f6b6-4ac9-939c-2e1188e92e89": "What are the key principles for designing ethical automated systems?", "72d17156-9c97-4463-a90b-1619a6608c3d": "How can automated systems impact public rights and opportunities?", "85b5625a-d5ea-45b5-b7b3-e66d4556da73": "What steps should be taken to ensure automated systems are fair and unbiased?", "8b7eeeff-ae14-458b-978e-5c1fc9573219": "How do you integrate ethical principles into the technological design process?", "7b875bc5-cd9a-4069-bcfa-6de556eb6548": "What are some examples of automated systems affecting access to critical needs?", "ee228074-989d-4a9b-bb46-df0a26dfda27": "How can designers ensure that automated systems do not infringe on public rights?", "89b66459-d623-4a30-a195-8da50e72a096": "What role do ethical guidelines play in the development of automated technologies?", "9a2bb4f3-2d1a-4689-9dfd-70c1a4fcfade": "How can we measure the impact of automated systems on public opportunities?", "ea968134-16f4-4d5c-810d-6049e27309d5": "What are the challenges in implementing ethical principles in technology design?", "a62f4790-c903-4ecf-bd87-b92068d5138a": "How can automated systems be designed to enhance public access to critical needs?", "9e50e870-f706-492e-b58e-93871354422c": "What are aggression detectors and how are they being used in schools?", "56433327-6403-42b5-bf0e-0d4ac4b47722": "How effective are aggression detectors in monitoring student behavior?", "bfb3f439-fb7d-4a61-b36f-ce7e06ea95fa": "What are the privacy concerns associated with using aggression detectors in schools?", "2e31e7e4-1966-455f-9c93-2f0416756f97": "How did cheating-detection companies profit during the pandemic?", "552e3fce-d322-41d0-a8d1-3af4d9b6d239": "What are the main arguments students have against cheating-detection companies?", "9f9d57e8-6574-422f-a98d-9523410c912d": "How does virtual testing disadvantage disabled students?", "6f686792-3271-44f2-962a-d0c914f0a618": "What are some examples of ableism and disability discrimination in new surveillance technologies?", "608ada78-40e7-49ac-a75a-e38f46e3d296": "How are new surveillance technologies impacting education for disabled students?", "44ee99fa-4fa1-4199-a49e-31e3f890d5de": "What measures can be taken to ensure virtual testing is fair for disabled students?", "b9dd8dbc-8dcc-4aa5-ae17-13bc77130913": "What are the ethical implications of using invasive surveillance technology in schools?", "f49391ff-b450-458f-8e1d-f4b2b768a48b": "What role did the American Civil Liberties Union (ACLU) play in the development of the Blueprint for an AI Bill of Rights?", "3c010abe-44a4-4a61-9b06-c9c60c98d68b": "How did the Aspen Commission on Information Disorder contribute to the discussions on AI oversight possibilities?", "815c1373-abe0-4296-ac84-38501b0c77cd": "What insights did the Australian Human Rights Commission provide regarding the potential harms of AI technologies?", "9eec3afd-f85a-4f17-a4d9-2c0989096d84": "In what ways did the Brookings Institute influence the positive use cases of AI discussed in the OSTP meetings?", "b795e850-79da-4183-9560-e011ed68a0a6": "How did the Center for Democracy and Technology participate in the development of the AI Bill of Rights?", "0ed96dda-2f6e-4335-86b8-3a5d06011bbd": "What specific ideas did Deepmind offer during the OSTP meetings on AI technologies?", "2a6ac783-bbc1-4474-9864-2029c75aea04": "How did the Center on Privacy and Technology at Georgetown Law address privacy concerns related to AI?", "3e13f6fd-312b-432b-9012-933f8b0a169a": "What contributions did the Data and Society Research Institute make to the discussions on AI oversight?", "7b11f5c5-827e-4e70-85f7-d83417de66c7": "How did the Electronic Privacy Information Center (EPIC) engage in the conversations about AI harms and benefits?", "fc17d202-010f-4306-916d-724cc681a109": "What was the focus of the EdSAFE AI Alliance's participation in the OSTP meetings?", "690220f2-52f5-463a-a2bc-b46c7e1aa79c": "What are the key privacy risks to consider during the development life cycle of an automated system?", "e2b24491-dd1a-45d0-a381-86ca5ec207df": "How can privacy risks from reidentification be mitigated in machine learning models?", "56f6feff-327b-4075-ac32-9d237ff6468f": "What are some potential harms to non-users of an automated system due to inferred data?", "425a7779-bf1b-4757-8833-e612c9b1ea05": "How should data collection be communicated to individuals whose data is being collected?", "e03f414b-1fb3-4067-99fc-cd4b122f509d": "What legal considerations should be taken into account when collecting data for training machine learning models?", "0d06fec9-3c74-49df-bc13-1e3ac9679a8d": "How can user experience research help in ensuring that data collection practices align with user expectations?", "b13e829f-73e8-4b70-9adf-6ea6b7b298e8": "What are some effective technical measures to minimize privacy risks in automated systems?", "ad29fd63-96d1-4788-8c4e-794dd0d3f326": "How can policy measures help in mitigating privacy risks associated with community surveillance?", "cefe533c-58c1-4179-b1f7-9134e20f1d19": "Why is it important to minimize data collection in the development of automated systems?", "61db5427-3644-439f-9a42-012708bb8917": "What steps can be taken to ensure that data collection for machine learning is consistent with user expectations and desires?", "7d332e8c-9943-4cdf-8bb4-1a3b498766ea": "What is the importance of tailoring explanations to specific audiences?", "b8324cd6-d521-45f3-8ba9-08ce631df758": "How can user experience research help in assessing the effectiveness of tailored explanations?", "05f09f2b-477a-4dbf-aaec-b5af1923c6b1": "Why might an explanation to a decision subject differ from one given to an advocate or domain expert?", "f022ec7a-8358-48d6-824c-0c26e658b35a": "What mechanisms can be used to build understanding and intuitions for a stated purpose?", "469f8389-8d8d-4b27-a69a-f16514c85c43": "How can explanations be effectively targeted to different audiences?", "5e39df0c-36a5-4afa-a2f9-6c5e341815f9": "What are some methods to assess the tailoring of explanations?", "8d3feca0-94b3-4b4a-a785-23a3b9b9a23c": "Why is it important to clearly state the audience for an explanation?", "3a3c3db2-4132-4478-a847-b36068c56e01": "How does the role of the recipient (eg, subject, advocate, expert) influence the type of explanation provided?", "15467e60-3777-472b-bd0b-47bf9f467a78": "What are the benefits of providing tailored explanations in decision-making processes?", "9a7b141e-920a-487a-a055-e1e9f4f1b2e6": "How can plain-language statements about causality differ from other types of explanations?", "ab11ab5b-818a-4880-8e91-ed269bd1af2c": "What does it mean when a document states that mentioning commercial partners is for information only?", "df1199d7-da58-4fef-8f9f-07735134932e": "Why do some documents include a disclaimer about not implying endorsement by a US Government agency?", "5958036c-3258-4303-8b1a-1622e068421a": "How should I interpret references to academic partners in a government document?", "5a32b7cd-ddd5-4513-abdf-563e5cd76816": "What is the significance of stating that materials or equipment are not necessarily the best available?", "fee5f65d-cb22-46ee-8464-222e373ff06b": "Why might a document specify that it does not intend to imply recommendation of any products?", "4a58ee08-f3de-45fd-907f-e153459dc81e": "What is the purpose of including a disclaimer about non-profit partners in official documents?", "d42d824c-1120-43e8-9235-7572b76c40a4": "How can I determine if a product mentioned in a government document is endorsed by the agency?", "4a312aa6-5cb4-4c06-8984-88e91ac45dc4": "What should I consider when a document mentions commercial entities but includes a disclaimer?", "d04730cf-a6d4-47bc-a699-0e3df94761de": "Why do government documents often include disclaimers about the quality of mentioned entities or materials?", "14564a8a-cdac-40c0-a780-78be519b65dd": "How does a disclaimer about not implying endorsement affect the credibility of the information provided?", "569527ac-7ac6-431b-875e-d434eb402c21": "What is AI red-teaming and how does it help in assessing privacy risks in AI systems?", "8389f03a-5744-4818-89fe-c077ff7f056c": "How can AI systems output training data samples and what are the associated risks?", "1ccccd94-2c43-4041-a4bc-08e24d811d35": "What are model extraction and membership inference risks in AI systems?", "93b0c907-004d-4f32-8b53-a052b75beeff": "How can AI systems reveal biometric or confidential information, and what measures can be taken to prevent this?", "a7f6c8ab-1b04-4dfa-9f57-4235258646b6": "What is the importance of engaging with end-users to understand their concerns about content provenance in AI systems?", "526267ce-38f4-4e58-b51d-6ae5ff0cf0dd": "How can AI systems track or reveal the location information of users or members of training datasets?", "b79cbec1-977d-4eb4-83ae-3d2d9ac42e08": "What are some techniques for designing provenance data-tracking in AI systems?", "9fa37ff2-7f29-4880-94c1-06fb3c6e92d5": "How does the Human-AI Configuration impact the privacy risks of AI systems?", "93413343-a62f-4859-8ee9-a611536c2b93": "What role do domain experts play in the operation and monitoring of AI systems to ensure privacy?", "48834fa9-9abe-4fae-a27c-636139f88c50": "How can intellectual property be protected in the deployment of AI systems?", "65958d5c-13fc-4718-8038-77c445872b42": "What are the key expectations for automated systems in terms of data privacy?", "ffe21033-700d-4f6d-aace-0e85d2620745": "Why are traditional terms of service considered inadequate for protecting privacy?", "8c46db62-ddab-49e2-b983-32432a14f583": "How can built-in privacy protections enhance data privacy in automated systems?", "4a376bd0-31f5-4955-8cfe-1e0e65d8f7e0": "What is meant by \"data minimization\" in the context of automated systems?", "7e329714-1d9f-4b04-926d-a8d79ddfdd9d": "How can transparency be ensured in the use and collection of personal data by automated systems?", "7d478e4e-d640-4a81-a971-a2d88d655d78": "What mechanisms should be in place to allow users to control access to their data?", "61151ee6-a28e-4a40-97ad-d1edeee36eb6": "How does \"privacy by design and by default\" differ from traditional privacy measures?", "b3576af0-4c36-49f5-a0e8-247d2ec6f65d": "What are the benefits of having clear mechanisms for users to manage their metadata?", "b624d6cb-faa1-4468-96a8-136321416574": "How should automated systems handle the sharing and storing of personal data to meet privacy expectations?", "8ecd7751-64ef-421e-a44c-3231886cdc17": "What role do technical standards and practices play in the development of privacy protections for automated systems?", "632ebbb0-13c7-4a44-b49f-bb277513d09c": "What is the importance of verifying deduplication in GAI training data samples?", "e06e7091-ac74-4abc-bc2b-da388c1149b9": "How does synthetic data impact the deduplication process in AI training?", "64518426-3d37-4769-9d8d-826b0577f97a": "What are the potential risks of not verifying deduplication in AI training data?", "dc8b4a4c-213f-4f2e-932c-a9a6f8cdadcc": "How can harmful bias and homogenization affect AI deployment?", "1bcb29e6-07a9-43ff-a455-16802ef28195": "What roles do domain experts play in AI impact assessment?", "19e66fef-7521-471f-82e2-f6884868acaa": "Why is it crucial to involve end-users in the operation and monitoring of AI systems?", "488f2216-2ff2-4ee4-9851-37299ad2c6c7": "What are the best practices for ensuring information integrity in AI systems?", "64edf8a2-3462-4be0-976d-1fddeea48012": "How can AI actors mitigate the risks of harmful bias in AI systems?", "b841ebb5-559d-4fe8-881f-c79ff7004ee3": "What is the role of TEVV in AI deployment and monitoring?", "5a0bd7f7-a52e-418f-9ada-e1fe84848613": "How does deduplication of training data samples contribute to the overall performance of AI models?", "64a056c2-8ae4-4280-874c-4a01461cc3e4": "What are some examples of state and local governments responding to AI-related problems with legislation?", "d69e8d1e-a600-475f-9486-61b3c75a2df4": "How have courts extended longstanding statutory protections to new and emerging technologies?", "2dbbbadc-b880-41d0-bb6c-e682dacb3df7": "What companies are known for incorporating additional protections in their automated systems?", "2827fc62-14af-4e2c-b663-ba391d6d25ba": "What innovative guardrails are researchers developing for the ethical use of AI?", "7fb6fed7-6aae-4ccc-b597-ab7e62e9b21f": "What are the key principles proposed by advocates and researchers for the ethical use of AI?", "44938ddc-9358-4c82-94f2-840413742d55": "What is the OECD\u2019s 2019 Recommendation on Artificial Intelligence?", "61da46c4-d66a-4522-bc97-af4fc2456222": "How has the United States adopted the OECD\u2019s principles for trustworthy AI?", "3f063cef-02a0-408b-98c7-56446e0fc13b": "What are the main principles outlined in Executive Order 13960 on AI?", "b4c11f6f-dc78-45df-9b02-6c9e97e63441": "How does Executive Order 13960 aim to promote the use of trustworthy AI in the federal government?", "a88f3780-0edd-49b8-89f3-212ba3ce8b3a": "What role do government organizations play in proposing principles for the ethical use of AI?", "ba2105e2-73d4-4990-9944-6d240e81707f": "How can automated systems be designed to prevent discrimination in loan approvals?", "17ebc163-d3e6-449c-980f-7ed26f839df6": "What are the basic safeguards against bias in automated systems?", "aab856e9-8ff2-46d9-893b-b6d07ab393c6": "How do automated systems impact underserved communities?", "cbad6951-7c8a-46df-bb70-c92a3f311a56": "What measures can be taken to ensure fairness in automated hiring processes?", "79e16b79-9d36-4087-8659-146694974dfc": "How can we ensure that automated systems treat all people fairly in the criminal justice system?", "1b05d0a8-49d2-47be-ab48-25a75c6e77f6": "What are the potential biases in using educational attainment in loan underwriting models?", "a980423a-f92e-407d-8954-c365cd973ffd": "How can we protect against abuse in automated medical treatment and payment systems?", "70182aa9-6598-41d8-94c5-c86d69052289": "What proactive protections can support underserved communities against automated system biases?", "c0cdbc54-4086-43e2-9a8b-0e45b61ecc4e": "How can nontraditional factors in automated systems lead to discrimination?", "732b7212-2022-429b-9d2d-ea2f1ff7d3f2": "What are the implications of higher loan prices for HBCU graduates in automated loan pricing models?", "9875b4af-3367-4c2e-9a31-faf2702adfa5": "What are the best practices for reviewing and documenting the accuracy and relevance of data used in different stages of the AI lifecycle?", "6fe66997-2216-429a-9ef4-7fe53eb306b3": "How can harmful bias and homogenization be mitigated in AI systems?", "36ec6e8f-35e5-4186-b6d7-f265dcdef11f": "What techniques are effective for fact-checking information generated by GAI systems?", "7d63e0e7-2c2e-4330-bdf2-4c7e114b7805": "How can the accuracy and veracity of information from multiple or unknown sources be verified in AI systems?", "bfa45ef0-bea8-47fc-b980-0b69ed2e1008": "What methods can be used to develop and implement testing techniques to identify synthetic media produced by GAI?", "6df2f1c4-ff8a-4107-a463-f56276352018": "How can one distinguish between GAI-produced content and human-generated content?", "51560d91-654c-4d78-bfbe-98c8ec9efde0": "What are the recommended plans for regular adversarial testing of GAI systems?", "9fde8cf0-b0b2-45f7-ad80-cadc55db3835": "How can vulnerabilities and potential misuse of GAI systems be identified through adversarial testing?", "b5e1a791-bb5b-42e1-b095-4eddeb8cbe89": "What are the key tasks for AI actors in AI development, domain expertise, and TEVV?", "3d828c80-9b73-4da4-a5ca-9009d879a58e": "What processes should be in place to ensure operator and practitioner proficiency with AI system performance and trustworthiness?", "8fd42408-bbd3-4239-b478-4be231789ff6": "What are the benefits of providing limited waivers of confidentiality for automated systems?", "41478b94-524f-4cb6-a05f-d28d7bf4f9c5": "How can designers protect intellectual property while allowing meaningful oversight of automated systems?", "607f4dd7-ca7e-4ee9-b4a8-f5f9760aeb1f": "What measures can be taken to ensure trade secrets are not unwarrantedly disclosed during legal discovery?", "dc9d51d9-e01e-4c24-8bc5-f2d310dd159f": "Why is meaningful access to source code and documentation important in sensitive domains?", "d012d297-b626-462a-868b-099e4ebe5d08": "How can automated systems be designed to provide built-in explanations for high-risk scenarios?", "19032e5d-0bf0-4167-86e2-54f143702e03": "What is the principle of Notice and Explanation in the context of automated systems?", "46b67447-c9d2-4689-b32c-eb292015ef9b": "How can fully-transparent models benefit the examination of automated systems?", "bbd073b0-20ee-4d44-ba79-37e22da7f19b": "What are the challenges of balancing confidentiality and transparency in automated systems?", "9fd04f5e-f2a7-4d3d-b5fb-3c5182e8df33": "How can court orders be used to protect sensitive information during the examination of automated systems?", "4a50706f-2be3-4191-a799-d03cfb6bd582": "What role does legal discovery play in the oversight of automated systems in sensitive domains?", "ef610b4b-0ce3-4569-b444-685ef6d6f71d": "What is algorithmic discrimination and how can it violate legal protections?", "3332f97e-e957-4370-b156-5b2e74510318": "How can designers and developers protect against algorithmic discrimination?", "38324b8e-0942-49f8-88c3-e261660ac848": "What are proactive equity assessments in the context of system design?", "9676f8ec-7e8e-461d-a77e-337c20095d6e": "Why is it important to use representative data in automated systems?", "07c06943-1c60-4690-a161-f2c3d04c88b7": "How can proxies for demographic features lead to algorithmic discrimination?", "f8088e52-e35c-4f3b-8479-e530e41e83c5": "What measures can be taken to ensure accessibility for people with disabilities in automated systems?", "d218c959-31ff-4b08-8feb-b6cd5b7f9808": "What is disparity testing and why is it important before deploying automated systems?", "fcda6d4e-26ec-4b88-b9e2-33410629db75": "How can organizations provide clear oversight of automated systems to prevent discrimination?", "358806ca-03c5-4219-8f5d-7d6bd50c4a51": "What is an algorithmic impact assessment and why is it necessary?", "95dfc992-0553-4499-94a7-d42021d7a805": "How can independent evaluation and plain language reporting help in mitigating algorithmic discrimination?", "3c860073-dead-456a-9dd9-746a0c1f2cc0": "What is ballot curing and how does it work?", "6e31af36-593c-4b4b-a439-f6361f629e60": "Which states have ballot curing procedures in place?", "bcac432d-f310-4e4c-8294-803789746673": "Are ballot curing procedures constitutionally required in all states?", "59c27c92-ad44-4eec-b9a6-c79134babf4b": "How do election officials contact voters for ballot curing?", "753f8d63-ebe4-412c-8c70-4b6defdfe6bf": "What kind of information might voters need to provide during the ballot curing process?", "838c69d0-ff96-462d-a5ec-c67efa2bcca9": "Can a voter cure their ballot if they missed the initial deadline?", "c7ec0382-b12d-4075-915b-a29a72506cfc": "How does the ballot curing process ensure the validity of a ballot?", "22887c27-fdf6-433a-9832-9a9115f9683a": "What are the common reasons a ballot might need curing?", "fdad09f6-1e41-4f9c-9715-fffb065295c1": "How long do voters typically have to cure their ballots?", "e1115d17-d43b-4b36-8792-e50c67b9bb8c": "Are there any states that do not allow ballot curing?", "ebd1eb6d-41f7-4335-b070-d78501a2156e": "What is algorithmic discrimination and how can it be avoided?", "64a7ca44-9bdd-4f2f-bdb1-baed69c8d781": "How do proxies contribute to algorithmic discrimination?", "20367a8b-c64a-4864-bc1b-3d280f351a0e": "Why is it important to test for correlation between demographic information and attributes in data?", "d9858772-aa90-4a5a-be0c-fc5b5b333bd8": "What steps should be taken if a proxy is identified in a system?", "57ce6697-9b12-431e-8391-82fdd25840ee": "How can organizations ensure that a proxy feature is not given undue weight in decision-making?", "39f694c3-4c98-4d86-b3e2-28fd601599af": "What are some examples of attributes that might serve as proxies for demographic features?", "14fb21ac-2111-40ac-bda5-782d92f9b5a6": "What legal implications can arise from using proxies in algorithmic decision-making?", "fb146223-b6a8-49be-bb4d-631246b9b613": "How can alternative attributes be identified if a proxy is found in a system?", "b11ec9e4-e31c-4b32-b7d2-e9801186fd91": "What are the best practices for monitoring systems to prevent algorithmic discrimination?", "8fd37fe4-2c42-4678-bce5-922ed9d2dae5": "Why is proactive testing crucial in the design, development, and use of systems to counter discrimination?", "4457a37e-6d0e-411d-aea4-b1c32f5a127d": "What are the limitations of AI in different contexts of use?", "a7e21fa9-a576-4c9c-b7b8-cf1dc782ba81": "How can structured human feedback improve AI systems?", "bdaa7693-aa11-46bb-a39b-d7e351b3fff2": "What are some anticipated human-AI configurations in the future?", "bc7e0482-14cb-4e29-83b9-d34e973bcfb4": "How can harmful bias and homogenization in AI be mitigated?", "06906bd2-d444-4b50-86fc-e7d4b6caa7be": "What measures can be taken to prevent AI from generating dangerous, violent, or hateful content?", "e7276fb9-5e30-4e77-a07f-98fae0b0a30c": "How can organizations identify and document illegal uses of AI systems?", "416fc8f9-4237-4877-a514-88013a360abd": "What are the risks associated with AI in handling CBRN (Chemical, Biological, Radiological, and Nuclear) information?", "35cbeeef-7459-4fe7-bb33-74fc872c987a": "How can interdisciplinary teams contribute to the development of AI systems?", "e5be6c98-b642-4a1b-968b-8d3d71eb0fd3": "What competencies and skills are necessary for AI actors to establish context reflecting demographic diversity?", "f6636c23-4d93-4bb1-abf3-5ef8d69586c7": "Why is interdisciplinary collaboration important in AI development?", "6e27bf91-4131-4e12-b6fa-cc6d5997f88f": "What are the long-term performance characteristics of General Artificial Intelligence (GAI) that remain unknown?", "ff520072-afb0-4b73-9f62-29ac419bf82d": "How can we ensure information integrity in the deployment of GAI systems?", "4e3cb88c-db89-46db-bfaf-6efc6c06e573": "What are the potential dangers of GAI generating violent or hateful content?", "1ba43e0c-45c7-42b2-9dcf-0edbb0e71b32": "How can a plan be devised to halt the development or deployment of a GAI system that poses unacceptable negative risks?", "82d470a2-1e99-4a76-92f8-281573661995": "What measures can be taken to prevent GAI systems from generating content that violates the law, such as CSAM or NCII?", "2e5d1e86-46b3-4528-b9e2-cbe1e372e99b": "What are the risks associated with GAI generating obscene, degrading, or abusive content?", "c53e6933-dd22-42ec-865b-0cfc8a4a6f10": "How can harmful bias and homogenization be mitigated in GAI systems?", "60fdcce3-24cf-46ff-bd37-71e20af72d5b": "What are the best practices for establishing transparent acceptable use policies for GAI?", "35c63a1b-39bb-4e6e-87d1-597fbe552fb0": "How can governance and oversight be effectively implemented for GAI systems?", "7e800537-d1f9-48cc-b514-dc45ba1e805f": "What are the key components of a risk management process for GAI that ensures transparency and aligns with organizational risk priorities?", "8caffdb8-0e56-4747-8e14-5076b635e19f": "What are the key roles and responsibilities for managing AI risks within an organization?", "7a804990-826f-4344-923d-164698caefdd": "How should an organization document and communicate AI incidents to stakeholders?", "1fefa53a-88bb-48ff-8f41-3aeae62bce74": "What procedures should be established for engaging teams in AI system incident response?", "b4eb2632-537c-4adb-8f56-5f7392106c81": "How can an organization ensure that AI Actors have the appropriate skills and training for incident response?", "3e0d09b6-f68d-4dc8-bef2-d2295751db89": "What are some official resources for reporting AI incidents?", "b9023848-3972-4a1d-9214-477117a0d3df": "How can harmful bias and homogenization be addressed in AI incident response procedures?", "8b69e61b-4fce-477c-8e17-3871ba07c8ca": "What is the importance of having clear lines of communication for AI risk management?", "3003c533-bec8-424a-a54a-5bbe26b84144": "How can organizations verify the skills and training of AI Actors involved in incident response?", "6e59a970-f171-4ff5-a512-b3d6396bb916": "What are the benefits of having diverse teams for AI system incident response?", "30812fe9-ef65-459a-9731-9e837e6be7cb": "How should organizations integrate value chain and component integration in AI risk management?", "8abc3501-531b-42b8-9cec-6ed049ec1079": "What are some appropriate responses to identified privacy risks in data processing?", "473df226-ad88-4f10-8241-ea6b0ab61506": "Why is it not appropriate to transfer privacy risks to users via notice or consent requests?", "a74c77b8-07cd-430c-8aac-7b1585bc505d": "What are privacy-preserving security best practices for automated systems?", "c4688abb-c2c2-46c4-86b1-0261e15da71b": "How can privacy-enhancing cryptography help in maintaining data privacy?", "003673d2-5ecb-440b-80be-5cd34bbaa356": "What role do fine-grained permissions and access control mechanisms play in privacy-preserving security?", "cb249eee-5357-4ed7-99fb-8da55348c57c": "Why is it important to ensure data and metadata do not leak beyond the consented use case?", "af4ab8cd-cae8-4e7c-922b-8e193f1f5383": "What are some examples of privacy-enhancing technologies?", "8fbca3b4-2fde-4348-a2e2-1dede9fbabb2": "How can entities balance privacy risks and benefits in data processing?", "39179d19-89d2-4969-a2e9-b1c27831cd8f": "What are conventional system security protocols that can be used alongside privacy-enhancing technologies?", "4e933b6b-f6f3-45a9-aa9d-c54fc2d80ade": "How can entities ensure users understand the privacy risks associated with data processing?", "7a230dee-19b1-4409-ac9b-4fd593416a92": "What are the main challenges for consumers with the rise of AI-enabled products and services?", "e0de42d1-9769-4cec-a48a-c883f8a5c316": "How can communities benefit from the growing ecosystem of IoT devices and smart city products?", "1bbc381a-2090-45be-8cad-d9d9d862608d": "What role does the Federal Trade Commission play in protecting consumer privacy in the context of advanced platforms and services?", "93fdcd7f-ecce-4c63-80b4-7e3b65a0ec49": "How can consumers ensure their rights are protected when using AI-enabled consumer products?", "e3a6aac7-0d0f-47f2-a09a-5a902286de83": "What are some potential risks associated with the use of smart city products and services?", "9343529d-ade3-4b58-8c53-8a84ae0b6620": "How can policymakers balance innovation with consumer protection in the digital age?", "1402d638-7b8d-4525-9c64-93611b63063a": "What strategies can be employed to enhance consumer trust in AI-enabled products and services?", "2b45e986-94f6-441b-a5b6-ad7d5710929e": "How do IoT devices impact consumer privacy and what measures can be taken to mitigate these impacts?", "60e72442-44d0-4e8e-8f79-1d3e0616d45d": "What are the opportunities for improving community well-being through the use of advanced digital platforms?", "5f17138e-15e8-4f1b-9538-d62720ee1357": "How can consumers stay informed about their rights and protections in the evolving digital landscape?", "5c5c28fe-f220-4cfb-b5dd-59fa4fc0ed70": "What is the NSF Program on Fairness in Artificial Intelligence in collaboration with Amazon?", "1ecd21e2-5962-46c3-8ac6-39f368d94cb0": "How does automatic signature verification software threaten to disenfranchise US voters?", "9a291c46-0178-49d0-a45a-eb38560f5715": "What is the cure period for absentee and mail-in ballots according to Ballotpedia?", "df46e7f9-256e-4668-a774-41a48f74c576": "How can you tell if two mail ballot signatures are by the same person, as discussed by the New York Times?", "3bac4694-ad52-44b3-a9b8-bdd45f2f3526": "What are the main points discussed in the article \"The Low Down on Ballot Curing\" by Rachel Orey and Owen Bacskai?", "caf5e917-228f-452a-aa7e-5e4722643f18": "What are the potential issues with automatic signature verification software in the context of voting?", "d769a613-d040-42c5-b109-da27d5f9787e": "How does the National Science Foundation's program on AI fairness aim to address biases?", "2f8b1ef4-df6f-4ba6-9615-e1a85909f4af": "What are the steps involved in the ballot curing process?", "ace15994-5883-41c6-a269-9979b4205fbd": "Why is the cure period for absentee and mail-in ballots important for election integrity?", "e1eb277b-b995-4e63-a1eb-9180ffd6f139": "What examples of signature matching challenges are highlighted by Larry Buchanan and Alicia Parlapiano in the New York Times?", "076a1fc1-5b6b-46f0-b2b6-48cfac0d15e7": "What is the importance of sharing pre-deployment testing results with relevant GAI actors?", "64993f9a-4b76-4a8f-874c-3d273367f43f": "Who are considered relevant GAI actors in the context of system release approval?", "153b18fe-97ea-4516-a51c-8aee0b2f8f07": "How does pre-deployment testing contribute to information security?", "99dc15b6-9a6f-46c8-ac5b-2de91142fa28": "What are the key components of human-AI configuration in information security?", "ee485024-fbdf-4772-9401-42eb2a5b5603": "What steps are involved in the pre-deployment testing process for AI systems?", "94cb95a8-ec57-470d-b1e8-3959d8963369": "How can sharing pre-deployment testing results improve system release decisions?", "af4cbd1c-b744-4bab-97a4-ec1f323b9260": "What are the potential risks of not sharing pre-deployment testing results with relevant actors?", "0325a366-a9b0-45a5-87cf-7107248c17f6": "How does confabulation relate to information security in AI systems?", "a2a6f02b-4f15-4743-a2b5-3f2025414a01": "What role does system release approval authority play in the deployment of AI systems?", "835ee7d9-eea0-48db-a932-b70328a2b80f": "How can human-AI configuration impact the effectiveness of information security measures?", "2184e32c-4f19-4057-964f-48f6090c4d64": "What are the health benefits of traffic calming measures according to the US Department of Transportation?", "426c71f4-c8da-4c45-b83c-0cb9d64407ac": "How do traffic calming measures help in slowing vehicle speeds?", "4f9726e7-c892-47d5-941c-423f9a84d608": "What are some examples of traffic calming measures mentioned by the US Department of Transportation?", "89c9ee09-99a0-44e8-9140-622366b15748": "How can organizations monitor and fix their AI models using responsible AI ventures?", "02099e7a-c0f9-4fec-8ac9-5f7fe1eab08c": "What are some startups that focus on AI ethics according to Karen Hao?", "38cff01a-3e4d-4f0d-84b0-6e9383d80e02": "What is the role of responsible AI ventures in promoting ethical AI practices?", "2c7799cd-0027-4338-a539-47cd43e086c6": "Can you provide a summary of the article \"Worried about your firm\u2019s AI ethics? These startups are here to help\" by Karen Hao?", "dc59187d-f64f-4de6-af9d-5e6e93133b18": "What are some top progressive companies building ethical AI in 2021 according to Disha Sinha?", "6f52455b-2a16-4f6c-94cb-d9ba727691af": "How does the growing ecosystem of responsible AI ventures impact the development of AI ethics?", "16af67cc-0dfc-4203-815d-8b6bf5ef6277": "What are the key points discussed in the MIT Technology Review article on AI ethics startups?", "555d774d-d331-4349-951f-af19f683089a": "What are the main privacy risks associated with AI as discussed by Lee, H et al (2024)?", "91ef15f4-5185-4c16-9ef0-4bbb37697969": "How does data poisoning exploit generative AI according to Lenaerts-Bergmans, B (2024)?", "1c1560c2-164b-4de3-9972-65d5c636bd55": "Why are GPT detectors biased against non-native English writers as per Liang, W et al (2023)?", "b0939336-ece6-40eb-82f5-1ec5f0e3b997": "What are the energy costs associated with AI deployment discussed by Luccioni, A et al (2023)?", "e8beb28b-df88-4857-a896-9492bc49fe69": "What operational risks does AI pose in large-scale biological attacks according to Mouton, C et al (2024)?", "d799c0a7-a358-47d3-8fc2-0b8da05d95fa": "How does generative AI exhibit worse biases compared to humans as stated by Nicoletti, L et al (2023)?", "4f6a16c0-eb08-4d81-9e2d-968a9c7bbe5a": "What are the key findings of the National Institute of Standards and Technology (2024) on adversarial machine learning?", "8029f69a-cddb-4697-8f5f-a117433fee74": "How can deepfakes impact privacy according to the taxonomy provided by Lee, H et al (2024)?", "66f00bc6-ab1d-43e9-9153-e2c75516e556": "What measures can be taken to mitigate data poisoning in generative AI as suggested by Lenaerts-Bergmans, B (2024)?", "5d336249-8464-410f-8952-8b2a4b802ba1": "What are the implications of biased GPT detectors for non-native English writers as discussed by Liang, W et al (2023)?", "cca47a77-0520-490a-ba33-7fc205506cff": "What are tenant screening algorithms and how do they impact housing applications?", "193d2e40-1043-47cd-a7ed-4c589f9ed491": "How do automated valuation systems work in mortgage underwriting?", "1377b78c-14b8-431e-bbcf-a61ca726482b": "What role do workplace algorithms play in determining employee pay and promotions?", "b20bfb27-3464-4d36-af79-19e0efb7136b": "How are virtual or augmented reality programs used in workplace training?", "b63ce3cf-4572-4655-8f8c-f0590a07b1dd": "What are the implications of electronic workplace surveillance on employee privacy?", "518edd21-747b-416c-a5e4-eded44945fd5": "How do AI-assisted diagnostic tools support clinical decision making in healthcare?", "f29882f4-75bf-4ba7-8c1a-4908f184296a": "What are the benefits and risks of using medical AI systems and devices?", "0477b1d1-9503-4a65-9872-d4e96a8ba1b1": "How do predictive models in healthcare influence patient treatment plans?", "cb0e5e06-fc4b-4849-a9f5-cc5a5541d9c4": "What are the ethical concerns surrounding the use of algorithms in employment decisions?", "675faee1-4b6f-46f9-9004-bfea75569eee": "How do automated valuations from online aggregator websites affect home insurance rates?", "e3b5b92f-9f7b-4c54-9240-dfaff35e382f": "What information is required to build or validate a risk assessment?", "50ddae98-3e18-4f13-87df-bdf5c87c3e49": "How can the public access information used in risk assessments?", "857942ee-2e35-4394-93cc-4a1070f88dbf": "Are trade secrets protected in criminal cases?", "039a84a0-ad22-41a4-9569-a900c59cd915": "Can trade secrets be used to prevent discovery in criminal matters?", "730583a5-c594-465e-b9db-d94372af5b92": "What are the legal implications of using trade secrets in criminal cases?", "a399efb4-2fe3-4b7d-bb74-468cb88c6692": "How does public inspection of risk assessment information impact transparency?", "25b7a363-4a6f-4e92-bf19-820353d20eda": "What constitutes a trade secret in the context of criminal law?", "e89b7e4e-9d0c-49e9-ba4b-d96fb7f38d1d": "How does the law balance trade secrets and public interest in criminal cases?", "43939503-05a7-4f81-a001-b61fae0e6cf3": "What are the consequences of failing to disclose information in a risk assessment?", "741c8a8a-a15d-4b18-b19a-a167119ce939": "How can parties in a criminal case challenge the use of trade secrets to quash discovery?", "ce483416-c348-4911-9628-813050e4eeab": "What are the best practices for limiting the scope of data collection to avoid mission creep?", "2ca2c34f-c0e3-4a49-bb51-b639dcabcfe2": "How can organizations determine if data collection is strictly necessary for their identified goals?", "361b48b8-e93c-4e16-91a5-cc5e07f1fe3d": "What steps should be taken to minimize data collection as much as possible?", "ac634aac-bdc9-4b09-83c7-537d7fab01bb": "How should organizations assess new privacy risks when using data in a different context?", "7f844336-cb98-4ae3-b02c-d29460977665": "What are appropriate mitigation measures for new privacy risks, and when is express consent required?", "09a89a5d-baf9-44e7-97ce-9150f52dcddb": "How can clear timelines for data retention be established and enforced?", "145c8074-9a0f-4eeb-a364-f358745607c7": "What are the legal or policy-based limitations that affect data retention timelines?", "9f2b34d5-6f6f-477a-95d2-34caa90de98d": "How should data retention timelines be documented and justified?", "1e82f71e-654d-42ec-9c14-6dadbe1f6a21": "What methods can entities use to proactively identify potential harms related to sensitive data?", "99c21c13-0f1b-4e41-ba73-66b99a72b9f5": "What strategies can be employed to manage and mitigate risks associated with the collection, use, sharing, or storage of sensitive data?", "3be3f630-af00-421e-9293-5b36b1457f21": "What are the AI RMF functions and their corresponding tags?", "15856cf5-933b-4a51-9b87-1a41b7989c41": "How should organizations determine the applicability of suggested actions to relevant AI actors?", "f8eeb340-f824-4954-8bba-97e13a1eaaa4": "What does the Action ID GV-11-001 represent?", "41e2ede8-bed6-4392-91c8-4d6e11fd5723": "Are suggested actions for GAI developers always relevant to GAI deployers?", "8d49c1c5-f878-4154-9587-d0639e096bfe": "What information is included in each table of suggested actions?", "256b9f00-7e6f-424f-a18c-4c07a21a9c0a": "How are GAI risks linked to suggested actions?", "2fefdcdf-4aed-4bf3-a395-cca2e7e6f51f": "What does the tag \"MP\" stand for in the AI RMF functions?", "5073c0c1-051a-4a7f-8466-425db5f7c409": "How can organizations manage GAI risks according to the suggested actions?", "6a8808c6-ab61-4357-826e-0a9c216b874d": "What are AI Actor Tasks, and how are they related to subcategories?", "ac5de47b-969a-4190-8637-c26262014360": "Why might not every AI Actor Task be listed for each subcategory?", "2d85a293-4a92-4d77-a148-01e6bdb2e171": "What are the best practices for identifying and documenting how a system relies on upstream data sources?", "fa278b40-585c-4815-898c-0b82776e868b": "How can one ensure the integrity of information when a system serves as an upstream dependency for other systems?", "d2d872e7-55fe-471f-8a3c-444fd24feaeb": "What methods can be used to observe and analyze the interaction of a GAI system with external networks?", "ce2f6805-1d0b-408b-93cb-df89733e20d7": "How can potential negative externalities be identified when analyzing a GAI system's interaction with external networks?", "f0e5e018-68e2-4930-9f82-18a05118dd73": "What are the key considerations for ensuring scientific integrity in experimental design and data collection for GAI systems?", "aaf22726-5e88-48f2-9816-290e976a2c52": "How can the accuracy and reliability of GAI output be assessed effectively?", "621c3d3b-6588-4b26-817f-34cf97d21faf": "What strategies can be employed to validate the authenticity of GAI output?", "d4ebcdf7-e442-4f4e-ae79-bc5b7049698f": "How important is content provenance in maintaining the integrity of information in GAI systems?", "1ed4e09e-46b0-42fb-8f66-ad56d901feb1": "What are the risks associated with the integration of value chains and components in GAI systems?", "4ee25323-db4d-4006-941f-65f9ef0a30a2": "How can one document the trustworthiness and construct validation of a GAI system?", "c87b4890-2e5b-4bac-9ab2-38345179a167": "What are the current consumer data privacy protection regimes in the United States?", "a5cec61b-fe2c-4f0a-b43c-0bcfda0a4e61": "Why does the United States lack a comprehensive statutory or regulatory framework for personal data rights?", "cd837571-a21f-4d34-be84-a254ecaabd8e": "How do existing laws guide the collection and use of personal data in specific contexts like health and employment?", "bf81addc-77e6-4962-a28d-6a88b104c798": "What are the potential harms of not having a standardized data privacy protection regime in the US?", "0a2781a2-70af-4a14-833a-be0db30d26de": "How do state-level consumer data privacy laws differ from one another?", "70ebdeb5-d993-421c-98de-6f8c8a151dcc": "What additional protections could assure the American public about the use of automated systems?", "c3a7e646-03e3-4fcb-a49d-f6aeb95cd652": "How does the patchwork of laws affect the application of data privacy in an automated society?", "b2069dc4-e694-456f-ac4e-bc92042d8f57": "What are the challenges in applying existing data privacy laws to new technological contexts?", "eaf0aa98-7660-4a3d-9f6e-c63c68dafdbc": "How can consumers ensure their personal data is not being monitored or collected without consent?", "d8553bac-b1a1-4c02-9567-b5f42bb59bee": "What legal authority is required for automated systems to collect personal data in the US?", "6a84a0e6-451d-4969-8be6-245780aeb397": "What is prompt injection in the context of GAI systems?", "7b29eb41-5e52-429f-af23-ae265e916f3f": "How do direct prompt injections differ from indirect prompt injections?", "f9c5155b-5175-472a-bbc4-0b5013dfe6b9": "What are some potential consequences of direct prompt injection attacks on GAI systems?", "8318048b-c34f-44ee-a2ba-511717b16077": "How can indirect prompt injections exploit LLM-integrated applications?", "0eb2f6c5-07ed-4df1-b0ee-9772ba08a943": "What are some examples of vulnerabilities that can be exploited through indirect prompt injections?", "1d52cdc1-e84a-4d67-80f9-7540a2133c4c": "How can querying a closed production model reveal previously undisclosed information?", "7b697db4-b43e-445e-bdaf-c9ceb08eb05e": "What measures can be taken to protect GAI systems from prompt injection attacks?", "41daecd9-dceb-4f72-a42a-e18ea7fda937": "How do conventional cybersecurity practices need to evolve to address prompt injection threats?", "fd25cb30-3e1b-4f40-bd7a-02df040ec85c": "What are the risks associated with malicious prompts in GAI systems?", "c5b9acfc-ac53-4dbd-85d3-f28fa4f32c26": "How can security researchers demonstrate the impact of indirect prompt injections on proprietary data?", "6d74ac43-d15a-4127-8db7-cef0fdb9d105": "What is the importance of using representative data in system design?", "c71c8dd4-63a7-4818-b770-97043dc5007e": "How can organizations protect against proxies for demographic features in their systems?", "2d5bfd5e-dbdc-4c0c-818e-615f91006738": "What are some best practices for ensuring accessibility for people with disabilities in design and development?", "0029c940-ec04-411f-a02c-3d2ed811162a": "Why is pre-deployment disparity testing crucial in system development?", "a07d446c-3b58-4fde-86ea-42a39458f472": "How can ongoing disparity testing and mitigation improve system fairness?", "c3e83063-2c07-421c-8e37-a16fff3f39e8": "What role does clear organizational oversight play in maintaining system integrity?", "606bee4d-8e16-4cd6-a403-2f19c040f21c": "What is an algorithmic impact assessment and why is it important?", "553267de-5d7a-4b26-91a6-2066782e1eca": "How can independent evaluation contribute to the transparency of algorithmic systems?", "2663ee64-79f0-4c1f-8410-651d596a09cb": "What should be included in plain language reporting of algorithmic impact assessments?", "dddf4214-014b-4cae-a517-b49cd94d6dbb": "Why is it important to make disparity testing results and mitigation information public?", "791a3b0f-42da-4f1e-8230-e984b9e83a5d": "What are some examples of automated systems that can impact civil rights and civil liberties?", "2e9b844a-3516-48c7-9857-37ddb2b13880": "How do automated content moderation tools affect free speech?", "41172f4c-70e5-4cec-9baa-a1647ae750e3": "What role do predictive policing algorithms play in the criminal justice system?", "e28c299b-5a05-4d08-b18b-a133fd152cee": "How can automated license plate readers impact privacy?", "89e46e02-8e3a-48fb-aee7-332e3cb87322": "What are the potential risks of using real-time facial recognition systems?", "d4f21fa8-9d60-4e63-b735-56afa6012b7e": "Why should the Blueprint for an AI Bill of Rights cover automated systems that do not yet exist?", "6605c4f9-86eb-48ba-970b-2ec5cbda43d5": "How do surveillance algorithms affect civil liberties?", "ed41893b-1bb9-4e32-bf94-8499f5845e84": "What is the significance of including speech-related systems in the AI Bill of Rights?", "06f4e666-7e80-47d4-920c-020d8e66d063": "How can risk assessment algorithms in the criminal justice system impact individual rights?", "d8fdf8f4-8a77-4d9d-9d04-353cf7713d24": "What are the implications of using automated systems for surveillance in terms of privacy?", "94bdbb5b-6d65-480b-8601-b46cc88fc568": "What are the potential harms of AI systems in terms of political opinions, sex life, or criminal convictions?", "455d3295-e1b6-4838-9757-ee00fbf6fc3f": "How can disparities between groups lead to harm when using AI models?", "dcad9f20-5d3c-4fa0-a3da-0807a6e8e29c": "What challenges arise in establishing a baseline scenario to measure harm caused by AI?", "a9fffb40-a9a9-44a4-8bd7-139528a1ab89": "How can biased behavior in AI systems result in harm to different subgroups?", "d0babf07-9aad-4ae7-a6cd-85ecdcba8291": "What constitutes an unambiguous harm caused by an AI system?", "89597661-548a-4a06-a978-89132aba1eb0": "How can we determine if an AI system has worsened someone's situation compared to the absence of the system?", "f9670d38-896e-4fbc-8f5b-b9d0037c76ff": "What are some examples of harm caused by disparities in AI behavior?", "a0b6a03d-c670-468c-bce1-9294b6d93b53": "How do divergent views on disparities in AI behavior affect the assessment of harm?", "86dbbc9d-37e8-4fa1-87dc-808e4eb2b54e": "What mechanisms can be used to identify harm caused by AI systems?", "001c0aca-6ef2-4987-9528-4e438dccb697": "How can we address the issue of biased behavior in AI to prevent harm to subgroups?", "ff4430a8-31f2-4f0d-a6e0-5c8649634b27": "What are some effective strategies for disparity mitigation in automated systems?", "e535b78c-e479-4e22-9856-3ae2f3a944b8": "How can we identify and evaluate multiple models to select the one with the least adverse impact?", "07577988-b22e-464d-a114-5a3836a9b93e": "What steps should be taken if adequate mitigation of disparity is not possible in an automated system?", "dbb54f3d-f426-42fa-85ac-fdf51750e91c": "How do unobservable targets lead to the inappropriate use of proxies in automated systems?", "7fdfe1a9-36d4-4691-885b-a3946764874a": "What legal requirements exist for mitigating or eliminating disparities in automated systems?", "7cae1803-9318-4bf5-a8b5-7013514edc4f": "How can modifying data input choices help in reducing disparities in automated systems?", "692e4a6c-a9d5-46ca-a0d6-9a31d7f06f67": "What are the potential consequences of algorithmic discrimination in automated systems?", "9601cee0-678d-42b5-a2a6-8db03a41e877": "How can we ensure that an automated system aligns with equity goals?", "087c8f2b-0171-4cb4-81de-f085a3a439ca": "What are the best practices for conducting a disparity assessment in automated systems?", "9ed4da28-5f9b-4191-8f88-b3d3f17c019c": "How can meaningful harm caused by disparities in automated systems be identified and addressed?", "1a5f3970-e2ad-4c5a-b2f2-464b42ba6670": "What are the common sources of bias in GAI training and TEVV data?", "1f4eaffe-4d1e-4e65-927f-b30861a0c252": "How do differences in outcome distributions across groups affect GAI systems?", "7108defb-707d-4f17-be57-997ab61d8de5": "What is the impact of the digital divide on the representativeness of GAI training data?", "dbfa0169-4237-4e27-a0a2-6f6add38775e": "How can latent systemic bias in images and text be identified in GAI systems?", "786162d0-4467-47da-a17d-83e793b39e99": "What role does demographic group coverage play in the effectiveness of GAI training data?", "2dccbfb2-4d4e-4e46-bb34-553b404afd69": "How can input data features act as proxies for demographic group membership in GAI systems?", "2026e84e-f0b0-41f3-a034-e2ee060d5e42": "What methods are used to filter hate speech in GAI system training data?", "af8f1310-f89e-41d6-a386-57d253594be4": "How prevalent is GAI-generated data in GAI system training datasets?", "cc1890d2-8f2e-48d0-abcb-8f49bfb2f5b2": "What are Winogender Schemas and how are they used to study gender bias in GAI systems?", "2ee7b790-cd75-4629-a52f-8036fad31546": "How can the completeness and balance of data sources be measured in GAI training data?", "53c25f8b-f67e-480c-ab2a-951cfbd311df": "What are the technical risks associated with advanced AI models?", "8be2ee75-d646-4383-b30c-966d720b0fa8": "How can AI confabulation pose a risk to safety?", "f18be8d3-47f5-4006-83fa-afb8ce01872b": "What are the dangers of AI making violent recommendations?", "4a8b4330-7921-4bb8-becf-4ea1bb6b54e3": "How does data privacy become a risk in the context of advanced AI?", "ce71108e-36bc-49d1-a29d-19023f609a26": "What is meant by value chain and component integration in AI risk management?", "4a77b200-1ee4-4bbb-b131-970c384060be": "How can harmful bias in AI systems be mitigated?", "3aa2d071-ce40-40d5-be9e-8219f64dbef9": "What are the potential risks of AI misuse by humans?", "73bb4bbd-de45-44ae-9b2f-d51c7dc9c39c": "How can AI be misused to spread obscene or abusive content?", "e5a3d5df-7333-4465-9aef-c982135b06e1": "What are the systemic risks of AI to the ecosystem and society?", "92a08a8e-413f-431b-92b3-ab96effc5cfb": "How does AI impact intellectual property rights?", "4e3b03a7-bfc2-43b1-b05b-f1a0c38eff6c": "What is algorithmic discrimination?", "70f62e50-5170-4ad9-928d-15660d1f86b5": "How can we protect against algorithmic discrimination?", "674c4e49-a7d5-47f2-bc90-df8320d389ce": "What are some examples of algorithmic discrimination?", "c61b9e7b-0fb9-4e82-a7c4-64d87b67c0b2": "How do algorithms lead to discrimination?", "2e142a47-da67-4d69-b1f4-c340f690597a": "What laws exist to prevent algorithmic discrimination?", "4e2fb6ff-c26c-4485-adb5-69581eb0a253": "How can companies ensure their algorithms are not discriminatory?", "114af13c-f1ec-49c5-a9a2-f604e098e204": "What are the ethical implications of algorithmic discrimination?", "454c3073-ee6a-49e6-b85d-712601950be6": "How can algorithmic discrimination be detected?", "890c20df-f21b-467f-9126-136a56509c15": "What role does transparency play in preventing algorithmic discrimination?", "ff14594e-b5c4-4958-99b5-c3c354b9f502": "How can individuals protect themselves from algorithmic discrimination?", "4b585781-3f5c-4022-b77a-4d5874711f71": "What is the significance of the watch list that Chicago police fought to keep secret, as reported by Mick Dumke and Frank Main?", "c3bfc377-21d8-4ea9-aa9d-28bf11fa7174": "How does the ACLU case in Idaho highlight the pitfalls of artificial intelligence decision-making, according to Jay Stanley?", "04ce1a4c-76ce-4640-9775-83d32fb8e781": "What are the key provisions of the Illinois Biometric Information Privacy Act that became effective on October 3, 2008?", "ee94abbb-0f06-48b9-944e-c9be35cad15f": "What is the ABOUT ML Reference Document by the Partnership on AI, and what does it cover?", "d9f37ef0-5071-4f8e-9872-db98336653a5": "How does the model cards framework contribute to transparency in machine learning models, as discussed by Margaret Mitchell and her colleagues?", "66ebcef0-85e0-4e6d-afc7-bdd573d73837": "What were the main findings of the Chicago Sun Times article on the police watch list by Mick Dumke and Frank Main?", "508213e7-c376-4ead-bb89-162fc3fef0e7": "How does the ACLU blog post by Jay Stanley address privacy and technology concerns related to AI decision-making?", "67c9bee6-f621-4966-ba5b-b12a16c01f45": "What are the implications of the Illinois Biometric Information Privacy Act for businesses and individuals in Illinois?", "061e1226-744d-4d65-8114-0fbadd9b3d06": "What is the purpose of the ABOUT ML Reference Document, and how can it be accessed?", "af11a645-0690-4cf6-929f-476f6853ee58": "Who are the contributors to the model cards framework, and what are their roles in the development of this framework?", "d7605540-f9a3-4e51-9036-60f1c4df408b": "What is the Biometric Information Privacy Act in Illinois?", "379f0256-6648-4343-82bd-85d0ba551fe2": "How does the Biometric Information Privacy Act protect individual biometric data?", "097159ce-edec-42b3-8e7d-f7eaa02730ca": "What are the provisions of the Biometric Information Privacy Act regarding the use of biometric information?", "80dcda41-28de-4d4b-a5f6-d968bf53fca2": "How are people in Illinois notified about the use of their biometric information?", "ada88ac3-f4cc-4c8c-9572-1eef6b100f8c": "What are some real-life examples of laws protecting biometric information?", "a9cc0b3d-ed88-41d5-9b61-453f88b305d5": "How can technical and sociotechnical approaches protect rights and access to biometric data?", "465a72fd-3256-436b-8e18-d0a099b3fc3a": "What are major technology companies doing to communicate with the public about biometric data use?", "8ffdf82f-7776-4d09-8d87-dd3b9b2d6dce": "What are the requirements for private entities to collect biometric information in Illinois?", "81883056-15e0-4dac-a219-beb17eae9f58": "How do policies help in protecting biometric information?", "30810cb5-f31d-468a-b938-a53597ae1d54": "What practical approaches can be taken to ensure the protection of biometric data?", "e7dc392f-0994-4434-83ca-5a2b95bfb984": "How have chat-bots and AI-driven call response systems improved customer service?", "d17c2c7a-b481-4a0a-8c1f-ecce10c054d1": "What are the benefits of using partially automated customer service platforms?", "1fd47749-e6b5-4a4e-9982-0d7a4096be47": "How do integrated human-AI systems enhance the speed of customer care?", "886cbf14-7c71-4800-97a2-a3f8f91c9aef": "Why is it important to maintain human agents in customer service despite the use of AI?", "c68e9ed0-dbc2-47cb-8531-79bafa03558c": "What role do human agents play in resolving complicated customer service requests?", "009e2017-2f03-4ae5-80e7-1e266e24c0c1": "How do businesses compile common customer problems for human agents to review?", "7e569e34-0129-4adc-9ffa-13874c019581": "What are ballot curing laws and how do they function in the context of voter signature matching algorithms?", "97e257bf-87aa-4bbd-a07a-8ebb0d758152": "How many states have ballot curing laws that require a fallback system for voters?", "78b69abb-f1c6-4398-9e4e-619d89054b29": "What happens if a voter signature matching algorithm incorrectly flags a ballot as invalid?", "9ede1912-c15f-41cf-83b6-4ac0a0be6c0f": "Why is it necessary to have a review by an election official in the ballot curing process?", "1c3e63ce-81d0-49de-920c-d4c81fd0d223": "What can I do if a former employer provides false information about my job title?", "729f05ea-87c5-43a9-8190-306ccc177546": "How can false data from a previous employer affect my future job prospects?", "99785c94-c276-4ed1-8039-13f1d0943fdd": "What are my rights if a company supplies incorrect information about my employment history?", "0c4d45a4-e1e2-46e5-b8cd-59ac132cfb62": "Can a job offer be revoked based on false information from a previous employer?", "fd23ff35-ce12-4ab5-8f00-6522d5466c82": "How can I dispute false information provided by a former employer to potential employers?", "68940d08-efcc-42d0-96b0-7e26d8c550cc": "What steps should I take if I find out a former employer gave false data to a bank or landlord?", "b8ac00ac-57f4-4259-aead-6d6f608ccea9": "How can false employment data impact my ability to rent an apartment?", "fe589612-ce8a-4fec-bfb6-4a9173dff0a2": "What legal actions can I take if a former employer provides false information about me?", "ae7f2e11-db6c-470f-9093-9964aba79b39": "How can I prove that a former employer supplied false data about my job title?", "9ccf00e2-cd6a-4824-8e75-cb8c6bc51c37": "What are the consequences for a company that provides false employment information?", "d7947ff9-c5a1-430f-a50d-48369fe5d238": "What is the National Science Foundation's program on Fairness in Artificial Intelligence?", "da12cd0e-8846-4a5c-84a5-84fc2b21b168": "How does the National Science Foundation support research in explainable AI?", "aad8a5bb-bb98-4c8c-942a-60d55b2f3a3a": "What are the goals of the National Science Foundation\u2019s program on Fairness in Artificial Intelligence?", "62e9df72-50c1-414a-85e4-ec1b02cc7b3a": "Why is explainable AI important in the context of fairness in artificial intelligence?", "e688d828-a12e-4b21-a574-d41223a895e4": "What kind of research foundations are being developed for explainable AI?", "d9a5744c-7e1e-4f1c-bfe4-9ccafe96cd82": "How does the National Science Foundation define fairness in artificial intelligence?", "bc9af756-894b-4f0e-936f-fc6f94db6b7b": "What are some examples of projects funded by the National Science Foundation\u2019s program on Fairness in Artificial Intelligence?", "c24ff655-ee05-4769-96a1-1598937bb5d5": "How can explainable AI contribute to the development of fair AI systems?", "6c682518-b844-4763-a6a6-0c784122c7e9": "What challenges are associated with creating explainable AI?", "02b62987-5164-4ddb-b1ea-ea1c5ae2bfa2": "How does the National Science Foundation\u2019s program on Fairness in Artificial Intelligence impact the development of AI technologies?", "9d1e0807-b733-47c7-aab7-6db6d469a140": "What are the legal limitations on reusing sensitive data in domains like finance, employment, and housing?", "11e017f1-450d-484e-80d0-fd445c1441ff": "How can extra oversight ensure the safety and efficacy of sensitive data reuse?", "09d9a596-3e41-43ef-83c1-590975022445": "What are the benefits and risks of reusing criminal data for civil legal matters?", "1845dce6-8092-4224-b27c-4416e17dad7c": "What measures can be implemented to mitigate the risks associated with sensitive data reuse?", "aa8a4f38-7a8e-4236-a7d0-6066bfef485e": "How should sensitive data be labeled to identify contexts for limited reuse?", "31b0b161-5d09-4e06-8df0-3cd3719087e0": "In what ways can aggregated datasets replace individual-level sensitive data?", "eba60a78-3558-4289-b6c4-c260c5ddd08d": "What are the requirements for demonstrating the safety and effectiveness of automated systems?", "3e075c52-14a9-4ce8-a841-7081ebf2773f": "How can automated systems be designed to allow for independent evaluation?", "76205606-28f9-4aa8-b954-f88b34b55c55": "What are the potential benefits of private sector use of sensitive domain data?", "da56e9b1-2461-4b61-9841-d2518ab0182c": "What are the criteria for legally authorizing the reuse of sensitive data in other contexts?", "9c269a12-6410-4ffb-b5cc-7e74a8f47bd2": "What are the National Artificial Intelligence Research Institutes funded by the National Science Foundation?", "b2d39dd5-4224-4f84-9380-d8ed71a03606": "How can I apply for funding opportunities in Cyber-Physical Systems through the NSF?", "607bb0c5-d732-4661-89d2-8c8968dc8954": "What is the Secure and Trustworthy Cyberspace (SaTC) program by the NSF?", "137febbc-d1a5-48ce-ae7b-8fbe207161b9": "What are the objectives of the Formal Methods in the Field (FMiTF) program by the NSF?", "0dad671a-1be1-4246-86ac-e3a70cf4fa38": "How does the NSF's Designing Accountable Software Systems (DASS) program work?", "5e1f7127-82d6-481e-b40c-00469b2a02f1": "Where can I find more information about the National Artificial Intelligence Research Institutes?", "ff09d5ba-b0ce-431f-a9e6-6443aef1d947": "What types of projects are eligible for funding under the Cyber-Physical Systems program by the NSF?", "ab935b74-ec3e-4c32-9554-a212ec3eac3e": "What are the key focus areas of the Secure and Trustworthy Cyberspace initiative by the NSF?", "77e27420-8614-491c-870b-1f18f4bc11ea": "How does the Formal Methods in the Field program contribute to advancements in technology?", "5c9a5427-5b74-4e51-97bf-ff3fe62e0773": "What are the requirements for submitting a proposal to the Designing Accountable Software Systems program by the NSF?", "ff62ad50-d65f-41bd-aee2-94ee02783edd": "What are the potential risks of automating HR functions like performance evaluations?", "fae2091d-78df-4aeb-84f0-c4796d91062a": "How can errors in automated medical systems impact patient care?", "1174d0d9-9f4e-48c8-b445-47e1b63e081e": "What steps can be taken to ensure automated systems in healthcare do not deny necessary treatments?", "a7594475-953f-4c1b-ba9b-7e06027df340": "How do automated HR systems handle employee appeals or disputes?", "38758d4b-c5d6-4e3f-a96c-ca37a83ffa88": "What are the ethical considerations of using automated systems to make employment decisions?", "8ff16b60-4549-4d28-a5f8-d09dc421e48d": "How can companies ensure fairness when using automated systems for performance evaluations?", "1e5dacbd-129e-4493-b540-f6526c84911f": "What are some examples of automated systems causing harm in the workplace?", "23c3efca-d4e8-49c3-b686-8b432530b4f6": "How can employees protect themselves from errors in automated HR systems?", "70b624ad-4e3d-49ea-b622-028680721234": "What role should human oversight play in automated decision-making systems?", "53b65fc2-c35d-42d3-bd12-9411f43f20fe": "How can organizations balance efficiency and fairness when implementing automated systems?", "79527f3f-64a1-47c2-8080-526e87d6de07": "What are some novel methods for measuring GAI-related risks in content provenance?", "6ecf170a-bccc-40bf-a94b-cdee16acc4b6": "How can we evaluate the effectiveness of technologies in detecting offensive cyber activities?", "2a759b35-2e4f-4be9-b7cd-da0671a48a2f": "What are the challenges in maintaining information integrity while assessing GAI-related risks?", "05a5cf4b-6f21-4f0d-a726-782a1b5f0055": "How do current technologies measure the risks associated with CBRN information or capabilities?", "7464ee39-be9e-4591-9805-942ced6f3320": "What strategies can be employed to ensure AI models produce factually accurate outputs?", "623fdaff-f939-45e1-b135-53865f42ef09": "How can harmful bias and homogenization be mitigated in AI configurations?", "cec41fa7-ba2b-4f27-b233-a38c64d2be39": "What are the implications of AI-generated obscene, degrading, and/or abusive content?", "4e306b7e-b18d-408a-a7ff-ff6ef4bb5ef0": "How can we balance the need for reliable AI outputs with the prevention of harmful content?", "861cc15d-b987-4ae4-8da8-87774f1fd4a2": "What role do representative AI actors play in managing GAI-related risks?", "9e1b0b50-9c70-4f88-b9e9-1bce21f959c9": "How can we improve the reliability of AI models in the context of offensive cyber threats?", "312e6911-48ad-414d-b366-80e0cca7c405": "What are the risks associated with increased attack surfaces for targeted cyberattacks on AI systems?", "822e0d55-b6d6-4fd6-b0aa-970bda988794": "How can the availability, confidentiality, or integrity of training data be compromised in cyberattacks?", "b39af8a9-fdbb-4957-b79a-1ff8ff6bebfd": "What are the potential intellectual property issues related to the replication of copyrighted or trademarked content using AI?", "789e4c72-791b-4dea-8f9f-92ecbfb598d6": "How does AI ease the exposure of trade secrets and what are the implications?", "f4b466db-87c7-4ab8-8d5b-cf86ef2d84e5": "What are the dangers of AI in producing obscene, degrading, and/or abusive content?", "e5767722-faaf-40d4-a45c-7a1913c24ca6": "How can synthetic child sexual abuse material (CSAM) be generated using AI, and what are the risks?", "e81ed8e0-0b64-4bec-b518-b4f8140f20b6": "What are nonconsensual intimate images (NCII) and how can AI contribute to their creation and distribution?", "583946a4-f8da-4e37-9457-b91e6a6ee12b": "What challenges arise from the non-transparent integration of third-party components in AI systems?", "63097304-7442-4cef-88eb-325c2ccf4638": "How can improperly obtained data affect the integrity of AI systems?", "e17ed95d-b504-4234-b183-12b62f58b109": "What are the risks associated with improper supplier vetting in the AI value chain?", "3f995ade-9508-4868-9f0c-834fe1fedd5d": "What are the key factors considered in health insurance risk assessments?", "faaf64ee-40f7-4b25-9728-d640745e0a90": "How do wearable technologies contribute to wellness apps?", "03221c60-4936-437c-ad35-65b5cb1935c1": "What algorithms are used in determining access to financial systems?", "d909e267-78c1-4718-abc3-4c5eacc1c332": "How do credit scoring systems impact loan allocation?", "4953d062-f6dc-4435-8edf-ed0f4e8baf36": "What role do automated interest rate determinations play in financial systems?", "a1f064d0-fe0e-4009-ad4e-da914ad74ab1": "How do insurance algorithms assess drug addiction risks?", "90c10536-7c1f-4080-96dc-6558f5fb05e1": "What are the ethical concerns surrounding insurance care allocation algorithms?", "9d896814-0ecb-4f79-9aee-8558f5e95807": "How do financial algorithms apply penalties like wage garnishment?", "9fba01ca-f4ac-40a5-845e-7e7798ee3c4a": "What is the impact of underwriting algorithms on health insurance costs?", "9c45750d-00eb-4f95-b273-e109238629c4": "How do wellness apps integrate with wearable technologies to improve health outcomes?", "9dfeb337-4771-4307-8f63-5a084befadf1": "What are the key steps in ensuring automated systems are safe and effective?", "5db1d569-a143-4b95-a780-abd6a626429c": "How can diverse community consultation improve the safety of automated systems?", "36cb7b8b-ec8a-4240-932d-f4d013ec010c": "What is the importance of pre-deployment testing for automated systems?", "4e1b4a56-946d-4b57-97a8-a7e7043aafbd": "How do you identify and mitigate risks in automated systems?", "ba44fb84-6b28-4604-b4cc-4e0cb6156a75": "Why is ongoing monitoring crucial for the safety of automated systems?", "709b6157-47f9-4f13-b778-73ea7b5cd999": "What should be done if an automated system is found to be unsafe after deployment?", "b831d5ce-83d9-44cc-8451-30165592bc6a": "How can automated systems be designed to prevent unintended harm?", "48591766-4e73-4127-9689-ac3ec34938b0": "What role do domain-specific standards play in the development of automated systems?", "70259660-a0cb-4dad-9af2-f1552f5c5405": "How can stakeholders contribute to the development of safe automated systems?", "5da3d175-a205-4f12-9bc7-b0694cc97663": "What measures can be taken to ensure automated systems do not endanger community safety?", "ba9a37a2-ff2b-496c-b75a-bea68b9b4d20": "What is the main argument presented by Darshali A Vyas et al in their article on race correction in clinical algorithms?", "77397e84-ee4c-4691-9eea-95549a0f45b1": "How does the Executive Order on Advancing Racial Equity define 'equity' and 'underserved communities'?", "c4c9deb3-0d0c-4b68-a899-07733f551dce": "What are some of the proposals offered by various organizations for designing algorithmic impact assessments?", "2af51b13-b8e3-4522-b662-cbd6f11fa87c": "Can you provide a summary of the article \"Hidden in Plain Sight \u2013 Reconsidering the Use of Race Correction in Clinical Algorithms\"?", "203b4219-e580-474c-8c70-588f4c24500f": "What is the significance of the Executive Order on Advancing Racial Equity and Support for Underserved Communities?", "c20f89ba-0198-4bb6-83d4-436159a5fecb": "Who are the authors of the report \"Assembling Accountability: Algorithmic Impact Assessment for the Public Interest\"?", "beea4d1a-fc3a-4f4c-b9fa-a3c73abf6041": "How does the New England Journal of Medicine article address the issue of race correction in clinical algorithms?", "b49c589c-51d8-4cdc-93e1-6d74c67948f7": "What are the key points discussed in Section 2 of the Executive Order on Advancing Racial Equity?", "71a79413-b607-4093-91a6-cedb011b3b57": "What is the role of Data & Society in the context of algorithmic impact assessments?", "89504f33-70c7-44e7-acee-ad69679cf410": "How can one access the full text of the article \"Hidden in Plain Sight \u2013 Reconsidering the Use of Race Correction in Clinical Algorithms\"?", "abccae6f-f846-42a0-ae0c-e7553ed3bcf9": "How do automated systems threaten the rights of the American public?", "1fe6aca7-365b-48fd-840b-21cafc375daa": "In what ways have technology and data been used to limit opportunities and access to resources?", "35d9684c-2d7c-462a-888f-687e5c1743d1": "What are some documented problems with systems designed to help with patient care?", "f3af11a5-dee0-41ce-9ec8-2befaa2c4b82": "How do algorithms in hiring and credit decisions reproduce existing inequities?", "f6a36e8c-7547-40e4-ab95-7e3640f7d9b0": "What are the potential harms of unchecked social media data collection?", "fd9e9dca-1dea-4621-9bc7-a973840546ac": "How can automated systems undermine privacy and track activity without consent?", "86f7a45a-b678-4ca0-9231-2659114e545f": "What are some examples of bias and discrimination embedded in automated systems?", "2807de8e-8f7e-4f04-9938-9baaf2698edf": "How can the harmful outcomes of automated systems be prevented?", "82042ccd-7ba3-45de-be88-dd7926ed2fa7": "What are the challenges posed to democracy by the use of technology and data?", "3f49ac16-f537-46ae-ac21-b82e769969c2": "How can we ensure that automated systems are safe and effective?", "ad65e418-3028-4caf-8dda-28cfc82b6e65": "What is generative AI and how does it create synthetic content?", "8a14b547-517f-4f3e-b937-5205af638a25": "How are foundation models related to generative AI?", "e996fac3-d63c-4fec-bdd3-645e2052ce20": "What are dual-use foundation models as defined by EO 14110?", "2fff0be9-8a59-42da-9d8f-9bf01c03c3a5": "What is the significance of self-supervision in training AI models?", "ff4c692f-1cfe-467e-9925-e44da6bac8a6": "How many parameters do dual-use foundation models typically contain?", "77dc336f-61a8-4597-8e60-7d6a28b2750a": "What is the role of the National Institute of Standards and Technology (NIST) in developing resources for generative AI?", "992eb21e-18d3-431b-82ee-6c8845b57e84": "What is the AI RMF mentioned in the context of EO 14110?", "754a638c-4963-45fc-b877-baf962d095cd": "How does EO 14110 impact the development of generative AI models?", "7837880f-1aaa-4a74-a820-8b848142069f": "What types of digital content can generative AI produce?", "83e7fc2a-5676-4a2d-9b53-fe9dc216d52d": "What is the purpose of NIST AI 100\u20131 in relation to generative AI?", "da4c933d-5790-469e-8c9c-08a80e387962": "What are the best practices for obtaining informed consent in feedback activities?", "b85c7dc7-598b-4f88-a94c-845f6bfd5cec": "How can organizations ensure they are following human subjects research requirements?", "e973c5e2-042d-4219-9ab3-9357946c544f": "What are effective methods for compensating subjects in research studies?", "3750af0a-f7d0-4923-8075-a53beefd9441": "How can feedback activities improve system documentation?", "5d13e05d-ba03-4e6f-8b60-c6aba8ce6ab7": "What role does informed consent play in enhancing debugging practices?", "de4376c0-1172-4302-94d6-b2308ff91785": "What are the key components of human subjects research requirements?", "35b33780-ab39-406c-a73a-5af626b322df": "How can organizations balance subject compensation with ethical considerations?", "2da11dfc-4bf8-44c6-b11b-bb784841bfa5": "What strategies can be used to integrate feedback into decision-making processes?", "9c4e8887-02a6-46a2-855f-dd49cdc870b1": "How does subject compensation impact the quality of feedback received?", "c3b4dffe-1622-4cde-b35d-0384b5fe8b90": "What are the ethical considerations when implementing feedback activities in organizations?", "ee6a09cb-bc0e-4337-94c7-9f98ea4e5ee3": "What is the role of the Software & Information Industry Association in the tech industry?", "b23e7b4f-f930-4e25-9deb-614c17f86250": "How is Stephanie Dinkins contributing to the Future Histories Studio at Stony Brook University?", "40981bd2-f90d-4edb-a063-87981f5fad81": "What initiatives does TechNet support in the technology sector?", "dc149b68-bca5-4e5e-912d-d7be8e71e054": "How does the Alliance for Media Arts and Culture collaborate with MIT Open Documentary Lab and Co-Creation Studio?", "d5696d57-18c7-4cce-961f-32fcfcc85df9": "What are the main objectives of the International Brotherhood of Teamsters in relation to technology?", "61c0fd7b-0e62-4a0b-9328-ce82b486e261": "How does the Leadership Conference on Civil and Human Rights engage with technology policy?", "6c72d4a0-152b-4b01-afbc-bbec5f6e4b2f": "What is Thorn's mission in the context of technology and human rights?", "8478afea-bd7b-47d0-8e3b-4ade048996f5": "What is the US Chamber of Commerce\u2019s Technology Engagement Center's stance on emerging technologies?", "f855fd92-7288-4188-bcc8-9e9d6658cb4c": "How does the University of Pittsburgh Undergraduate Student Collaborative contribute to tech research?", "9363da58-a7e3-417b-8b3f-f36f8cc73b2e": "What is the focus of the XR Safety Initiative in the realm of extended reality technologies?", "c7a8a9e5-f64e-4726-a954-752b9bfa62d8": "What are the key components of establishing policies, procedures, and processes for oversight functions in the GAI lifecycle?", "d4f81aa1-536d-4926-ab69-7bf7a5842d58": "How can organizations ensure effective oversight from problem formulation to system decommission in AI projects?", "6ec865eb-0ef1-4d0f-a574-83c9bcb8e93a": "What roles do senior leadership, legal, and compliance teams play in the oversight of AI systems?", "10621bd5-3020-4fd2-8090-ee0a5a365370": "What are the main tasks involved in AI deployment, design, development, operation, and monitoring?", "8a985b69-031f-42d8-b2fe-c3c003206f80": "How should organizational teams document the risks and potential impacts of AI technology?", "d55c5fb5-723c-4f9c-b466-fbe12ec885fb": "What are the best practices for communicating the impacts of AI technology more broadly within an organization?", "87cdba18-ff3f-490d-97f4-3679a7ab585f": "Why is it important to establish terms of use and terms of service for GAI systems?", "d1a0a484-a7da-40ad-b494-d8fba48d4cc8": "How can organizations address risks related to intellectual property, dangerous content, and abusive content in AI systems?", "d95e85a2-6162-47ed-bc37-6e7bf3a90580": "What is the significance of including relevant AI actors in the GAI system risk identification process?", "c8a9e9a9-ec2d-4b97-a906-cc52fec59a02": "How can organizations verify the downstream impacts of GAI systems, especially when using third-party components?", "050deb8f-2d38-4b19-abce-8d42367a3897": "Why is data privacy considered a foundational principle in modern business models?", "e4ead17c-b324-49df-9768-46f3947244e3": "How do companies use data collection to build individual profiles?", "2e67721a-7a35-4081-a350-c289a7b797bb": "What are some examples of how data privacy can protect against surveillance?", "ffcf5bdb-0269-4d50-a0fc-e0f5cd5d6cf0": "How do government agencies utilize data collection for law enforcement purposes?", "805ffbfc-6fde-4a13-af7b-92d425ac5ff2": "What are the potential risks of companies tracking the behavior of the public?", "b7173668-8845-4ff4-a8bf-82d58d4670cf": "How does data privacy impact the use of automated systems?", "f786de70-6184-40ef-bcd4-dbc7e418ec99": "Why is data sharing and reuse a concern for data privacy?", "dd27c837-114d-4771-b470-8edadae0e05e": "What technologies are used by law enforcement to enhance surveillance capabilities?", "f986530c-70e1-4674-a4a3-d2c2fa9f3c48": "How can data privacy principles help protect individual freedoms?", "d6f7085a-3f9d-41d4-a61c-de22f689406b": "What are the implications of expanded surveillance capabilities on data privacy?", "69e6c713-aa1a-4a39-b3b8-5a9c3d192560": "What are the potential risks of using the same algorithm in employment and lending decisions?", "b9ded17f-ece6-4a9a-83db-3d1c1ce214b6": "How can correlated failures in AI systems affect the labor market?", "118c93d6-f413-43f8-9eb0-5322555c7701": "What are some examples of unexpected shocks that could impact AI decision-making systems?", "378ad341-25e9-4a99-82e3-2d3b20c79183": "How might the use of AI in employment decisions influence job security?", "3e2c5916-b757-4486-950c-91ae7c275a13": "What are the projected impacts of AI on the workforce according to recent studies?", "604a356d-af0d-4af6-ae0a-2362a5215a8e": "Why are fewer studies examining the impact of General Artificial Intelligence (GAI) on the labor market?", "70c87bb5-4afa-45a5-a192-51c40b99026a": "How are employees and employers reacting to the potential disruption caused by GAI?", "6246f0e9-a17a-44cc-99f0-30db573afe58": "What measures can be taken to mitigate the risks of correlated failures in AI systems?", "e8751b61-9fee-43e4-99ce-3c16b3f81807": "How do industry surveys reflect the concerns of employees regarding AI in the workplace?", "5e9a5f8c-765c-428a-a81c-62574fa7770e": "What are the implications of multiple actors relying on the same algorithm in lending decisions?", "8fd0cff6-85a3-4dba-abda-91cdb762349a": "What are the environmental impacts of high compute resource utilization in training AI models?", "5cd61fe8-2405-49cc-93bf-9ad9a656887b": "How does the use of non-representative training data lead to performance disparities between sub-groups or languages in AI models?", "05c34830-40b3-4fe5-9695-44a5b4ddb868": "In what ways can AI models amplify historical, societal, and systemic biases?", "a5419133-45d4-4c99-9e69-273c2f4058cb": "What are the potential adverse effects on ecosystems due to the high compute resource utilization in AI operations?", "ef754679-4152-42b3-a445-a7b434eebddd": "How can undesired homogeneity in AI model outputs lead to ill-founded decision-making?", "832fc999-15fc-4b42-9654-2177da3e8011": "What is algorithmic aversion, and how does it affect human-AI interactions?", "15f4dc2c-db75-4f81-a8cf-149786ddd579": "How can over-reliance on AI systems impact human decision-making?", "e4d93cdb-eeac-42f2-9ae7-a646b63d3e7c": "What are the risks of anthropomorphizing AI systems in human-AI configurations?", "ec919833-ed12-42e2-9839-457e42e0568f": "How does automation bias manifest in interactions between humans and AI systems?", "3dd2b1f9-4fae-4eb2-8ead-27f913346a48": "What measures can be taken to mitigate the amplification of harmful biases in AI models?", "8eb81f04-21af-4b5e-b8bc-5dd9ddf12a19": "What are the most effective metrics for measuring the effectiveness of data provenance in security?", "7c17281e-f1f1-4b05-a681-4f085c6d7b0d": "How can user feedback be analyzed to improve understanding of content authenticity?", "57455a6a-fdc6-40a8-810e-ce67e69a459c": "What are the common concerns users have regarding content provenance and authenticity?", "cf632d03-f1b6-4eac-82f3-c0eeb5c6a7b7": "How do watermarking and cryptographic signatures contribute to content authentication?", "cbedd326-5ed2-4e1e-8b52-9599a3a3ef5a": "What methods can be used to measure the reliability of content authentication techniques?", "e199ba84-6648-43a1-8075-da2bccf8135f": "How can the rate of false positives and false negatives in content provenance be evaluated?", "42cbc313-aee1-442e-9707-f8a4cda1b659": "What is the importance of model integrity verification in content provenance?", "f174193d-52c9-4008-9de8-a830c2ab8659": "How does the number of unauthorized access attempts reflect the effectiveness of security measures?", "447c315e-07a6-4f78-bbc8-b783bcbf758a": "What role do digital fingerprints play in ensuring information integrity?", "3b87a3bd-9810-4130-9a77-016a6194b4af": "How can access controls and conformity assessments support content provenance techniques?", "6d54ebc0-4ddd-48e8-ac25-0f3b41399d6e": "How can I find out if an automated system is being used to make decisions that impact me?", "6126ed1b-d1c5-4b25-8dc0-506e2f075845": "What kind of documentation should designers and developers provide for automated systems?", "4e4463eb-454a-4f19-83a0-710cb38be7ed": "Who is responsible for maintaining and updating the notice about the use of automated systems?", "0875bf4d-94e5-4bc1-b7bd-a0618b496482": "How can I understand the role of automation in the outcomes that affect me?", "c4015147-e2ab-4686-b432-838d5504d8f4": "What should I do if I notice significant changes in the functionality of an automated system that impacts me?", "8f24b9bc-1fb7-45c6-9731-cce8c51d4bd2": "How can I get a clear explanation of how an automated system determined an outcome that affects me?", "ce820b6d-3bab-4138-b21e-3c94a05b131b": "What does it mean for an explanation from an automated system to be technically valid and meaningful?", "415c6ec6-f835-405b-bbcc-1e0ed22ea3e8": "How often should the notice about the use of automated systems be updated?", "7f81c5f0-eec3-40da-88f8-3a10b20297e9": "What should be included in the plain language documentation for automated systems?", "9fa50cab-5394-4aec-916b-5e47d663a1fb": "How can I know if an automated system is not the sole input determining an outcome that impacts me?", "ca32a8ce-0352-48e1-b059-40b626805076": "What are the key expectations for automated systems to ensure they are free from algorithmic discrimination?", "c303bf4a-19e7-45a2-a17a-3a2cbb7c518b": "How can automated systems be tested to ensure they do not exhibit algorithmic discrimination?", "3248fe7a-931f-43b9-a807-be31c9cba85c": "What does it mean to design automated systems to ensure equity, broadly construed?", "2541eb4b-0325-4e71-a932-aa9c2240ff5f": "How do existing anti-discrimination laws apply to algorithmic discrimination in automated systems?", "f12e1350-6a69-48ac-9443-7bdf2fe8a551": "What proactive technical steps can be taken to reinforce legal protections against algorithmic discrimination?", "d6014c0b-7667-4f4c-8c17-3d64e472ae45": "What policy steps can be taken to ensure equity for underserved communities in the context of automated systems?", "caf9948f-d28b-4304-b2a9-7b8099401937": "How can protections against algorithmic discrimination be integrated throughout the design process of automated systems?", "aa086a0f-d233-467a-a4d1-307fd662e78e": "What are some examples of sectors or contexts where additional technical standards for automated systems might be needed?", "1ed1b3ca-848b-43f1-9413-11eb5e39d5cf": "How can the development of automated systems extend beyond legal protections to ensure equity?", "30377abc-d189-4360-8bda-75aa620ba449": "What are the potential challenges in ensuring automated systems are free from algorithmic discrimination?", "5c610b06-5ba5-458d-96b7-23660211a937": "What are the main reasons people might prefer not to use an automated system?", "f2bd0bb9-78d0-463e-9e19-206aca0bdab8": "How can automated systems lead to unintended outcomes?", "9a107472-63da-4150-b45b-9ee5a0f906d1": "In what ways can automated systems reinforce bias?", "38c99ae1-7267-4154-86cf-10c475dfab87": "Why might automated systems be considered inaccessible to some people?", "1fdcc7e8-a5a5-4068-84b8-8860d4fae85a": "What are the potential inconveniences of using automated systems?", "fabe7ff6-7665-4ee8-9e67-18e690b5c99a": "How can the replacement of paper or manual processes by automated systems affect people?", "4f7e6756-8436-4690-bb5d-8dd5e1dc19d3": "What challenges do people face when trying to reach a human decision-maker after using an automated system?", "5c5aab7b-a9cb-4e35-9853-670e020c2aff": "How does the lack of human reconsideration impact access to rights and opportunities?", "110bdd1f-0551-477c-8ad2-fe3771e46d11": "What are some examples of delayed access caused by reliance on automated systems?", "d584dcfb-bb0c-406b-813d-7ed4f0a60630": "How can the principle of human alternatives and reconsideration protect against the flaws of automated systems?", "6f2db439-4624-4bad-9cfd-f22bb387bf87": "What are the processes for identifying emergent GAI system risks?", "71f13148-d4ab-498f-ad28-d437b31d648c": "How can external AI actors be consulted to identify GAI system risks?", "915bdb26-45ca-41a4-a5c4-026de9664a4d": "What is the role of human-AI configuration in managing GAI risks?", "3f1a9bb4-4f35-4ca2-8c26-6d0fe7f70c0c": "How does confabulation impact GAI systems?", "562ffbd0-42ee-4f9d-a966-3fb61c224bdf": "What tasks are AI actors responsible for in the context of GAI risks?", "6ca39f09-5de1-4418-b8c2-8326d872cf08": "How are feedback processes for end users integrated into AI system evaluation metrics?", 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and component integration process?", "55a7d693-1922-4dd6-8840-e8017fd5d458": "What organizational practices are essential for effective AI operation and monitoring?", "088e1b4b-78b3-4dca-a354-7414b72febcc": "How can information integrity be maintained through content provenance methodologies?", "4979e972-3cfb-4a75-b2e2-92fc4640b928": "What are the key components of an effective AI incident reporting system?", "826ee64d-fab2-40f1-a6c0-911a7a68785a": "How can organizations ensure information security in AI systems?", "4216a185-7dcb-478c-b3cb-1cf32485b29f": "What tasks are involved in AI development and how do they impact the overall AI governance?", "1f50cb43-e63f-46c6-8a05-c03b8d9f604c": "How can organizations establish effective policies for AI system incident reporting?"}, "relevant_contexts": {"1d8a0cfc-df53-467f-88e8-cd378990da4b": ["70527d5b-6c55-4982-ae73-eb6cbd605bc1"], "9ec9d981-9115-4672-bd74-23035ecc2e7f": ["70527d5b-6c55-4982-ae73-eb6cbd605bc1"], 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"350eaf07-f263-4761-aa56-cb44ce3ea3d1": ["657cf38d-9798-4c12-83e4-12695c9d7a54"], "aa8cb59a-2ee8-4000-a39f-520d7f5ab6b3": ["657cf38d-9798-4c12-83e4-12695c9d7a54"], "55a7d693-1922-4dd6-8840-e8017fd5d458": ["657cf38d-9798-4c12-83e4-12695c9d7a54"], "088e1b4b-78b3-4dca-a354-7414b72febcc": ["657cf38d-9798-4c12-83e4-12695c9d7a54"], "4979e972-3cfb-4a75-b2e2-92fc4640b928": ["657cf38d-9798-4c12-83e4-12695c9d7a54"], "826ee64d-fab2-40f1-a6c0-911a7a68785a": ["657cf38d-9798-4c12-83e4-12695c9d7a54"], "4216a185-7dcb-478c-b3cb-1cf32485b29f": ["657cf38d-9798-4c12-83e4-12695c9d7a54"], "1f50cb43-e63f-46c6-8a05-c03b8d9f604c": ["657cf38d-9798-4c12-83e4-12695c9d7a54"]}, "corpus": {"70527d5b-6c55-4982-ae73-eb6cbd605bc1": "15 \nGV-1.3-004 Obtain input from stakeholder communities to identify unacceptable use, in \naccordance with activities in the AI RMF Map function. \nCBRN Information or Capabilities; \nObscene, Degrading, and/or \nAbusive Content; Harmful Bias \nand Homogenization; Dangerous, \nViolent, or Hateful Content \nGV-1.3-005 \nMaintain an updated hierarchy of identi\ufb01ed and expected GAI risks connected to \ncontexts of GAI model advancement and use, potentially including specialized risk \nlevels for GAI systems that address issues such as model collapse and algorithmic \nmonoculture. \nHarmful Bias and Homogenization \nGV-1.3-006 \nReevaluate organizational risk tolerances to account for unacceptable negative risk \n(such as where signi\ufb01cant negative impacts are imminent, severe harms are \nactually occurring, or large-scale risks could occur); and broad GAI negative risks, \nincluding: Immature safety or risk cultures related to AI and GAI design, \ndevelopment and deployment, public information integrity risks, including impacts", "e1c576fd-2981-4519-abe0-a6954ac7bfc7": "55 \nDe Angelo, D. (2024) Short, Mid and Long-Term Impacts of AI in Cybersecurity. Palo Alto Networks. \nhttps://www.paloaltonetworks.com/blog/2024/02/impacts-of-ai-in-cybersecurity/ \nDe Freitas, J. et al. (2023) Chatbots and Mental Health: Insights into the Safety of Generative AI. Harvard \nBusiness School. https://www.hbs.edu/ris/Publication%20Files/23-011_c1bdd417-f717-47b6-bccb-\n5438c6e65c1a_f6fd9798-3c2d-4932-b222-056231fe69d7.pdf \nDietvorst, B. et al. (2014) Algorithm Aversion: People Erroneously Avoid Algorithms After Seeing Them \nErr. Journal of Experimental Psychology. https://marketing.wharton.upenn.edu/wp-\ncontent/uploads/2016/10/Dietvorst-Simmons-Massey-2014.pdf \nDuhigg, C. (2012) How Companies Learn Your Secrets. New York Times. \nhttps://www.nytimes.com/2012/02/19/magazine/shopping-habits.html \nElsayed, G. et al. (2024) Images altered to trick machine vision can in\ufb02uence humans too. Google \nDeepMind. https://deepmind.google/discover/blog/images-altered-to-trick-machine-vision-can-", "b0c72830-d6f3-465d-9db2-3a0fe4eca18d": "40 \nMANAGE 1.3: Responses to the AI risks deemed high priority, as identi\ufb01ed by the MAP function, are developed, planned, and \ndocumented. Risk response options can include mitigating, transferring, avoiding, or accepting. \nAction ID \nSuggested Action \nGAI Risks \nMG-1.3-001 \nDocument trade-o\ufb00s, decision processes, and relevant measurement and \nfeedback results for risks that do not surpass organizational risk tolerance, for \nexample, in the context of model release: Consider di\ufb00erent approaches for \nmodel release, for example, leveraging a staged release approach. Consider \nrelease approaches in the context of the model and its projected use cases. \nMitigate, transfer, or avoid risks that surpass organizational risk tolerances. \nInformation Security \nMG-1.3-002 \nMonitor the robustness and e\ufb00ectiveness of risk controls and mitigation plans \n(e.g., via red-teaming, \ufb01eld testing, participatory engagements, performance \nassessments, user feedback mechanisms). \nHuman-AI Con\ufb01guration", "c8f55f69-05d8-4ee1-a313-d97e683e995c": "MEASURE 1.1: Approaches and metrics for measurement of AI risks enumerated during the MAP function are selected for \nimplementation starting with the most signi\ufb01cant AI risks. The risks or trustworthiness characteristics that will not \u2013 or cannot \u2013 be \nmeasured are properly documented. \nAction ID \nSuggested Action \nGAI Risks \nMS-1.1-001 Employ methods to trace the origin and modi\ufb01cations of digital content. \nInformation Integrity \nMS-1.1-002 \nIntegrate tools designed to analyze content provenance and detect data \nanomalies, verify the authenticity of digital signatures, and identify patterns \nassociated with misinformation or manipulation. \nInformation Integrity \nMS-1.1-003 \nDisaggregate evaluation metrics by demographic factors to identify any \ndiscrepancies in how content provenance mechanisms work across diverse \npopulations. \nInformation Integrity; Harmful \nBias and Homogenization \nMS-1.1-004 Develop a suite of metrics to evaluate structured public feedback exercises", "0c405046-7c29-4c97-9cd3-b0fa85f4e26e": "https://www.whitehouse.gov/wp-\ncontent/uploads/legacy_drupal_\ufb01les/omb/circulars/A130/a130revised.pdf \nThe White House (2023) Executive Order on the Safe, Secure, and Trustworthy Development and Use of \nArti\ufb01cial Intelligence. https://www.whitehouse.gov/brie\ufb01ng-room/presidential-\nactions/2023/10/30/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-\narti\ufb01cial-intelligence/ \nThe White House (2022) Roadmap for Researchers on Priorities Related to Information Integrity \nResearch and Development. https://www.whitehouse.gov/wp-content/uploads/2022/12/Roadmap-\nInformation-Integrity-RD-2022.pdf? \nThiel, D. (2023) Investigation Finds AI Image Generation Models Trained on Child Abuse. Stanford Cyber \nPolicy Center. https://cyber.fsi.stanford.edu/news/investigation-\ufb01nds-ai-image-generation-models-\ntrained-child-abuse", "f477adb6-0df5-47c6-abe8-a23fe8b6feec": "false, illegal, or violent content related to the GAI application, including for CSAM \nand NCII. These \ufb01lters can be rule-based or leverage additional machine learning \nmodels to \ufb02ag problematic inputs and outputs. \nInformation Integrity; Harmful Bias \nand Homogenization; Dangerous, \nViolent, or Hateful Content; \nObscene, Degrading, and/or \nAbusive Content \nMG-3.2-006 \nImplement real-time monitoring processes for analyzing generated content \nperformance and trustworthiness characteristics related to content provenance \nto identify deviations from the desired standards and trigger alerts for human \nintervention. \nInformation Integrity", "77cdea0d-2124-4f93-8aa1-8bca37d473cf": "guidance/\n54. Ziad Obermeyer, Brian Powers, Christine Vogeli, and Sendhil Mullainathan. Dissecting racial bias in\nan algorithm used to manage the health of populations. Science. Vol. 366, No. 6464. Oct. 25, 2019. https://\nwww.science.org/doi/10.1126/science.aax2342\n55. Data & Trust Alliance. Algorithmic Bias Safeguards for Workforce: Overview. Jan. 2022. https://\ndataandtrustalliance.org/Algorithmic_Bias_Safeguards_for_Workforce_Overview.pdf\n56. Section 508.gov. IT Accessibility Laws and Policies. Access Board. https://www.section508.gov/\nmanage/laws-and-policies/\n67", "ac99c8aa-92a2-4280-93c2-b20c7b858026": "yet foreseeable, uses or impacts of automated systems. You should be \nprotected from inappropriate or irrelevant data use in the design, de\u00ad\nvelopment, and deployment of automated systems, and from the \ncompounded harm of its reuse. Independent evaluation and report\u00ad\ning that confirms that the system is safe and effective, including re\u00ad\nporting of steps taken to mitigate potential harms, should be per\u00ad\nformed and the results made public whenever possible. \n15", "4b7be742-d2a1-4cc5-9bae-6c4cdda913c5": "Models Using Complex Algorithms. May 26, 2022.\nhttps://www.consumerfinance.gov/about-us/newsroom/cfpb-acts-to-protect-the-public-from-black\u00ad\nbox-credit-models-using-complex-algorithms/\n93. Anthony Zaller. California Passes Law Regulating Quotas In Warehouses \u2013 What Employers Need to\nKnow About AB 701. Zaller Law Group California Employment Law Report. Sept. 24, 2021.\nhttps://www.californiaemploymentlawreport.com/2021/09/california-passes-law-regulating-quotas\u00ad\nin-warehouses-what-employers-need-to-know-about-ab-701/\n94. National Institute of Standards and Technology. AI Fundamental Research \u2013 Explainability.\nAccessed Jun. 4, 2022.\nhttps://www.nist.gov/artificial-intelligence/ai-fundamental-research-explainability\n95. DARPA. Explainable Artificial Intelligence (XAI). Accessed July 20, 2022.\nhttps://www.darpa.mil/program/explainable-artificial-intelligence\n71", "2bbd9e32-096d-4731-9cca-baad231face1": "robustness, safety, security (resilience), and mitigation of unintended and/or harmful bias, as well as of \nharmful \nuses. \nThe \nNIST \nframework \nwill \nconsider \nand \nencompass \nprinciples \nsuch \nas \ntransparency, accountability, and fairness during pre-design, design and development, deployment, use, \nand testing and evaluation of AI technologies and systems. It is expected to be released in the winter of 2022-23. \n21", "170bd80f-9f9f-4392-a542-6c6048951770": "use within sensitive domains, including, but not limited to, criminal \njustice, employment, education, and health, should additionally be \ntailored to the purpose, provide meaningful access for oversight, \ninclude training for any people interacting with the system, and in\u00ad\ncorporate human consideration for adverse or high-risk decisions. \nReporting that includes a description of these human governance \nprocesses and assessment of their timeliness, accessibility, out\u00ad\ncomes, and effectiveness should be made public whenever possible. \nHUMAN ALTERNATIVES, CONSIDERATION\nALLBACK\nF\nAND\n, \n46", "b3c303db-afa6-45c9-b4c4-9081fde8c735": "\u201cquantified number of tasks to be performed or materials to be produced or handled, within the defined \ntime period, and any potential adverse employment action that could result from failure to meet the quota.\u201d93\nAcross the federal government, agencies are conducting and supporting research on explain-\nable AI systems. The NIST is conducting fundamental research on the explainability of AI systems. A multidis-\nciplinary team of researchers aims to develop measurement methods and best practices to support the \nimplementation of core tenets of explainable AI.94 The Defense Advanced Research Projects Agency has a \nprogram on Explainable Artificial Intelligence that aims to create a suite of machine learning techniques that \nproduce more explainable models, while maintaining a high level of learning performance (prediction \naccuracy), and enable human users to understand, appropriately trust, and effectively manage the emerging", "4fe6d91a-9662-4530-83d4-30121fbaa3e1": "assessment and mitigation. Organizational stakeholders including those with oversight of the business process \nor operation being automated, as well as other organizational divisions that may be affected due to the use of \nthe system, should be involved in establishing governance procedures. Responsibility should rest high enough \nin the organization that decisions about resources, mitigation, incident response, and potential rollback can be \nmade promptly, with sufficient weight given to risk mitigation objectives against competing concerns. Those \nholding this responsibility should be made aware of any use cases with the potential for meaningful impact on \npeople\u2019s rights, opportunities, or access as determined based on risk identification procedures.  In some cases, \nit may be appropriate for an independent ethics review to be conducted before deployment. \nAvoid inappropriate, low-quality, or irrelevant data use and the compounded harm of its \nreuse", "65f61b92-532d-4937-a252-a07f66dc8b6d": "system is introduced or a large change implemented. This consultation should directly engage diverse impact\u00ad\ned communities to consider concerns and risks that may be unique to those communities, or disproportionate\u00ad\nly prevalent or severe for them. The extent of this engagement and the form of outreach to relevant stakehold\u00ad\ners may differ depending on the specific automated system and development phase, but should include \nsubject matter, sector-specific, and context-specific experts as well as experts on potential impacts such as \ncivil rights, civil liberties, and privacy experts. For private sector applications, consultations before product \nlaunch may need to be confidential. Government applications, particularly law enforcement applications or \napplications that raise national security considerations, may require confidential or limited engagement based \non system sensitivities and preexisting oversight laws and structures. Concerns raised in this consultation", "4bcaf9fc-e04a-4901-a926-656d64bc2300": "APPENDIX\nPanel 3: Equal Opportunities and Civil Justice. This event explored current and emerging uses of \ntechnology that impact equity of opportunity in employment, education, and housing. \nWelcome: \n\u2022\nRashida Richardson, Senior Policy Advisor for Data and Democracy, White House Office of Science and\nTechnology Policy\n\u2022\nDominique Harrison, Director for Technology Policy, The Joint Center for Political and Economic\nStudies\nModerator: Jenny Yang, Director, Office of Federal Contract Compliance Programs, Department of Labor \nPanelists: \n\u2022\nChristo Wilson, Associate Professor of Computer Science, Northeastern University\n\u2022\nFrida Polli, CEO, Pymetrics\n\u2022\nKaren Levy, Assistant Professor, Department of Information Science, Cornell University\n\u2022\nNatasha Duarte, Project Director, Upturn\n\u2022\nElana Zeide, Assistant Professor, University of Nebraska College of Law\n\u2022\nFabian Rogers, Constituent Advocate, Office of NY State Senator Jabari Brisport and Community", "be74e45d-d511-47b2-96c9-b56ff1e3ef92": "Human-AI Con\ufb01guration \nGV-2.1-004 When systems may raise national security risks, involve national security \nprofessionals in mapping, measuring, and managing those risks. \nCBRN Information or Capabilities; \nDangerous, Violent, or Hateful \nContent; Information Security \nGV-2.1-005 \nCreate mechanisms to provide protections for whistleblowers who report, based \non reasonable belief, when the organization violates relevant laws or poses a \nspeci\ufb01c and empirically well-substantiated negative risk to public safety (or has \nalready caused harm). \nCBRN Information or Capabilities; \nDangerous, Violent, or Hateful \nContent \nAI Actor Tasks: Governance and Oversight", "56e2a4fd-2a2a-444b-83a2-afa40b190add": "which can be used to evaluate gender bias in natural language processing coreference resolution systems.", "cb3de03f-35e4-4032-8357-256a59e540bf": "helped to reshape power and give more voice to those lacking the financial or political power to effect change. \nIn discussion of technical and governance interventions that that are needed to protect against the harms \nof these technologies, various panelists emphasized the need for transparency, data collection, and \nflexible and reactive policy development, analogous to how software is continuously updated and deployed. \nSome panelists pointed out that companies need clear guidelines to have a consistent environment for \ninnovation, with principles and guardrails being the key to fostering responsible innovation. \nPanel 2: The Criminal Justice System. This event explored current and emergent uses of technology in \nthe criminal justice system and considered how they advance or undermine public safety, justice, and \ndemocratic values. \nWelcome: \n\u2022\nSuresh Venkatasubramanian, Assistant Director for Science and Justice, White House Office of Science\nand Technology Policy\n\u2022", "3c605102-fdfc-4821-b1f4-70662c729e24": "Jersey man was accused of shoplifting and trying to hit an officer with a car. He is the third known Black man\nto be wrongfully arrested based on face recognition. New York Times. Dec. 29, 2020, updated Jan. 6, 2021.\nhttps://www.nytimes.com/2020/12/29/technology/facial-recognition-misidentify-jail.html; Khari\nJohnson. How Wrongful Arrests Based on AI Derailed 3 Men's Lives. Wired. Mar. 7, 2022. https://\nwww.wired.com/story/wrongful-arrests-ai-derailed-3-mens-lives/\n32. Student Borrower Protection Center. Educational Redlining. Student Borrower Protection Center\nReport. Feb. 2020. https://protectborrowers.org/wp-content/uploads/2020/02/Education-Redlining\u00ad\nReport.pdf\n33. Jeffrey Dastin. Amazon scraps secret AI recruiting tool that showed bias against women. Reuters. Oct.\n10, 2018. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps\u00ad\nsecret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G", "79c6fb87-7d88-4ad2-81ff-29bd976fa9d3": "53 \nDocumenting, reporting, and sharing information about GAI incidents can help mitigate and prevent \nharmful outcomes by assisting relevant AI Actors in tracing impacts to their source. Greater awareness \nand standardization of GAI incident reporting could promote this transparency and improve GAI risk \nmanagement across the AI ecosystem.  \nDocumentation and Involvement of AI Actors \nAI Actors should be aware of their roles in reporting AI incidents. To better understand previous incidents \nand implement measures to prevent similar ones in the future, organizations could consider developing \nguidelines for publicly available incident reporting which include information about AI actor \nresponsibilities. These guidelines would help AI system operators identify GAI incidents across the AI \nlifecycle and with AI Actors regardless of role. Documentation and review of third-party inputs and \nplugins for GAI systems is especially important for AI Actors in the context of incident disclosure; LLM", "6f9495a3-d6c2-4cc8-9349-19f6faddcec6": "AI technology can produce varied outputs in multiple modalities and present many classes of user \ninterfaces. This leads to a broader set of AI Actors interacting with GAI systems for widely di\ufb00ering \napplications and contexts of use. These can include data labeling and preparation, development of GAI \nmodels, content moderation, code generation and review, text generation and editing, image and video \ngeneration, summarization, search, and chat. These activities can take place within organizational \nsettings or in the public domain. \nOrganizations can restrict AI applications that cause harm, exceed stated risk tolerances, or that con\ufb02ict \nwith their tolerances or values. Governance tools and protocols that are applied to other types of AI \nsystems can be applied to GAI systems. These plans and actions include: \n\u2022 Accessibility and reasonable \naccommodations \n\u2022 AI actor credentials and quali\ufb01cations  \n\u2022 Alignment to organizational values \n\u2022 Auditing and assessment \n\u2022 Change-management controls", "e8e842a4-5f1e-4c1f-8a44-ebd6ae57a409": "57 \nNational Institute of Standards and Technology (2023) AI Risk Management Framework, Appendix B: \nHow AI Risks Di\ufb00er from Traditional Software Risks. \nhttps://airc.nist.gov/AI_RMF_Knowledge_Base/AI_RMF/Appendices/Appendix_B \nNational Institute of Standards and Technology (2023) AI RMF Playbook. \nhttps://airc.nist.gov/AI_RMF_Knowledge_Base/Playbook \nNational Institue of Standards and Technology (2023) Framing Risk \nhttps://airc.nist.gov/AI_RMF_Knowledge_Base/AI_RMF/Foundational_Information/1-sec-risk \nNational Institute of Standards and Technology (2023) The Language of Trustworthy AI: An In-Depth \nGlossary of Terms https://airc.nist.gov/AI_RMF_Knowledge_Base/Glossary \nNational Institue of Standards and Technology (2022) Towards a Standard for Identifying and Managing \nBias in Arti\ufb01cial Intelligence https://www.nist.gov/publications/towards-standard-identifying-and-\nmanaging-bias-arti\ufb01cial-intelligence", "2a987bbc-787b-4a9c-b59c-595f5b9c2fc8": "vators deserve clear rules of the road that allow new ideas to flourish, and the American public deserves protections \nfrom unsafe outcomes. All can benefit from assurances that automated systems will be designed, tested, and consis\u00ad\ntently confirmed to work as intended, and that they will be proactively protected from foreseeable unintended harm\u00ad\nful outcomes. \n\u2022\nA proprietary model was developed to predict the likelihood of sepsis in hospitalized patients and was imple\u00ad\nmented at hundreds of hospitals around the country. An independent study showed that the model predictions\nunderperformed relative to the designer\u2019s claims while also causing \u2018alert fatigue\u2019 by falsely alerting\nlikelihood of sepsis.6\n\u2022\nOn social media, Black people who quote and criticize racist messages have had their own speech silenced when\na platform\u2019s automated moderation system failed to distinguish this \u201ccounter speech\u201d (or other critique\nand journalism) from the original hateful messages to which such speech responded.7\n\u2022", "1bf50b19-5134-4a8f-be9a-e74affa8cdd0": "primary information security risks: GAI could potentially discover or enable new cybersecurity risks by \nlowering the barriers for or easing automated exercise of o\ufb00ensive capabilities; simultaneously, it \nexpands the available attack surface, as GAI itself is vulnerable to attacks like prompt injection or data \npoisoning.  \nO\ufb00ensive cyber capabilities advanced by GAI systems may augment cybersecurity attacks such as \nhacking, malware, and phishing. Reports have indicated that LLMs are already able to discover some \nvulnerabilities in systems (hardware, software, data) and write code to exploit them. Sophisticated threat \nactors might further these risks by developing GAI-powered security co-pilots for use in several parts of \nthe attack chain, including informing attackers on how to proactively evade threat detection and escalate \nprivileges after gaining system access. \nInformation security for GAI models and systems also includes maintaining availability of the GAI system", "3203966f-15b4-425b-b621-fd964e3bd46f": "defense, substantive or procedural, enforceable at law or in equity by any party against the United States, its \ndepartments, agencies, or entities, its officers, employees, or agents, or any other person, nor does it constitute a \nwaiver of sovereign immunity. \nCopyright Information \nThis document is a work of the United States Government and is in the public domain (see 17 U.S.C. \u00a7105). \n2", "4bcc930c-273e-4cbd-bba5-a297e9f9e390": "should not be used in education, work, housing, or in other contexts where the use of such surveillance \ntechnologies is likely to limit rights, opportunities, or access. Whenever possible, you should have access to \nreporting that confirms your data decisions have been respected and provides an assessment of the \npotential impact of surveillance technologies on your rights, opportunities, or access. \nNOTICE AND EXPLANATION\nYou should know that an automated system is being used and understand how and why it \ncontributes to outcomes that impact you. Designers, developers, and deployers of automated systems \nshould provide generally accessible plain language documentation including clear descriptions of the overall \nsystem functioning and the role automation plays, notice that such systems are in use, the individual or organiza\u00ad\ntion responsible for the system, and explanations of outcomes that are clear, timely, and accessible. Such notice", "e4abdb97-5b2c-4dc9-974e-3357719369a9": "in-2021/ https://www.technologyreview.com/2021/01/15/1016183/ai-ethics-startups/; Disha Sinha. Top\nProgressive Companies Building Ethical AI to Look Out for in 2021. Analytics Insight. June 30, 2021.\n18. Office of Management and Budget. Study to Identify Methods to Assess Equity: Report to the President.\nAug. 2021. https://www.whitehouse.gov/wp-content/uploads/2021/08/OMB-Report-on-E013985\u00ad\nImplementation_508-Compliant-Secure-v1.1.pdf\n19. National Institute of Standards and Technology. AI Risk Management Framework. Accessed May 23,\n2022. https://www.nist.gov/itl/ai-risk-management-framework\n20. U.S. Department of Energy. U.S. Department of Energy Establishes Artificial Intelligence Advancement\nCouncil. U.S. Department of Energy Artificial Intelligence and Technology Office. April 18, 2022. https://\nwww.energy.gov/ai/articles/us-department-energy-establishes-artificial-intelligence-advancement-council\n21. Department of Defense. U.S Department of Defense Responsible Artificial Intelligence Strategy and", "e1c3047a-75b7-40a8-b937-22cfe0b3f2b1": "delivery, various panelists pointed to a number of concerns including access to and expense of broadband \nservice, the privacy concerns associated with telehealth systems, the expense associated with health \nmonitoring devices, and how this can exacerbate equity issues.  On the issue of technology enhanced care, \nsome panelists spoke extensively about the way in which racial biases and the use of race in medicine \nperpetuate harms and embed prior discrimination, and the importance of ensuring that the technologies used \nin medical care were accountable to the relevant stakeholders. Various panelists emphasized the importance \nof having the voices of those subjected to these technologies be heard.\n59", "48516a8d-e470-431b-ab6f-2b090a40107b": "confidence that their rights, opportunities, and access as well as their expectations about technologies are respected. \n3\nHOW THESE PRINCIPLES CAN MOVE INTO PRACTICE: \nThis section provides real-life examples of how these guiding principles can become reality, through laws, policies, and practices. \nIt describes practical technical and sociotechnical approaches to protecting rights, opportunities, and access. \nThe examples provided are not critiques or endorsements, but rather are offered as illustrative cases to help \nprovide a concrete vision for actualizing the Blueprint for an AI Bill of Rights. Effectively implementing these \nprocesses require the cooperation of and collaboration among industry, civil society, researchers, policymakers, \ntechnologists, and the public. \n14", "7b016e8e-1c9f-40b9-b7f5-246b6e7584d5": "56 \nKarasavva, V. et al. (2021) Personality, Attitudinal, and Demographic Predictors of Non-consensual \nDissemination of Intimate Images. NIH. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554400/ \nKatzman, J., et al. (2023) Taxonomizing and measuring representational harms: a look at image tagging. \nAAAI. https://dl.acm.org/doi/10.1609/aaai.v37i12.26670 \nKhan, T. et al. (2024) From Code to Consumer: PAI\u2019s Value Chain Analysis Illuminates Generative AI\u2019s Key \nPlayers. AI. https://partnershiponai.org/from-code-to-consumer-pais-value-chain-analysis-illuminates-\ngenerative-ais-key-players/ \nKirchenbauer, J. et al. (2023) A Watermark for Large Language Models. OpenReview. \nhttps://openreview.net/forum?id=aX8ig9X2a7 \nKleinberg, J. et al. (May 2021) Algorithmic monoculture and social welfare. PNAS. \nhttps://www.pnas.org/doi/10.1073/pnas.2018340118 \nLakatos, S. (2023) A Revealing Picture. Graphika. https://graphika.com/reports/a-revealing-picture", "498bff21-8221-4f12-b4c1-93f47337fba6": "content performance and impact, and work in collaboration with AI Actors \nexperienced in user research and experience. \nHuman-AI Con\ufb01guration \nMG-4.1-004 Implement active learning techniques to identify instances where the model fails \nor produces unexpected outputs. \nConfabulation \nMG-4.1-005 \nShare transparency reports with internal and external stakeholders that detail \nsteps taken to update the GAI system to enhance transparency and \naccountability. \nHuman-AI Con\ufb01guration; Harmful \nBias and Homogenization \nMG-4.1-006 \nTrack dataset modi\ufb01cations for provenance by monitoring data deletions, \nrecti\ufb01cation requests, and other changes that may impact the veri\ufb01ability of \ncontent origins. \nInformation Integrity", "ef7137f6-e670-41e6-8905-2d7c0a133bea": "NOTICE & \nEXPLANATION \nWHY THIS PRINCIPLE IS IMPORTANT\nThis section provides a brief summary of the problems which the principle seeks to address and protect \nagainst, including illustrative examples. \n\u2022\nA predictive policing system claimed to identify individuals at greatest risk to commit or become the victim of\ngun violence (based on automated analysis of social ties to gang members, criminal histories, previous experi\u00ad\nences of gun violence, and other factors) and led to individuals being placed on a watch list with no\nexplanation or public transparency regarding how the system came to its conclusions.85 Both police and\nthe public deserve to understand why and how such a system is making these determinations.\n\u2022\nA system awarding benefits changed its criteria invisibly. Individuals were denied benefits due to data entry\nerrors and other system flaws. These flaws were only revealed when an explanation of the system", "d3ad3601-20e3-41bb-bc05-092a46287a0d": "https://www.dol.gov/agencies/olms/laws/labor-management-reporting-and-disclosure-act (Section\n203). See also: U.S Department of Labor. Form LM-10. OLMS Fact Sheet, Accessed May 2, 2022. https://\nwww.dol.gov/sites/dolgov/files/OLMS/regs/compliance/LM-10_factsheet.pdf\n82. See, e.g., Apple. Protecting the User\u2019s Privacy. Accessed May 2, 2022.\nhttps://developer.apple.com/documentation/uikit/protecting_the_user_s_privacy; Google Developers.\nDesign for Safety: Android is secure by default and private by design. Accessed May 3, 2022.\nhttps://developer.android.com/design-for-safety\n83. Karen Hao. The coming war on the hidden algorithms that trap people in poverty. MIT Tech Review.\nDec. 4, 2020.\nhttps://www.technologyreview.com/2020/12/04/1013068/algorithms-create-a-poverty-trap-lawyers\u00ad\nfight-back/\n84. Anjana Samant, Aaron Horowitz, Kath Xu, and Sophie Beiers. Family Surveillance by Algorithm.\nACLU. Accessed May 2, 2022.\nhttps://www.aclu.org/fact-sheet/family-surveillance-algorithm\n70", "d1e994ed-591e-4c95-a8d4-cf84a7926602": "should be documented, and the automated system developers were proposing to create, use, or deploy should \nbe reconsidered based on this feedback. \nTesting. Systems should undergo extensive testing before deployment. This testing should follow \ndomain-specific best practices, when available, for ensuring the technology will work in its real-world \ncontext. Such testing should take into account both the specific technology used and the roles of any human \noperators or reviewers who impact system outcomes or effectiveness; testing should include both automated \nsystems testing and human-led (manual) testing. Testing conditions should mirror as closely as possible the \nconditions in which the system will be deployed, and new testing may be required for each deployment to \naccount for material differences in conditions from one deployment to another. Following testing, system \nperformance should be compared with the in-place, potentially human-driven, status quo procedures, with", "aa34d6fa-7664-4579-90fa-4f3a7ef8610c": "HUMAN ALTERNATIVES, \nCONSIDERATION, AND \nFALLBACK \nWHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\nThe expectations for automated systems are meant to serve as a blueprint for the development of additional \ntechnical standards and practices that are tailored for particular sectors and contexts. \nAn automated system should provide demonstrably effective mechanisms to opt out in favor of a human alterna\u00ad\ntive, where appropriate, as well as timely human consideration and remedy by a fallback system, with additional \nhuman oversight and safeguards for systems used in sensitive domains, and with training and assessment for any \nhuman-based portions of the system to ensure effectiveness. \nProvide a mechanism to conveniently opt out from automated systems in favor of a human \nalternative, where appropriate \nBrief, clear, accessible notice and instructions. Those impacted by an automated system should be", "8e92bbe0-47e0-42c1-acae-c650f210bf9f": "You should be protected from abusive data practices via built-in \nprotections and you should have agency over how data about \nyou is used. You should be protected from violations of privacy through \ndesign choices that ensure such protections are included by default, including \nensuring that data collection conforms to reasonable expectations and that \nonly data strictly necessary for the specific context is collected. Designers, de\u00ad\nvelopers, and deployers of automated systems should seek your permission \nand respect your decisions regarding collection, use, access, transfer, and de\u00ad\nletion of your data in appropriate ways and to the greatest extent possible; \nwhere not possible, alternative privacy by design safeguards should be used. \nSystems should not employ user experience and design decisions that obfus\u00ad\ncate user choice or burden users with defaults that are privacy invasive. Con\u00ad\nsent should only be used to justify collection of data in cases where it can be", "64a6a839-474e-4542-96a8-cb04179fdd27": "system is in use. \nLimited and proportionate surveillance. Surveillance should be avoided unless it is strictly necessary \nto achieve a legitimate purpose and it is proportionate to the need. Designers, developers, and deployers of \nsurveillance systems should use the least invasive means of monitoring available and restrict monitoring to the \nminimum number of subjects possible. To the greatest extent possible consistent with law enforcement and \nnational security needs, individuals subject to monitoring should be provided with clear and specific notice \nbefore it occurs and be informed about how the data gathered through surveillance will be used. \nScope limits on surveillance to protect rights and democratic values. Civil liberties and civil \nrights must not be limited by the threat of surveillance or harassment facilitated or aided by an automated \nsystem. Surveillance systems should not be used to monitor the exercise of democratic rights, such as voting,", "cdc23111-1d88-49c3-80f3-9ebd70b44b12": "WHY THIS PRINCIPLE IS IMPORTANT\nThis section provides a brief summary of the problems which the principle seeks to address and protect \nagainst, including illustrative examples. \u00ad\u00ad\u00ad\n\u2022\nAn automated sentiment analyzer, a tool often used by technology platforms to determine whether a state-\nment posted online expresses a positive or negative sentiment, was found to be biased against Jews and gay\npeople. For example, the analyzer marked the statement \u201cI\u2019m a Jew\u201d as representing a negative sentiment,\nwhile \u201cI\u2019m a Christian\u201d was identified as expressing a positive sentiment.36 This could lead to the\npreemptive blocking of social media comments such as: \u201cI\u2019m gay.\u201d A related company with this bias concern\nhas made their data public to encourage researchers to help address the issue37 and has released reports\nidentifying and measuring this problem as well as detailing attempts to address it.38\n\u2022\nSearches for \u201cBlack girls,\u201d \u201cAsian girls,\u201d or \u201cLatina girls\u201d return predominantly39 sexualized content, rather", "5741a856-e0d3-4918-ad9e-a70c052fa59f": "need to understand the system, and calibrated to the level of risk \nbased on the context. Reporting that includes summary information \nabout these automated systems in plain language and assessments of \nthe clarity and quality of the notice and explanations should be made \npublic whenever possible.   \nNOTICE AND EXPLANATION\n40", "416b3a7a-8d1a-4742-ab01-b6663ae8e0fa": "54 \nAppendix B. References \nAcemoglu, D. (2024) The Simple Macroeconomics of AI https://www.nber.org/papers/w32487 \nAI Incident Database. https://incidentdatabase.ai/ \nAtherton, D. (2024) Deepfakes and Child Safety: A Survey and Analysis of 2023 Incidents and Responses. \nAI Incident Database. https://incidentdatabase.ai/blog/deepfakes-and-child-safety/ \nBadyal, N. et al. (2023) Intentional Biases in LLM Responses. arXiv. https://arxiv.org/pdf/2311.07611 \nBing Chat: Data Ex\ufb01ltration Exploit Explained. Embrace The Red. \nhttps://embracethered.com/blog/posts/2023/bing-chat-data-ex\ufb01ltration-poc-and-\ufb01x/ \nBommasani, R. et al. (2022) Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome \nHomogenization? arXiv. https://arxiv.org/pdf/2211.13972 \nBoyarskaya, M. et al. (2020) Overcoming Failures of Imagination in AI Infused System Development and \nDeployment. arXiv. https://arxiv.org/pdf/2011.13416 \nBrowne, D. et al. (2023) Securing the AI Pipeline. Mandiant.", "f6481b29-2176-4fe7-9fbc-c0b492535374": "ing sessions, meetings, a formal request for information, and input to a publicly accessible and widely-publicized \nemail address, people throughout the United States, public servants across Federal agencies, and members of the \ninternational community spoke up about both the promises and potential harms of these technologies, and \nplayed a central role in shaping the Blueprint for an AI Bill of Rights. The core messages gleaned from these \ndiscussions include that AI has transformative potential to improve Americans\u2019 lives, and that preventing the \nharms of these technologies is both necessary and achievable. The Appendix includes a full list of public engage-\nments. \n4", "8cddb4be-1854-4ac9-96d8-27f9a2fb057c": "25\nAlgorithmic \nDiscrimination \nProtections", "6dbc971e-9d84-465d-bdc4-ea5d2474f896": "data or observations, or otherwise interact with individuals and/or communities. Automated systems \ninclude, but are not limited to, systems derived from machine learning, statistics, or other data processing \nor artificial intelligence techniques, and exclude passive computing infrastructure. \u201cPassive computing \ninfrastructure\u201d is any intermediary technology that does not influence or determine the outcome of decision, \nmake or aid in decisions, inform policy implementation, or collect data or observations, including web \nhosting, domain registration, networking, caching, data storage, or cybersecurity. Throughout this \nframework, automated systems that are considered in scope are only those that have the potential to \nmeaningfully impact individuals\u2019 or communi-ties\u2019 rights, opportunities, or access. \nCOMMUNITIES: \u201cCommunities\u201d include: neighborhoods; social network connections (both online and", "dfcc2c8b-5dca-42d3-ac73-d3d69301e1bc": "bute as relevant to the specific use case. Data included should be carefully limited to avoid algorithmic \ndiscrimination resulting from, e.g., use of community characteristics, social network analysis, or group-based \ninferences. \nTailored to the situation. Human oversight should ensure that automated systems in sensitive domains \nare tailored to the specific use case and real-world deployment scenario, and evaluation testing should show \nthat the system is safe and effective for that specific situation. Validation testing performed based on one loca\u00ad\ntion or use case should not be assumed to transfer to another. \nHuman consideration before any high-risk decision. Automated systems, where they are used in \nsensitive domains, may play a role in directly providing information or otherwise providing positive outcomes \nto impacted people. However, automated systems should not be allowed to directly intervene in high-risk \nsituations, such as sentencing decisions or medical care, without human consideration.", "cf94ff83-f7a3-4d72-9761-ee38111d903e": "or that can be lawfully used to detect, monitor, intercept, collect, exploit, preserve, protect, transmit, and/or \nretain data, identifying information, or communications concerning individuals or groups. This framework \nlimits its focus to both government and commercial use of surveillance technologies when juxtaposed with \nreal-time or subsequent automated analysis and when such systems have a potential for meaningful impact \non individuals\u2019 or communities\u2019 rights, opportunities, or access. \nUNDERSERVED COMMUNITIES: The term \u201cunderserved communities\u201d refers to communities that have \nbeen systematically denied a full opportunity to participate in aspects of economic, social, and civic life, as \nexemplified by the list in the preceding definition of \u201cequity.\u201d \n11", "e65f76d3-eed7-4ce0-8cc4-9638ba09e5aa": "where it can be appropriately and meaningfully given. Any consent requests should be brief, be understandable \nin plain language, and give you agency over data collection and the specific context of use; current hard-to\u00ad\nunderstand notice-and-choice practices for broad uses of data should be changed. Enhanced protections and \nrestrictions for data and inferences related to sensitive domains, including health, work, education, criminal \njustice, and finance, and for data pertaining to youth should put you first. In sensitive domains, your data and \nrelated inferences should only be used for necessary functions, and you should be protected by ethical review \nand use prohibitions. You and your communities should be free from unchecked surveillance; surveillance \ntechnologies should be subject to heightened oversight that includes at least pre-deployment assessment of their \npotential harms and scope limits to protect privacy and civil liberties. Continuous surveillance and monitoring", "31953e75-65ce-4852-9a87-bdbefefcead4": "Records, Computers, and the Rights of Citizens (July 1973). https://www.justice.gov/opcl/docs/rec-com\u00ad\nrights.pdf.\n5. See, e.g., Office of Mgmt. & Budget, Exec. Office of the President, Circular A-130, Managing Information as a\nStrategic Resource, app. II \u00a7\u00a03 (July 28, 2016); Org. of Econ. Co-Operation & Dev., Revision of the\nRecommendation of the Council Concerning Guidelines Governing the Protection of Privacy and Transborder\nFlows of Personal Data, Annex Part Two (June 20, 2013). https://one.oecd.org/document/C(2013)79/en/pdf.\n6. Andrew Wong et al. External validation of a widely implemented proprietary sepsis prediction model in\nhospitalized patients. JAMA Intern Med. 2021; 181(8):1065-1070. doi:10.1001/jamainternmed.2021.2626\n7. Jessica Guynn. Facebook while black: Users call it getting 'Zucked,' say talking about racism is censored as hate\nspeech. USA Today. Apr. 24, 2019. https://www.usatoday.com/story/news/2019/04/24/facebook-while-black\u00ad", "59cc349a-6628-4b71-8f4f-56af9bbddfdc": "Health and Human Services. \nPanelists: \n\u2022\nMark Schneider, Health Innovation Advisor, ChristianaCare\n\u2022\nZiad Obermeyer, Blue Cross of California Distinguished Associate Professor of Policy and Management,\nUniversity of California, Berkeley School of Public Health\n\u2022\nDorothy Roberts, George A. Weiss University Professor of Law and Sociology and the Raymond Pace and\nSadie Tanner Mossell Alexander Professor of Civil Rights, University of Pennsylvania\n\u2022\nDavid Jones, A. Bernard Ackerman Professor of the Culture of Medicine, Harvard University\n\u2022\nJamila Michener, Associate Professor of Government, Cornell University; Co-Director, Cornell Center for\nHealth Equity\u00ad\nPanelists discussed the impact of new technologies on health disparities; healthcare access, delivery, and \noutcomes; and areas ripe for research and policymaking. Panelists discussed the increasing importance of tech-\nnology as both a vehicle to deliver healthcare and a tool to enhance the quality of care. On the issue of", "ae1b2df2-0052-44c0-9465-17e88b67c991": "26 \nMAP 4.1: Approaches for mapping AI technology and legal risks of its components \u2013 including the use of third-party data or \nsoftware \u2013 are in place, followed, and documented, as are risks of infringement of a third-party\u2019s intellectual property or other \nrights. \nAction ID \nSuggested Action \nGAI Risks \nMP-4.1-001 Conduct periodic monitoring of AI-generated content for privacy risks; address any \npossible instances of PII or sensitive data exposure. \nData Privacy \nMP-4.1-002 Implement processes for responding to potential intellectual property infringement \nclaims or other rights. \nIntellectual Property \nMP-4.1-003 \nConnect new GAI policies, procedures, and processes to existing model, data, \nsoftware development, and IT governance and to legal, compliance, and risk \nmanagement activities. \nInformation Security; Data Privacy \nMP-4.1-004 Document training data curation policies, to the extent possible and according to \napplicable laws and policies. \nIntellectual Property; Data Privacy;", "69b93abd-4e87-4056-87c5-e5819c310f8e": "existing human performance considered as a performance baseline for the algorithm to meet pre-deployment, \nand as a lifecycle minimum performance standard. Decision possibilities resulting from performance testing \nshould include the possibility of not deploying the system. \nRisk identification and mitigation. Before deployment, and in a proactive and ongoing manner, poten\u00ad\ntial risks of the automated system should be identified and mitigated. Identified risks should focus on the \npotential for meaningful impact on people\u2019s rights, opportunities, or access and include those to impacted \ncommunities that may not be direct users of the automated system, risks resulting from purposeful misuse of \nthe system, and other concerns identified via the consultation process. Assessment and, where possible, mea\u00ad\nsurement of the impact of risks should be included and balanced such that high impact risks receive attention", "757f2dc8-3aa9-4e16-9c81-12c6b390f008": "23 \nMP-1.1-002 \nDetermine and document the expected and acceptable GAI system context of \nuse in collaboration with socio-cultural and other domain experts, by assessing: \nAssumptions and limitations; Direct value to the organization; Intended \noperational environment and observed usage patterns; Potential positive and \nnegative impacts to individuals, public safety, groups, communities, \norganizations, democratic institutions, and the physical environment; Social \nnorms and expectations. \nHarmful Bias and Homogenization \nMP-1.1-003 \nDocument risk measurement plans to address identi\ufb01ed risks. Plans may \ninclude, as applicable: Individual and group cognitive biases (e.g., con\ufb01rmation \nbias, funding bias, groupthink) for AI Actors involved in the design, \nimplementation, and use of GAI systems; Known past GAI system incidents and \nfailure modes; In-context use and foreseeable misuse, abuse, and o\ufb00-label use; \nOver reliance on quantitative metrics and methodologies without su\ufb03cient", "fc97d203-7885-4077-a742-eef7cbd16ef1": "NOTICE & \nEXPLANATION \nWHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\nThe expectations for automated systems are meant to serve as a blueprint for the development of additional \ntechnical standards and practices that are tailored for particular sectors and contexts. \nAn automated system should provide demonstrably clear, timely, understandable, and accessible notice of use, and \nexplanations as to how and why a decision was made or an action was taken by the system. These expectations are \nexplained below. \nProvide clear, timely, understandable, and accessible notice of use and explanations \u00ad\nGenerally accessible plain language documentation. The entity responsible for using the automated \nsystem should ensure that documentation describing the overall system (including any human components) is \npublic and easy to find. The documentation should describe, in plain language, how the system works and how", "b10395f5-dd7d-4bdd-8b79-b1049adaf1cc": "offline); families (construed broadly); people connected by affinity, identity, or shared traits; and formal organi-\nzational ties. This includes Tribes, Clans, Bands, Rancherias, Villages, and other Indigenous communities. AI \nand other data-driven automated systems most directly collect data on, make inferences about, and may cause \nharm to individuals. But the overall magnitude of their impacts may be most readily visible at the level of com-\nmunities. Accordingly, the concept of community is integral to the scope of the Blueprint for an AI Bill of Rights. \nUnited States law and policy have long employed approaches for protecting the rights of individuals, but exist-\ning frameworks have sometimes struggled to provide protections when effects manifest most clearly at a com-\nmunity level. For these reasons, the Blueprint for an AI Bill of Rights asserts that the harms of automated \nsystems should be evaluated, protected against, and redressed at both the individual and community levels.", "7b72f3dd-06a6-4760-ade3-b68fa700d859": "Confabulation; Information \nSecurity \nMS-4.2-003 \nImplement interpretability and explainability methods to evaluate GAI system \ndecisions and verify alignment with intended purpose. \nInformation Integrity; Harmful Bias \nand Homogenization \nMS-4.2-004 \nMonitor and document instances where human operators or other systems \noverride the GAI's decisions. Evaluate these cases to understand if the overrides \nare linked to issues related to content provenance. \nInformation Integrity \nMS-4.2-005 \nVerify and document the incorporation of results of structured public feedback \nexercises into design, implementation, deployment approval (\u201cgo\u201d/\u201cno-go\u201d \ndecisions), monitoring, and decommission decisions. \nHuman-AI Con\ufb01guration; \nInformation Security \nAI Actor Tasks: AI Deployment, Domain Experts, End-Users, Operation and Monitoring, TEVV", "fbc5530f-3dc1-4c5a-9119-a4b13018ba7d": "Connected Health Initiative \nConsumer Technology Association \nCourtney Radsch \nCoworker \nCyber Farm Labs \nData & Society Research Institute \nData for Black Lives \nData to Actionable Knowledge Lab \nat Harvard University \nDeloitte \nDev Technology Group \nDigital Therapeutics Alliance \nDigital Welfare State & Human \nRights Project and Center for \nHuman Rights and Global Justice at \nNew York University School of \nLaw, and Temple University \nInstitute for Law, Innovation & \nTechnology \nDignari \nDouglas Goddard \nEdgar Dworsky \nElectronic Frontier Foundation \nElectronic Privacy Information \nCenter, Center for Digital \nDemocracy, and Consumer \nFederation of America \nFaceTec \nFight for the Future \nGanesh Mani \nGeorgia Tech Research Institute \nGoogle \nHealth Information Technology \nResearch and Development \nInteragency Working Group \nHireVue \nHR Policy Association \nID.me \nIdentity and Data Sciences \nLaboratory at Science Applications \nInternational Corporation \nInformation Technology and \nInnovation Foundation", "403a6510-6af3-4ee5-bbbe-b97a65a94130": "https://arxiv.org/pdf/2305.17493v2 \nSmith, A. et al. (2023) Hallucination or Confabulation? Neuroanatomy as metaphor in Large Language \nModels. PLOS Digital Health. \nhttps://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000388 \nSoice, E. et al. (2023) Can large language models democratize access to dual-use biotechnology? arXiv. \nhttps://arxiv.org/abs/2306.03809 \nSolaiman, I. et al. (2023) The Gradient of Generative AI Release: Methods and Considerations. arXiv. \nhttps://arxiv.org/abs/2302.04844 \nStaab, R. et al. (2023) Beyond Memorization: Violating Privacy via Inference With Large Language \nModels. arXiv. https://arxiv.org/pdf/2310.07298 \nStanford, S. et al. (2023) Whose Opinions Do Language Models Re\ufb02ect? arXiv. \nhttps://arxiv.org/pdf/2303.17548 \nStrubell, E. et al. (2019) Energy and Policy Considerations for Deep Learning in NLP. arXiv. \nhttps://arxiv.org/pdf/1906.02243 \nThe White House (2016) Circular No. A-130, Managing Information as a Strategic Resource.", "fc60770b-eee5-46f9-aa49-803aa5ea6dfd": "conversations. 2019. https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification\n38. Lucas Dixon, John Li, Jeffrey Sorensen, Nithum Thain, and Lucy Vasserman. Measuring and\nMitigating Unintended Bias in Text Classification. Proceedings of AAAI/ACM Conference on AI, Ethics,\nand Society. Feb. 2-3, 2018. https://dl.acm.org/doi/pdf/10.1145/3278721.3278729\n39. Paresh Dave. Google cuts racy results by 30% for searches like 'Latina teenager'. Reuters. Mar. 30,\n2022. https://www.reuters.com/technology/google-cuts-racy-results-by-30-searches-like-latina\u00ad\nteenager-2022-03-30/\n40. Safiya Umoja Noble. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press.\nFeb. 2018. https://nyupress.org/9781479837243/algorithms-of-oppression/\n41. Paresh Dave. Google cuts racy results by 30% for searches like 'Latina teenager'. Reuters. Mar. 30,\n2022. https://www.reuters.com/technology/google-cuts-racy-results-by-30-searches-like-latina\u00ad\nteenager-2022-03-30/", "dba635cf-41a7-47e0-820b-1d2232b26d3e": "HUMAN ALTERNATIVES, \nCONSIDERATION, AND \nFALLBACK \nWHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\nThe expectations for automated systems are meant to serve as a blueprint for the development of additional \ntechnical standards and practices that are tailored for particular sectors and contexts. \nImplement additional human oversight and safeguards for automated systems related to \nsensitive domains \nAutomated systems used within sensitive domains, including criminal justice, employment, education, and \nhealth, should meet the expectations laid out throughout this framework, especially avoiding capricious, \ninappropriate, and discriminatory impacts of these technologies. Additionally, automated systems used within \nsensitive domains should meet these expectations: \nNarrowly scoped data and inferences. Human oversight should ensure that automated systems in \nsensitive domains are narrowly scoped to address a defined goal, justifying each included data item or attri\u00ad", "aa38da46-37c1-4f6e-b21d-0f01b6463f05": "provided instructions and material to complete tasks which may elicit harmful model behaviors. \nThis type of exercise can be more e\ufb00ective with large groups of AI red-teamers. \n\u2022 \nExpert: Performed by specialists with expertise in the domain or speci\ufb01c AI red-teaming context \nof use (e.g., medicine, biotech, cybersecurity).  \n\u2022 \nCombination: In scenarios when it is di\ufb03cult to identify and recruit specialists with su\ufb03cient \ndomain and contextual expertise, AI red-teaming exercises may leverage both expert and", "cf169e60-9a05-44b1-8364-9e7cefe6a856": "49 \nearly lifecycle TEVV approaches are developed and matured for GAI, organizations may use \nrecommended \u201cpre-deployment testing\u201d practices to measure performance, capabilities, limits, risks, \nand impacts. This section describes risk measurement and estimation as part of pre-deployment TEVV, \nand examines the state of play for pre-deployment testing methodologies.  \nLimitations of Current Pre-deployment Test Approaches \nCurrently available pre-deployment TEVV processes used for GAI applications may be inadequate, non-\nsystematically applied, or fail to re\ufb02ect or mismatched to deployment contexts. For example, the \nanecdotal testing of GAI system capabilities through video games or standardized tests designed for \nhumans (e.g., intelligence tests, professional licensing exams) does not guarantee GAI system validity or \nreliability in those domains. Similarly, jailbreaking or prompt engineering tests may not systematically \nassess validity or reliability risks.", "e188de33-eaa4-4379-ae37-a335ce7e69b7": "DATA PRIVACY \nHOW THESE PRINCIPLES CAN MOVE INTO PRACTICE\nReal-life examples of how these principles can become reality, through laws, policies, and practical \ntechnical and sociotechnical approaches to protecting rights, opportunities, and access. \nThe Privacy Act of 1974 requires privacy protections for personal information in federal \nrecords systems, including limits on data retention, and also provides individuals a general \nright to access and correct their data. Among other things, the Privacy Act limits the storage of individual \ninformation in federal systems of records, illustrating the principle of limiting the scope of data retention. Under \nthe Privacy Act, federal agencies may only retain data about an individual that is \u201crelevant and necessary\u201d to \naccomplish an agency\u2019s statutory purpose or to comply with an Executive Order of the President. The law allows", "032e77bb-7ee8-43a8-b13d-4f1aea5a1084": "data privacy violations, obscenity, extremism, violence, or CBRN information in \nsystem training data. \nData Privacy; Intellectual Property; \nObscene, Degrading, and/or \nAbusive Content; Harmful Bias and \nHomogenization; Dangerous, \nViolent, or Hateful Content; CBRN \nInformation or Capabilities \nMS-2.6-003 Re-evaluate safety features of \ufb01ne-tuned models when the negative risk exceeds \norganizational risk tolerance. \nDangerous, Violent, or Hateful \nContent \nMS-2.6-004 Review GAI system outputs for validity and safety: Review generated code to \nassess risks that may arise from unreliable downstream decision-making. \nValue Chain and Component \nIntegration; Dangerous, Violent, or \nHateful Content \nMS-2.6-005 \nVerify that GAI system architecture can monitor outputs and performance, and \nhandle, recover from, and repair errors when security anomalies, threats and \nimpacts are detected. \nConfabulation; Information \nIntegrity; Information Security \nMS-2.6-006", "8a259709-51c6-4a1a-bd12-461abc901ca1": "44 \nMG-3.2-007 \nLeverage feedback and recommendations from organizational boards or \ncommittees related to the deployment of GAI applications and content \nprovenance when using third-party pre-trained models. \nInformation Integrity; Value Chain \nand Component Integration \nMG-3.2-008 \nUse human moderation systems where appropriate to review generated content \nin accordance with human-AI con\ufb01guration policies established in the Govern \nfunction, aligned with socio-cultural norms in the context of use, and for settings \nwhere AI models are demonstrated to perform poorly. \nHuman-AI Con\ufb01guration \nMG-3.2-009 \nUse organizational risk tolerance to evaluate acceptable risks and performance \nmetrics and decommission or retrain pre-trained models that perform outside of \nde\ufb01ned limits. \nCBRN Information or Capabilities; \nConfabulation \nAI Actor Tasks: AI Deployment, Operation and Monitoring, Third-party entities", "18bfbbbc-c65e-4bb3-a596-44dd8f4584fd": "procedures for communicating incidents to relevant AI Actors and where \napplicable, relevant legal and regulatory bodies.  \nInformation Security \nMG-4.3-002 Establish and maintain policies and procedures to record and track GAI system \nreported errors, near-misses, and negative impacts. \nConfabulation; Information \nIntegrity", "b8198357-3185-41a6-a9b3-5f2d5839c91c": "43 \nMG-3.1-005 Review various transparency artifacts (e.g., system cards and model cards) for \nthird-party models. \nInformation Integrity; Information \nSecurity; Value Chain and \nComponent Integration \nAI Actor Tasks: AI Deployment, Operation and Monitoring, Third-party entities \n \nMANAGE 3.2: Pre-trained models which are used for development are monitored as part of AI system regular monitoring and \nmaintenance. \nAction ID \nSuggested Action \nGAI Risks \nMG-3.2-001 \nApply explainable AI (XAI) techniques (e.g., analysis of embeddings, model \ncompression/distillation, gradient-based attributions, occlusion/term reduction, \ncounterfactual prompts, word clouds) as part of ongoing continuous \nimprovement processes to mitigate risks related to unexplainable GAI systems. \nHarmful Bias and Homogenization \nMG-3.2-002 \nDocument how pre-trained models have been adapted (e.g., \ufb01ne-tuned, or \nretrieval-augmented generation) for the speci\ufb01c generative task, including any", "424352b3-190e-433d-89f6-beb5f2519530": "of the evaluation of their accessibility. For systems used in sensitive domains, reporting should include infor\u00ad\nmation about training and governance procedures for these technologies. Reporting should also include docu\u00ad\nmentation of goals and assessment of meeting those goals, consideration of data included, and documentation \nof the governance of reasonable access to the technology. Reporting should be provided in a clear and \nmachine-readable manner. \n51", "6b457a05-02a8-43a9-b7bd-39e2c396f577": "for GAI risk measurement. Address general risks associated with a lack of \nexplainability and transparency in GAI systems by using ample documentation and \ntechniques such as: application of gradient-based attributions, occlusion/term \nreduction, counterfactual prompts and prompt engineering, and analysis of \nembeddings; Assess and update risk measurement approaches at regular \ncadences. \nConfabulation \nGV-4.1-002 \nEstablish policies, procedures, and processes detailing risk measurement in \ncontext of use with standardized measurement protocols and structured public \nfeedback exercises such as AI red-teaming or independent external evaluations. \nCBRN Information and Capability; \nValue Chain and Component \nIntegration", "c62b39ff-7e0d-437c-a0cf-e5f30c3aabc7": "policing, health care, and the workplace disproportionately harm disabled people. Center for Democracy\nand Technology Report. May 24, 2022.\nhttps://cdt.org/insights/ableism-and-disability-discrimination-in-new-surveillance-technologies-how\u00ad\nnew-surveillance-technologies-in-education-policing-health-care-and-the-workplace\u00ad\ndisproportionately-harm-disabled-people/\n69", "4b37fe12-0be1-495d-bba0-f49ca7f5df94": "59 \nTirrell, L. (2017) Toxic Speech: Toward an Epidemiology of Discursive Harm. Philosophical Topics, 45(2), \n139-162. https://www.jstor.org/stable/26529441  \nTufekci, Z. (2015) Algorithmic Harms Beyond Facebook and Google: Emergent Challenges of \nComputational Agency. Colorado Technology Law Journal. https://ctlj.colorado.edu/wp-\ncontent/uploads/2015/08/Tufekci-\ufb01nal.pdf \nTurri, V. et al. (2023) Why We Need to Know More: Exploring the State of AI Incident Documentation \nPractices. AAAI/ACM Conference on AI, Ethics, and Society. \nhttps://dl.acm.org/doi/fullHtml/10.1145/3600211.3604700 \nUrbina, F. et al. (2022) Dual use of arti\ufb01cial-intelligence-powered drug discovery. Nature Machine \nIntelligence. https://www.nature.com/articles/s42256-022-00465-9 \nWang, X. et al. (2023) Energy and Carbon Considerations of Fine-Tuning BERT. ACL Anthology. \nhttps://aclanthology.org/2023.\ufb01ndings-emnlp.607.pdf \nWang, Y. et al. (2023) Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs. arXiv.", "6745762d-e5d8-458d-be17-641b6b4d516e": "the Joint Center for Political and Economic Studies, New America, the German Marshall Fund, the Electronic \nPrivacy Information Center, and the Mozilla Foundation. The purpose of these convenings \u2013 recordings of \nwhich are publicly available online112 \u2013 was to bring together a variety of experts, practitioners, advocates \nand federal government officials to offer insights and analysis on the risks, harms, benefits, and \npolicy opportunities of automated systems. Each panel discussion was organized around a wide-ranging \ntheme, exploring current challenges and concerns and considering what an automated society that \nrespects democratic values should look like. These discussions focused on the topics of consumer \nrights and protections, the criminal justice system, equal opportunities and civil justice, artificial \nintelligence and democratic values, social welfare and development, and the healthcare system. \nSummaries of Panel Discussions:", "56a48ef8-56cc-4d56-82a4-b0c6d34bab3d": "their automated technologies. For example, a collection of non-profit organizations and companies have \nworked together to develop a framework that defines operational approaches to transparency for machine \nlearning systems.88 This framework, and others like it,89 inform the public about the use of these tools, going \nbeyond simple notice to include reporting elements such as safety evaluations, disparity assessments, and \nexplanations of how the systems work. \nLenders are required by federal law to notify consumers about certain decisions made about \nthem. Both the Fair Credit Reporting Act and the Equal Credit Opportunity Act require in certain circumstances \nthat consumers who are denied credit receive \"adverse action\" notices. Anyone who relies on the information in a \ncredit report to deny a consumer credit must, under the Fair Credit Reporting Act, provide an \"adverse action\" \nnotice to the consumer, which includes \"notice of the reasons a creditor took adverse action on the application", "677e974b-bbd2-4dc0-be4a-146bbf69bcb2": "results, and actions taken; and the procedures for and results from independent evaluations. Reporting \nshould be provided in a plain language and machine-readable manner. \n20", "ad920bc1-0052-4c4f-bf89-3468cb95f316": "additionally wish to allocate risk management resources relative to the severity and likelihood of \nnegative impacts, including where and how these risks manifest, and their direct and material impacts \nharms in the context of GAI use. Mitigations for model or system level risks may di\ufb00er from mitigations \nfor use-case or ecosystem level risks. \nImportantly, some GAI risks are unknown, and are therefore di\ufb03cult to properly scope or evaluate given \nthe uncertainty about potential GAI scale, complexity, and capabilities. Other risks may be known but \ndi\ufb03cult to estimate given the wide range of GAI stakeholders, uses, inputs, and outputs. Challenges with \nrisk estimation are aggravated by a lack of visibility into GAI training data, and the generally immature \nstate of the science of AI measurement and safety today. This document focuses on risks for which there \nis an existing empirical evidence base at the time this pro\ufb01le was written; for example, speculative risks", "50e8d128-6b17-41b4-9e92-5de8e14f82c7": "employers to verify resume information, every former Apple employee\u2019s title gets erased and replaced with\na generic title. The Washington Post. Feb. 10, 2022.\nhttps://www.washingtonpost.com/technology/2022/02/10/apple-associate/\n78. National Institute of Standards and Technology. Privacy Framework Perspectives and Success\nStories. Accessed May 2, 2022.\nhttps://www.nist.gov/privacy-framework/getting-started-0/perspectives-and-success-stories\n79. ACLU of New York. What You Need to Know About New York\u2019s Temporary Ban on Facial\nRecognition in Schools. Accessed May 2, 2022.\nhttps://www.nyclu.org/en/publications/what-you-need-know-about-new-yorks-temporary-ban-facial\u00ad\nrecognition-schools\n80. New York State Assembly. Amendment to Education Law. Enacted Dec. 22, 2020.\nhttps://nyassembly.gov/leg/?default_fld=&leg_video=&bn=S05140&term=2019&Summary=Y&Text=Y\n81. U.S Department of Labor. Labor-Management Reporting and Disclosure Act of 1959, As Amended.", "22b8897a-4de2-4c91-bd41-9e32a6c4fdfe": "Disinformation and misinformation \u2013 both of which may be facilitated by GAI \u2013 may erode public trust in \ntrue or valid evidence and information, with downstream e\ufb00ects. For example, a synthetic image of a \nPentagon blast went viral and brie\ufb02y caused a drop in the stock market. Generative AI models can also \nassist malicious actors in creating compelling imagery and propaganda to support disinformation \ncampaigns, which may not be photorealistic, but could enable these campaigns to gain more reach and \nengagement on social media platforms. Additionally, generative AI models can assist malicious actors in \ncreating fraudulent content intended to impersonate others. \nTrustworthy AI Characteristics: Accountable and Transparent, Safe, Valid and Reliable, Interpretable and \nExplainable \n2.9. Information Security \nInformation security for computer systems and data is a mature \ufb01eld with widely accepted and \nstandardized practices for o\ufb00ensive and defensive cyber capabilities. GAI-based systems present two", "b3f535d6-c485-498c-8c1f-b421042bb5b4": "on people of conscience to act to preserve civil rights\u2014including the right to privacy, which he has called \u201cthe \nbasis for so many more rights that we have come to take for granted that are ingrained in the fabric of this \ncountry.\u201d2\nTo advance President Biden\u2019s vision, the White House Office of Science and Technology Policy has identified \nfive principles that should guide the design, use, and deployment of automated systems to protect the American \npublic in the age of artificial intelligence. The Blueprint for an AI Bill of Rights is a guide for a society that \nprotects all people from these threats\u2014and uses technologies in ways that reinforce our highest values. \nResponding to the experiences of the American public, and informed by insights from researchers, \ntechnologists, advocates, journalists, and policymakers, this framework is accompanied by a technical \ncompanion\u2014a handbook for anyone seeking to incorporate these protections into policy and practice, including", "d53154bd-1a82-4a47-9c10-600a528e532e": "Innovation Foundation \nInformation Technology Industry \nCouncil \nInnocence Project \nInstitute for Human-Centered \nArtificial Intelligence at Stanford \nUniversity \nIntegrated Justice Information \nSystems Institute \nInternational Association of Chiefs \nof Police \nInternational Biometrics + Identity \nAssociation \nInternational Business Machines \nCorporation \nInternational Committee of the Red \nCross \nInventionphysics \niProov \nJacob Boudreau \nJennifer K. Wagner, Dan Berger, \nMargaret Hu, and Sara Katsanis \nJonathan Barry-Blocker \nJoseph Turow \nJoy Buolamwini \nJoy Mack \nKaren Bureau \nLamont Gholston \nLawyers\u2019 Committee for Civil \nRights Under Law \n60", "6048d14c-7855-4647-b087-57ae0d713497": "describes three broad challenges for mitigating bias \u2013 datasets, testing and evaluation, and human factors \u2013 and \nintroduces preliminary guidance for addressing them. Throughout, the special publication takes a socio-\ntechnical perspective to identifying and managing AI bias. \n29\nAlgorithmic \nDiscrimination \nProtections", "bbba260e-ff51-4950-bfd6-f97904f8b366": "established, may also count as human subject experimentation, and require special review under organizational \ncompliance bodies applying medical, scientific, and academic human subject experimentation ethics rules and \ngovernance procedures. \nData quality. In sensitive domains, entities should be especially careful to maintain the quality of data to \navoid adverse consequences arising from decision-making based on flawed or inaccurate data. Such care is \nnecessary in a fragmented, complex data ecosystem and for datasets that have limited access such as for fraud \nprevention and law enforcement. It should be not left solely to individuals to carry the burden of reviewing and \ncorrecting data. Entities should conduct regular, independent audits and take prompt corrective measures to \nmaintain accurate, timely, and complete data. \nLimit access to sensitive data and derived data. Sensitive data and derived data should not be sold,", "9e642b01-e82f-4f7e-ab17-f89df81f45ed": "SECTION TITLE\nAPPENDIX\nListening to the American People \nThe White House Office of Science and Technology Policy (OSTP) led a yearlong process to seek and distill \ninput from people across the country \u2013 from impacted communities to industry stakeholders to \ntechnology developers to other experts across fields and sectors, as well as policymakers across the Federal \ngovernment \u2013 on the issue of algorithmic and data-driven harms and potential remedies. Through panel \ndiscussions, public listening sessions, private meetings, a formal request for information, and input to a \npublicly accessible and widely-publicized email address, people across the United States spoke up about \nboth the promises and potential harms of these technologies, and played a central role in shaping the \nBlueprint for an AI Bill of Rights. \nPanel Discussions to Inform the Blueprint for An AI Bill of Rights \nOSTP co-hosted a series of six panel discussions in collaboration with the Center for American Progress,", "4d8ac59c-02fb-403b-bfba-6d1c62c8513b": "\u2022 Change-management controls \n\u2022 Commercial use \n\u2022 Data provenance", "8ad112fa-a36b-4a31-aa34-22d98017a0bd": "them\n10. Samantha Cole. This Horrifying App Undresses a Photo of Any Woman With a Single Click. Motherboard.\nJune 26, 2019. https://www.vice.com/en/article/kzm59x/deepnude-app-creates-fake-nudes-of-any-woman\n11. Lauren Kaori Gurley. Amazon\u2019s AI Cameras Are Punishing Drivers for Mistakes They Didn\u2019t Make.\nMotherboard. Sep. 20, 2021. https://www.vice.com/en/article/88npjv/amazons-ai-cameras-are-punishing\u00ad\ndrivers-for-mistakes-they-didnt-make\n63", "491f5c27-32de-47cc-97aa-a62540e2c12a": "50 \nParticipatory Engagement Methods \nOn an ad hoc or more structured basis, organizations can design and use a variety of channels to engage \nexternal stakeholders in product development or review. Focus groups with select experts can provide \nfeedback on a range of issues. Small user studies can provide feedback from representative groups or \npopulations. Anonymous surveys can be used to poll or gauge reactions to speci\ufb01c features. Participatory \nengagement methods are often less structured than \ufb01eld testing or red teaming, and are more \ncommonly used in early stages of AI or product development.  \nField Testing \nField testing involves structured settings to evaluate risks and impacts and to simulate the conditions \nunder which the GAI system will be deployed. Field style tests can be adapted from a focus on user \npreferences and experiences towards AI risks and impacts \u2013 both negative and positive. When carried", "ef089202-5f7b-40dc-a4d3-19c9a7065d3d": "ENDNOTES\n107. Centers for Medicare & Medicaid Services. Biden-Harris Administration Quadruples the Number\nof Health Care Navigators Ahead of HealthCare.gov Open Enrollment Period. Aug. 27, 2021.\nhttps://www.cms.gov/newsroom/press-releases/biden-harris-administration-quadruples-number\u00ad\nhealth-care-navigators-ahead-healthcaregov-open\n108. See, e.g., McKinsey & Company. The State of Customer Care in 2022. July 8, 2022. https://\nwww.mckinsey.com/business-functions/operations/our-insights/the-state-of-customer-care-in-2022;\nSara Angeles. Customer Service Solutions for Small Businesses. Business News Daily.\nJun. 29, 2022. https://www.businessnewsdaily.com/7575-customer-service-solutions.html\n109. Mike Hughes. Are We Getting The Best Out Of Our Bots? Co-Intelligence Between Robots &\nHumans. Forbes. Jul. 14, 2022.\nhttps://www.forbes.com/sites/mikehughes1/2022/07/14/are-we-getting-the-best-out-of-our-bots-co\u00ad\nintelligence-between-robots--humans/?sh=16a2bd207395", "18a7df82-ff90-4408-a0ee-a2d91effd2a2": "could reduce environmental impacts at inference time, but training and tuning such models may still \ncontribute to their environmental impacts. Currently there is no agreed upon method to estimate \nenvironmental impacts from GAI.  \nTrustworthy AI Characteristics: Accountable and Transparent, Safe \n2.6. Harmful Bias and Homogenization \nBias exists in many forms and can become ingrained in automated systems. AI systems, including GAI \nsystems, can increase the speed and scale at which harmful biases manifest and are acted upon, \npotentially perpetuating and amplifying harms to individuals, groups, communities, organizations, and \nsociety. For example, when prompted to generate images of CEOs, doctors, lawyers, and judges, current \ntext-to-image models underrepresent women and/or racial minorities, and people with disabilities. \nImage generator models have also produced biased or stereotyped output for various demographic", "81cbeaae-c1fe-4914-aebd-a0670f500364": "SENSITIVE DOMAINS: \u201cSensitive domains\u201d are those in which activities being conducted can cause material \nharms, including significant adverse effects on human rights such as autonomy and dignity, as well as civil liber\u00ad\nties and civil rights. Domains that have historically been singled out as deserving of enhanced data protections \nor where such enhanced protections are reasonably expected by the public include, but are not limited to, \nhealth, family planning and care, employment, education, criminal justice, and personal finance. In the context \nof this framework, such domains are considered sensitive whether or not the specifics of a system context \nwould necessitate coverage under existing law, and domains and data that are considered sensitive are under\u00ad\nstood to change over time based on societal norms and context. \nSURVEILLANCE TECHNOLOGY: \u201cSurveillance technology\u201d refers to products or services marketed for", "10009fcf-4d1c-4343-948a-2ed6fd9bcc09": "33 \nMEASURE 2.7: AI system security and resilience \u2013 as identi\ufb01ed in the MAP function \u2013 are evaluated and documented. \nAction ID \nSuggested Action \nGAI Risks \nMS-2.7-001 \nApply established security measures to: Assess likelihood and magnitude of \nvulnerabilities and threats such as backdoors, compromised dependencies, data \nbreaches, eavesdropping, man-in-the-middle attacks, reverse engineering, \nautonomous agents, model theft or exposure of model weights, AI inference, \nbypass, extraction, and other baseline security concerns. \nData Privacy; Information Integrity; \nInformation Security; Value Chain \nand Component Integration \nMS-2.7-002 \nBenchmark GAI system security and resilience related to content provenance \nagainst industry standards and best practices. Compare GAI system security \nfeatures and content provenance methods against industry state-of-the-art. \nInformation Integrity; Information \nSecurity \nMS-2.7-003 \nConduct user surveys to gather user satisfaction with the AI-generated content", "6d448984-e848-470c-8ed7-a1a740d3544d": "APPENDIX\n\u2022\nJulia Simon-Mishel, Supervising Attorney, Philadelphia Legal Assistance\n\u2022\nDr. Zachary Mahafza, Research & Data Analyst, Southern Poverty Law Center\n\u2022\nJ. Khadijah Abdurahman, Tech Impact Network Research Fellow, AI Now Institute, UCLA C2I1, and\nUWA Law School\nPanelists separately described the increasing scope of technology use in providing for social welfare, including \nin fraud detection, digital ID systems, and other methods focused on improving efficiency and reducing cost. \nHowever, various panelists individually cautioned that these systems may reduce burden for government \nagencies by increasing the burden and agency of people using and interacting with these technologies. \nAdditionally, these systems can produce feedback loops and compounded harm, collecting data from \ncommunities and using it to reinforce inequality. Various panelists suggested that these harms could be \nmitigated by ensuring community input at the beginning of the design process, providing ways to opt out of", "2ff90b7e-f382-4179-9da8-628b5a1a1b92": "safe, secure, and resilient; (e) understandable; (f ) responsible and traceable; (g) regularly monitored; (h) transpar-\nent; and, (i) accountable. The Blueprint for an AI Bill of Rights is consistent with the Executive Order. \nAffected agencies across the federal government have released AI use case inventories13 and are implementing \nplans to bring those AI systems into compliance with the Executive Order or retire them. \nThe law and policy landscape for motor vehicles shows that strong safety regulations\u2014and \nmeasures to address harms when they occur\u2014can enhance innovation in the context of com-\nplex technologies. Cars, like automated digital systems, comprise a complex collection of components. \nThe National Highway Traffic Safety Administration,14 through its rigorous standards and independent \nevaluation, helps make sure vehicles on our roads are safe without limiting manufacturers\u2019 ability to \ninnovate.15 At the same time, rules of the road are implemented locally to impose contextually appropriate", "9f8f273e-5d23-4eb9-89b0-255c934e24af": "or \nbe designed to proactively protect you from harms \nimpacts of automated systems. You should be protected from inappropriate or irrelevant data use in the \ndesign, development, and deployment of automated systems, and from the compounded harm of its reuse. \nIndependent evaluation and reporting that confirms that the system is safe and effective, including reporting of \nsteps taken to mitigate potential harms, should be performed and the results made public whenever possible. \nALGORITHMIC DISCRIMINATION PROTECTIONS\nYou should not face discrimination by algorithms and systems should be used and designed in \nan equitable way. Algorithmic discrimination occurs when automated systems contribute to unjustified \ndifferent treatment or impacts disfavoring people based on their race, color, ethnicity, sex (including \npregnancy, childbirth, and related medical conditions, gender identity, intersex status, and sexual", "77cc9870-55ed-4598-9480-e11a183531a6": "BLUEPRINT FOR AN \nAI BILL OF \nRIGHTS \nMAKING AUTOMATED \nSYSTEMS WORK FOR \nTHE AMERICAN PEOPLE \nOCTOBER 2022", "34b4a549-0384-4808-966e-f713a6ea12ad": "applications of GAI. \nCBRN Information or \nCapabilities; Obscene, \nDegrading, and/or Abusive \nContent; Data Privacy; Civil \nRights violations \nAI Actor Tasks: AI Development, AI Deployment, Governance and Oversight", "d2512e2e-5c60-4d43-af2b-449ec03a2865": "dinary benefits, from technology that helps farmers grow food more efficiently and computers that predict storm \npaths, to algorithms that can identify diseases in patients. These tools now drive important decisions across \nsectors, while data is helping to revolutionize global industries. Fueled by the power of American innovation, \nthese tools hold the potential to redefine every part of our society and make life better for everyone. \nThis important progress must not come at the price of civil rights or democratic values, foundational American \nprinciples that President Biden has affirmed as a cornerstone of his Administration. On his first day in office, the \nPresident ordered the full Federal government to work to root out inequity, embed fairness in decision-\nmaking processes, and affirmatively advance civil rights, equal opportunity, and racial justice in America.1 The \nPresident has spoken forcefully about the urgent challenges posed to democracy today and has regularly called", "83aa9af9-6569-437e-af51-675af1d1e46e": "and data that are considered sensitive are understood to change over time based on societal norms and context. \n36", "c51b3f98-fc6a-430b-8e01-4248eccba989": "Provide timely human consideration and remedy by a fallback and escalation system in the \nevent that an automated system fails, produces error, or you would like to appeal or con\u00ad\ntest its impacts on you \nProportionate. The availability of human consideration and fallback, along with associated training and \nsafeguards against human bias, should be proportionate to the potential of the automated system to meaning\u00ad\nfully impact rights, opportunities, or access. Automated systems that have greater control over outcomes, \nprovide input to high-stakes decisions, relate to sensitive domains, or otherwise have a greater potential to \nmeaningfully impact rights, opportunities, or access should have greater availability (e.g., staffing) and over\u00ad\nsight of human consideration and fallback mechanisms. \nAccessible. Mechanisms for human consideration and fallback, whether in-person, on paper, by phone, or \notherwise provided, should be easy to find and use. These mechanisms should be tested to ensure that users", "1b44f9d8-f8e4-40fb-9dce-83baf7655bb3": "About AI at NIST: The National Institute of Standards and Technology (NIST) develops measurements, \ntechnology, tools, and standards to advance reliable, safe, transparent, explainable, privacy-enhanced, \nand fair arti\ufb01cial intelligence (AI) so that its full commercial and societal bene\ufb01ts can be realized without \nharm to people or the planet. NIST, which has conducted both fundamental and applied work on AI for \nmore than a decade, is also helping to ful\ufb01ll the 2023 Executive Order on Safe, Secure, and Trustworthy \nAI. NIST established the U.S. AI Safety Institute and the companion AI Safety Institute Consortium to \ncontinue the e\ufb00orts set in motion by the E.O. to build the science necessary for safe, secure, and \ntrustworthy development and use of AI. \nAcknowledgments: This report was accomplished with the many helpful comments and contributions \nfrom the community, including the NIST Generative AI Public Working Group, and NIST sta\ufb00 and guest", "427b5af4-e471-4ebd-8a89-da73e750b6d4": "Applying The Blueprint for an AI Bill of Rights \nSENSITIVE DATA: Data and metadata are sensitive if they pertain to an individual in a sensitive domain \n(defined below); are generated by technologies used in a sensitive domain; can be used to infer data from a \nsensitive domain or sensitive data about an individual (such as disability-related data, genomic data, biometric \ndata, behavioral data, geolocation data, data related to interaction with the criminal justice system, relationship \nhistory and legal status such as custody and divorce information, and home, work, or school environmental \ndata); or have the reasonable potential to be used in ways that are likely to expose individuals to meaningful \nharm, such as a loss of privacy or financial harm due to identity theft. Data and metadata generated by or about \nthose who are not yet legal adults is also sensitive, even if not related to a sensitive domain. Such data includes, \nbut is not limited to, numerical, text, image, audio, or video data.", "fbb4ec61-5d7a-469c-8266-667075da02ba": "ENDNOTES\n75. See., e.g., Sam Sabin. Digital surveillance in a post-Roe world. Politico. May 5, 2022. https://\nwww.politico.com/newsletters/digital-future-daily/2022/05/05/digital-surveillance-in-a-post-roe\u00ad\nworld-00030459; Federal Trade Commission. FTC Sues Kochava for Selling Data that Tracks People at\nReproductive Health Clinics, Places of Worship, and Other Sensitive Locations. Aug. 29, 2022. https://\nwww.ftc.gov/news-events/news/press-releases/2022/08/ftc-sues-kochava-selling-data-tracks-people\u00ad\nreproductive-health-clinics-places-worship-other\n76. Todd Feathers. This Private Equity Firm Is Amassing Companies That Collect Data on America\u2019s\nChildren. The Markup. Jan. 11, 2022.\nhttps://themarkup.org/machine-learning/2022/01/11/this-private-equity-firm-is-amassing-companies\u00ad\nthat-collect-data-on-americas-children\n77. Reed Albergotti. Every employee who leaves Apple becomes an \u2018associate\u2019: In job databases used by", "4a1f6a6c-b79b-4a2f-b298-a7261f617663": "licensed works, or personal, privileged, proprietary or sensitive data; Underlying \nfoundation models, versions of underlying models, and access modes. \nData Privacy; Human-AI \nCon\ufb01guration; Information \nIntegrity; Intellectual Property; \nValue Chain and Component \nIntegration \nAI Actor Tasks: Governance and Oversight", "9eef7ac9-2709-4532-bbf9-e0d3adbf40c5": "whether they are genuinely helpful in solving an identified problem. \nIn discussion of technical and governance interventions that that are needed to protect against the harms of \nthese technologies, panelists individually described the importance of: receiving community input into the \ndesign and use of technologies, public reporting on crucial elements of these systems, better notice and consent \nprocedures that ensure privacy based on context and use case, ability to opt-out of using these systems and \nreceive a fallback to a human process, providing explanations of decisions and how these systems work, the \nneed for governance including training in using these systems, ensuring the technological use cases are \ngenuinely related to the goal task and are locally validated to work, and the need for institution and protection \nof third party audits to ensure systems continue to be accountable and valid. \n57", "90eb2dd9-3186-4c57-bcae-574485a1be52": "4 \n1. CBRN Information or Capabilities: Eased access to or synthesis of materially nefarious \ninformation or design capabilities related to chemical, biological, radiological, or nuclear (CBRN) \nweapons or other dangerous materials or agents. \n2. Confabulation: The production of con\ufb01dently stated but erroneous or false content (known \ncolloquially as \u201challucinations\u201d or \u201cfabrications\u201d) by which users may be misled or deceived.6 \n3. Dangerous, Violent, or Hateful Content: Eased production of and access to violent, inciting, \nradicalizing, or threatening content as well as recommendations to carry out self-harm or \nconduct illegal activities. Includes di\ufb03culty controlling public exposure to hateful and disparaging \nor stereotyping content. \n4. Data Privacy: Impacts due to leakage and unauthorized use, disclosure, or de-anonymization of \nbiometric, health, location, or other personally identi\ufb01able information or sensitive data.7", "f46c1f82-6ce7-493e-b3e8-3d02f09a2bda": "6 \n2.2. Confabulation \n\u201cConfabulation\u201d refers to a phenomenon in which GAI systems generate and con\ufb01dently present \nerroneous or false content in response to prompts. Confabulations also include generated outputs that \ndiverge from the prompts or other input or that contradict previously generated statements in the same \ncontext. These phenomena are colloquially also referred to as \u201challucinations\u201d or \u201cfabrications.\u201d \nConfabulations can occur across GAI outputs and contexts.9,10 Confabulations are a natural result of the \nway generative models are designed: they generate outputs that approximate the statistical distribution \nof their training data; for example, LLMs predict the next token or word in a sentence or phrase. While \nsuch statistical prediction can produce factually accurate and consistent outputs, it can also produce \noutputs that are factually inaccurate or internally inconsistent. This dynamic is particularly relevant when", "dabf101d-f998-43b9-ad15-0a6933bde316": "20 \nGV-4.3-003 \nVerify information sharing and feedback mechanisms among individuals and \norganizations regarding any negative impact from GAI systems. \nInformation Integrity; Data \nPrivacy \nAI Actor Tasks: AI Impact Assessment, A\ufb00ected Individuals and Communities, Governance and Oversight \n \nGOVERN 5.1: Organizational policies and practices are in place to collect, consider, prioritize, and integrate feedback from those \nexternal to the team that developed or deployed the AI system regarding the potential individual and societal impacts related to AI \nrisks. \nAction ID \nSuggested Action \nGAI Risks \nGV-5.1-001 \nAllocate time and resources for outreach, feedback, and recourse processes in GAI \nsystem development. \nHuman-AI Con\ufb01guration; Harmful \nBias and Homogenization \nGV-5.1-002 \nDocument interactions with GAI systems to users prior to interactive activities, \nparticularly in contexts involving more signi\ufb01cant risks.  \nHuman-AI Con\ufb01guration; \nConfabulation", "74f049f0-a803-4a0c-80cf-58f96cc16b98": "to wait\u2014immediate human consideration and fallback should be available. In many time-critical systems, such a \nremedy is already immediately available, such as a building manager who can open a door in the case an automated \ncard access system fails. \nIn the criminal justice system, employment, education, healthcare, and other sensitive domains, automated systems \nare used for many purposes, from pre-trial risk assessments and parole decisions to technologies that help doctors \ndiagnose disease. Absent appropriate safeguards, these technologies can lead to unfair, inaccurate, or dangerous \noutcomes. These sensitive domains require extra protections. It is critically important that there is extensive human \noversight in such settings. \nThese critical protections have been adopted in some scenarios. Where automated systems have been introduced to \nprovide the public access to government benefits, existing human paper and phone-based processes are generally still", "02282833-7fe4-4b1a-aebf-3604b78c9e23": "managing-bias-arti\ufb01cial-intelligence \nNorthcutt, C. et al. (2021) Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks. \narXiv. https://arxiv.org/pdf/2103.14749 \nOECD (2023) \"Advancing accountability in AI: Governing and managing risks throughout the lifecycle for \ntrustworthy AI\", OECD Digital Economy Papers, No. 349, OECD Publishing, Paris. \nhttps://doi.org/10.1787/2448f04b-en \nOECD (2024) \"De\ufb01ning AI incidents and related terms\" OECD Arti\ufb01cial Intelligence Papers, No. 16, OECD \nPublishing, Paris. https://doi.org/10.1787/d1a8d965-en \nOpenAI (2023) GPT-4 System Card. https://cdn.openai.com/papers/gpt-4-system-card.pdf \nOpenAI (2024) GPT-4 Technical Report. https://arxiv.org/pdf/2303.08774 \nPadmakumar, V. et al. (2024) Does writing with language models reduce content diversity? ICLR. \nhttps://arxiv.org/pdf/2309.05196 \nPark, P. et. al. (2024) AI deception: A survey of examples, risks, and potential solutions. Patterns, 5(5). \narXiv. https://arxiv.org/pdf/2308.14752", "aac514f9-9cfd-4d14-8171-8d4c909cede1": "proof history of the content, promote transparency, and enable traceability. \nRobust version control systems can also be applied to track changes across the AI \nlifecycle over time. \nInformation Integrity \nMS-2.8-004 Verify adequacy of GAI system user instructions through user testing. \nHuman-AI Con\ufb01guration \nAI Actor Tasks: AI Deployment, AI Impact Assessment, Domain Experts, Operation and Monitoring, TEVV", "aebd3e65-e2da-4b5f-ad11-9d4a31881517": "Notice and explanations also serve an important safety and efficacy purpose, allowing experts to verify the reasonable\u00ad\nness of a recommendation before enacting it. \nIn order to guard against potential harms, the American public needs to know if an automated system is being used. \nClear, brief, and understandable notice is a prerequisite for achieving the other protections in this framework. Like\u00ad\nwise, the public is often unable to ascertain how or why an automated system has made a decision or contributed to a \nparticular outcome. The decision-making processes of automated systems tend to be opaque, complex, and, therefore, \nunaccountable, whether by design or by omission. These factors can make explanations both more challenging and \nmore important, and should not be used as a pretext to avoid explaining important decisions to the people impacted \nby those choices. In the context of automated systems, clear and valid explanations should be recognized as a baseline \nrequirement.", "d372d7d5-e676-451d-9c07-75dbecc3beb4": "DATA PRIVACY \nWHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\nThe expectations for automated systems are meant to serve as a blueprint for the development of additional \ntechnical standards and practices that are tailored for particular sectors and contexts. \nData access and correction. People whose data is collected, used, shared, or stored by automated \nsystems should be able to access data and metadata about themselves, know who has access to this data, and \nbe able to correct it if necessary. Entities should receive consent before sharing data with other entities and \nshould keep records of what data is shared and with whom. \nConsent withdrawal and data deletion. Entities should allow (to the extent legally permissible) with\u00ad\ndrawal of data access consent, resulting in the deletion of user data, metadata, and the timely removal of \ntheir data from any systems (e.g., machine learning models) derived from that data.68", "771dac26-6584-4f0b-bc14-a12c56cd48ea": "DATA PRIVACY \nEXTRA PROTECTIONS FOR DATA RELATED TO SENSITIVE\nDOMAINS\n\u2022\nContinuous positive airway pressure machines gather data for medical purposes, such as diagnosing sleep\napnea, and send usage data to a patient\u2019s insurance company, which may subsequently deny coverage for the\ndevice based on usage data. Patients were not aware that the data would be used in this way or monitored\nby anyone other than their doctor.70 \n\u2022\nA department store company used predictive analytics applied to collected consumer data to determine that a\nteenage girl was pregnant, and sent maternity clothing ads and other baby-related advertisements to her\nhouse, revealing to her father that she was pregnant.71\n\u2022\nSchool audio surveillance systems monitor student conversations to detect potential \"stress indicators\" as\na warning of potential violence.72 Online proctoring systems claim to detect if a student is cheating on an", "998558ef-dea7-4966-b3be-986e930153d1": "disabilities, voters with shorter or hyphenated names, and voters who have changed their name.97 A human\ncuring process,98 which helps voters to confirm their signatures and correct other voting mistakes, is\nimportant to ensure all votes are counted,99 and it is already standard practice in much of the country for\nboth an election official and the voter to have the opportunity to review and correct any such issues.100 \n47", "6d5fe8b5-2369-47c1-9bd6-5aa5d716523a": "due to identity theft. Data and metadata generated by or about those who are not yet legal adults is also sensitive, even \nif not related to a sensitive domain. Such data includes, but is not limited to, numerical, text, image, audio, or video \ndata. \u201cSensitive domains\u201d are those in which activities being conducted can cause material harms, including signifi\u00ad\ncant adverse effects on human rights such as autonomy and dignity, as well as civil liberties and civil rights. Domains \nthat have historically been singled out as deserving of enhanced data protections or where such enhanced protections \nare reasonably expected by the public include, but are not limited to, health, family planning and care, employment, \neducation, criminal justice, and personal finance. In the context of this framework, such domains are considered \nsensitive whether or not the specifics of a system context would necessitate coverage under existing law, and domains", "3c0b8e22-5102-47e7-b4a0-8252e2df10e3": "should not be used in education, work, housing, or in other contexts where the \nuse of such surveillance technologies is likely to limit rights, opportunities, or \naccess. Whenever possible, you should have access to reporting that confirms \nyour data decisions have been respected and provides an assessment of the \npotential impact of surveillance technologies on your rights, opportunities, or \naccess. \nDATA PRIVACY\n30", "da2d77db-b7d9-40d4-b923-2bb8dba6d444": "sex (LGBTQI+) persons; older adults; persons with disabilities; persons who live in rural areas; and persons \notherwise adversely affected by persistent poverty or inequality. Assessment could include both qualitative \nand quantitative evaluations of the system. This equity assessment should also be considered a core part of the \ngoals of the consultation conducted as part of the safety and efficacy review. \nRepresentative and robust data. Any data used as part of system development or assessment should be \nrepresentative of local communities based on the planned deployment setting and should be reviewed for bias \nbased on the historical and societal context of the data. Such data should be sufficiently robust to identify and \nhelp to mitigate biases and potential harms. \nGuarding against proxies.  Directly using demographic information in the design, development, or \ndeployment of an automated system (for purposes other than evaluating a system for discrimination or using", "868df082-6495-43dd-a3a9-a3989e022a35": "a reduced ability to use analytical reasoning.61 Documented patterns show that personal data is being aggregated by \ndata brokers to profile communities in harmful ways.62 The impact of all this data harvesting is corrosive, \nbreeding distrust, anxiety, and other mental health problems; chilling speech, protest, and worker organizing; and \nthreatening our democratic process.63 The American public should be protected from these growing risks. \nIncreasingly, some companies are taking these concerns seriously and integrating mechanisms to protect consumer \nprivacy into their products by design and by default, including by minimizing the data they collect, communicating \ncollection and use clearly, and improving security practices. Federal government surveillance and other collection and \nuse of data is governed by legal protections that help to protect civil liberties and provide for limits on data retention", "d40255dc-30f7-4d12-a137-356c9331d036": "counterfactual and low-context (e.g., \u201cleader,\u201d \u201cbad guys\u201d) prompts. For ML \npipelines or business processes with categorical or numeric outcomes that rely \non GAI, apply general fairness metrics (e.g., demographic parity, equalized odds, \nequal opportunity, statistical hypothesis tests), to the pipeline or business \noutcome where appropriate; Custom, context-speci\ufb01c metrics developed in \ncollaboration with domain experts and a\ufb00ected communities; Measurements of \nthe prevalence of denigration in generated content in deployment (e.g., sub-\nsampling a fraction of tra\ufb03c and manually annotating denigrating content). \nHarmful Bias and Homogenization; \nDangerous, Violent, or Hateful \nContent \nMS-2.11-003 \nIdentify the classes of individuals, groups, or environmental ecosystems which \nmight be impacted by GAI systems through direct engagement with potentially \nimpacted communities. \nEnvironmental; Harmful Bias and \nHomogenization \nMS-2.11-004", "dd4ef4a9-d623-4695-8648-6dc788ce570b": "could lead to negative psychological impacts. \nTrustworthy AI Characteristics: Accountable and Transparent, Explainable and Interpretable, Fair with \nHarmful Bias Managed, Privacy Enhanced, Safe, Valid and Reliable \n2.8. Information Integrity \nInformation integrity describes the \u201cspectrum of information and associated patterns of its creation, \nexchange, and consumption in society.\u201d High-integrity information can be trusted; \u201cdistinguishes fact \nfrom \ufb01ction, opinion, and inference; acknowledges uncertainties; and is transparent about its level of \nvetting. This information can be linked to the original source(s) with appropriate evidence. High-integrity \ninformation is also accurate and reliable, can be veri\ufb01ed and authenticated, has a clear chain of custody, \nand creates reasonable expectations about when its validity may expire.\u201d11 \n \n \n11 This de\ufb01nition of information integrity is derived from the 2022 White House Roadmap for Researchers on", "6c472ef1-8115-4732-a5dc-a39c15d5eb94": "inputs and content delivered through these plugins is often distributed, with inconsistent or insu\ufb03cient \naccess control. \nDocumentation practices including logging, recording, and analyzing GAI incidents can facilitate \nsmoother sharing of information with relevant AI Actors. Regular information sharing, change \nmanagement records, version history and metadata can also empower AI Actors responding to and \nmanaging AI incidents.", "f469924d-ea0b-4792-976b-4b057974feca": "assess validity or reliability risks.  \nMeasurement gaps can arise from mismatches between laboratory and real-world settings. Current \ntesting approaches often remain focused on laboratory conditions or restricted to benchmark test \ndatasets and in silico techniques that may not extrapolate well to\u2014or directly assess GAI impacts in real-\nworld conditions. For example, current measurement gaps for GAI make it di\ufb03cult to precisely estimate \nits potential ecosystem-level or longitudinal risks and related political, social, and economic impacts. \nGaps between benchmarks and real-world use of GAI systems may likely be exacerbated due to prompt \nsensitivity and broad heterogeneity of contexts of use. \nA.1.5. Structured Public Feedback \nStructured public feedback can be used to evaluate whether GAI systems are performing as intended \nand to calibrate and verify traditional measurement methods. Examples of structured feedback include, \nbut are not limited to: \n\u2022", "e072ffd2-a697-41f5-ae4b-0ee596f98d0a": "Information Integrity \nMS-3.3-003 \nEvaluate potential biases and stereotypes that could emerge from the AI-\ngenerated content using appropriate methodologies including computational \ntesting methods as well as evaluating structured feedback input. \nHarmful Bias and Homogenization", "c02ee20e-7730-4a17-ae99-3ef97db1ac6d": "out with large groups of users, these tests can provide estimations of the likelihood of risks and impacts \nin real world interactions. \nOrganizations may also collect feedback on outcomes, harms, and user experience directly from users in \nthe production environment after a model has been released, in accordance with human subject \nstandards such as informed consent and compensation. Organizations should follow applicable human \nsubjects research requirements, and best practices such as informed consent and subject compensation, \nwhen implementing feedback activities. \nAI Red-teaming \nAI red-teaming is an evolving practice that references exercises often conducted in a controlled \nenvironment and in collaboration with AI developers building AI models to identify potential adverse \nbehavior or outcomes of a GAI model or system, how they could occur, and stress test safeguards\u201d. AI \nred-teaming can be performed before or after AI models or systems are made available to the broader", "4c667dca-e6ab-4029-9e45-9e9f70dee4c1": "those used in public places or during protected activities like peaceful protests), social media  \n    monitoring, and ankle monitoring devices; \nVoting-related systems such as signature matching tools; \nSystems with a potential privacy impact such as smart home systems and associated data,  \n    systems that use or collect health-related data, systems that use or collect education-related  \n    data, criminal justice system data, ad-targeting systems, and systems that perform big data  \n    analytics in order to build profiles or infer personal information about individuals; and \nAny system that has the meaningful potential to lead to algorithmic discrimination. \n\u2022 Equal opportunities, including but not limited to:\nEducation-related systems such as algorithms that purport to detect student cheating or  \n    plagiarism, admissions algorithms, online or virtual reality student monitoring systems,  \nprojections of student progress or outcomes, algorithms that determine access to resources or", "b8c15525-e535-4798-9d4a-7c596b7a91d3": "Terminology of Attacks and Mitigations https://csrc.nist.gov/pubs/ai/100/2/e2023/\ufb01nal \nNational Institute of Standards and Technology (2023) AI Risk Management Framework. \nhttps://www.nist.gov/itl/ai-risk-management-framework \nNational Institute of Standards and Technology (2023) AI Risk Management Framework, Chapter 3: AI \nRisks and Trustworthiness. \nhttps://airc.nist.gov/AI_RMF_Knowledge_Base/AI_RMF/Foundational_Information/3-sec-characteristics \nNational Institute of Standards and Technology (2023) AI Risk Management Framework, Chapter 6: AI \nRMF Pro\ufb01les. https://airc.nist.gov/AI_RMF_Knowledge_Base/AI_RMF/Core_And_Pro\ufb01les/6-sec-pro\ufb01le \nNational Institute of Standards and Technology (2023) AI Risk Management Framework, Appendix A: \nDescriptions of AI Actor Tasks. \nhttps://airc.nist.gov/AI_RMF_Knowledge_Base/AI_RMF/Appendices/Appendix_A#:~:text=AI%20actors%\n20in%20this%20category,data%20providers%2C%20system%20funders%2C%20product", "ddd2f334-6ef8-42e7-9807-2ca32d1cfa58": "18 \nGOVERN 3.2: Policies and procedures are in place to de\ufb01ne and di\ufb00erentiate roles and responsibilities for human-AI con\ufb01gurations \nand oversight of AI systems. \nAction ID \nSuggested Action \nGAI Risks \nGV-3.2-001 \nPolicies are in place to bolster oversight of GAI systems with independent \nevaluations or assessments of GAI models or systems where the type and \nrobustness of evaluations are proportional to the identi\ufb01ed risks. \nCBRN Information or Capabilities; \nHarmful Bias and Homogenization \nGV-3.2-002 \nConsider adjustment of organizational roles and components across lifecycle \nstages of large or complex GAI systems, including: Test and evaluation, validation, \nand red-teaming of GAI systems; GAI content moderation; GAI system \ndevelopment and engineering; Increased accessibility of GAI tools, interfaces, and \nsystems, Incident response and containment. \nHuman-AI Con\ufb01guration; \nInformation Security; Harmful Bias \nand Homogenization \nGV-3.2-003", "2df14ea9-2d95-4d2a-a898-51924df1d539": "7 \nunethical behavior. Text-to-image models also make it easy to create images that could be used to \npromote dangerous or violent messages. Similar concerns are present for other GAI media, including \nvideo and audio. GAI may also produce content that recommends self-harm or criminal/illegal activities.  \nMany current systems restrict model outputs to limit certain content or in response to certain prompts, \nbut this approach may still produce harmful recommendations in response to other less-explicit, novel \nprompts (also relevant to CBRN Information or Capabilities, Data Privacy, Information Security, and \nObscene, Degrading and/or Abusive Content). Crafting such prompts deliberately is known as \n\u201cjailbreaking,\u201d or, manipulating prompts to circumvent output controls. Limitations of GAI systems can be \nharmful or dangerous in certain contexts. Studies have observed that users may disclose mental health", "9e6e5d45-3bc3-48da-b43d-f8038b9cde7b": "Suggested Action \nGAI Risks \nMG-3.1-001 \nApply organizational risk tolerances and controls (e.g., acquisition and \nprocurement processes; assessing personnel credentials and quali\ufb01cations, \nperforming background checks; \ufb01ltering GAI input and outputs, grounding, \ufb01ne \ntuning, retrieval-augmented generation) to third-party GAI resources: Apply \norganizational risk tolerance to the utilization of third-party datasets and other \nGAI resources; Apply organizational risk tolerances to \ufb01ne-tuned third-party \nmodels; Apply organizational risk tolerance to existing third-party models \nadapted to a new domain; Reassess risk measurements after \ufb01ne-tuning third-\nparty GAI models. \nValue Chain and Component \nIntegration; Intellectual Property \nMG-3.1-002 \nTest GAI system value chain risks (e.g., data poisoning, malware, other software \nand hardware vulnerabilities; labor practices; data privacy and localization \ncompliance; geopolitical alignment). \nData Privacy; Information Security; \nValue Chain and Component", "baca4be8-4a8b-4a79-9934-69c4047b87fb": "Priorities Related to Information Integrity Research and Development.", "39c0388e-6071-4e28-a76a-89954c7a76cd": "Capabilities \nGV-1.3-002 \nEstablish minimum thresholds for performance or assurance criteria and review as \npart of deployment approval (\u201cgo/\u201dno-go\u201d) policies, procedures, and processes, \nwith reviewed processes and approval thresholds re\ufb02ecting measurement of GAI \ncapabilities and risks. \nCBRN Information or Capabilities; \nConfabulation; Dangerous, \nViolent, or Hateful Content \nGV-1.3-003 \nEstablish a test plan and response policy, before developing highly capable models, \nto periodically evaluate whether the model may misuse CBRN information or \ncapabilities and/or o\ufb00ensive cyber capabilities. \nCBRN Information or Capabilities; \nInformation Security", "6616086f-0d37-4a95-8d4e-56b9a0c20ae7": "while simultaneously enhancing the security effectiveness capabilities of the existing technology. \n\u2022\nThe National Disabled Law Students Association expressed concerns that individuals with disabilities were\nmore likely to be flagged as potentially suspicious by remote proctoring AI systems because of their disabili-\nty-specific access needs such as needing longer breaks or using screen readers or dictation software.45 \n\u2022\nAn algorithm designed to identify patients with high needs for healthcare systematically assigned lower\nscores (indicating that they were not as high need) to Black patients than to those of white patients, even\nwhen those patients had similar numbers of chronic conditions and other markers of health.46 In addition,\nhealthcare clinical algorithms that are used by physicians to guide clinical decisions may include\nsociodemographic variables that adjust or \u201ccorrect\u201d the algorithm\u2019s output on the basis of a patient\u2019s race or\nethnicity, which can lead to race-based health inequities.47\n25", "c7489ca0-62a7-4494-9c38-dc8c208a5226": "MANAGE 2.4: Mechanisms are in place and applied, and responsibilities are assigned and understood, to supersede, disengage, or \ndeactivate AI systems that demonstrate performance or outcomes inconsistent with intended use. \nAction ID \nSuggested Action \nGAI Risks \nMG-2.4-001 \nEstablish and maintain communication plans to inform AI stakeholders as part of \nthe deactivation or disengagement process of a speci\ufb01c GAI system (including for \nopen-source models) or context of use, including reasons, workarounds, user \naccess removal, alternative processes, contact information, etc. \nHuman-AI Con\ufb01guration", "80737253-4302-451d-a2f5-0b3f5dd957e8": "that resulted in sensitive data leaks; the number, type, and outcomes of ethical pre-reviews undertaken; a \ndescription of any data sold, shared, or made public, and how that data was assessed to determine it did not pres-\nent a sensitive data risk; and ongoing risk identification and management procedures, and any mitigation added \nbased on these procedures. Reporting should be provided in a clear and machine-readable manner. \n38", "0dbf8ebc-7f28-4e8b-b047-5c5399e261da": "help assess the authenticity, integrity, intellectual property rights, and potential manipulations in digital \ncontent. Some well-known techniques for provenance data tracking include digital watermarking, \nmetadata recording, digital \ufb01ngerprinting, and human authentication, among others. \nProvenance Data Tracking Approaches \nProvenance data tracking techniques for GAI systems can be used to track the history and origin of data \ninputs, metadata, and synthetic content. Provenance data tracking records the origin and history for \ndigital content, allowing its authenticity to be determined. It consists of techniques to record metadata \nas well as overt and covert digital watermarks on content. Data provenance refers to tracking the origin \nand history of input data through metadata and digital watermarking techniques. Provenance data \ntracking processes can include and assist AI Actors across the lifecycle who may not have full visibility or", "73ffeb66-1a26-4495-82ee-3a48226ba7f9": "60 \nZhang, Y. et al. (2023) Human favoritism, not AI aversion: People\u2019s perceptions (and bias) toward \ngenerative AI, human experts, and human\u2013GAI collaboration in persuasive content generation. Judgment \nand Decision Making. https://www.cambridge.org/core/journals/judgment-and-decision-\nmaking/article/human-favoritism-not-ai-aversion-peoples-perceptions-and-bias-toward-generative-ai-\nhuman-experts-and-humangai-collaboration-in-persuasive-content-\ngeneration/419C4BD9CE82673EAF1D8F6C350C4FA8 \nZhang, Y. et al. (2023) Siren\u2019s Song in the AI Ocean: A Survey on Hallucination in Large Language Models. \narXiv. https://arxiv.org/pdf/2309.01219 \nZhao, X. et al. (2023) Provable Robust Watermarking for AI-Generated Text. Semantic Scholar. \nhttps://www.semanticscholar.org/paper/Provable-Robust-Watermarking-for-AI-Generated-Text-Zhao-\nAnanth/75b68d0903af9d9f6e47ce3cf7e1a7d27ec811dc", "b85154a6-7baf-4d71-a85b-7d5874470889": "NIST Trustworthy and Responsible AI  \nNIST AI 600-1 \nArtificial Intelligence Risk Management \nFramework: Generative Artificial \nIntelligence Profile \n \n \n \nThis publication is available free of charge from: \nhttps://doi.org/10.6028/NIST.AI.600-1", "7ff9ca89-d042-4d93-86ca-c819ce96f571": "2021. https://www.justice.gov/opa/pr/justice-department-announces-new-initiative-combat-redlining\n52. PAVE Interagency Task Force on Property Appraisal and Valuation Equity. Action Plan to Advance\nProperty Appraisal and Valuation Equity: Closing the Racial Wealth Gap by Addressing Mis-valuations for\nFamilies and Communities of Color. March 2022. https://pave.hud.gov/sites/pave.hud.gov/files/\ndocuments/PAVEActionPlan.pdf\n53. U.S. Equal Employment Opportunity Commission. The Americans with Disabilities Act and the Use of\nSoftware, Algorithms, and Artificial Intelligence to Assess Job Applicants and Employees. EEOC\u00ad\nNVTA-2022-2. May 12, 2022. https://www.eeoc.gov/laws/guidance/americans-disabilities-act-and-use\u00ad\nsoftware-algorithms-and-artificial-intelligence; U.S. Department of Justice. Algorithms, Artificial\nIntelligence, and Disability Discrimination in Hiring. May 12, 2022. https://beta.ada.gov/resources/ai\u00ad\nguidance/", "9ce6023d-f47a-4508-b851-7bc92ec92e5d": "Public and Private Sector Uses of Biometric Technologies. Issued Oct. 8, 2021.\nhttps://www.federalregister.gov/documents/2021/10/08/2021-21975/notice-of-request-for\u00ad\ninformation-rfi-on-public-and-private-sector-uses-of-biometric-technologies\n114. National Artificial Intelligence Initiative Office. Public Input on Public and Private Sector Uses of\nBiometric Technologies. Accessed Apr. 19, 2022.\nhttps://www.ai.gov/86-fr-56300-responses/\n115. Thomas D. Olszewski, Lisa M. Van Pay, Javier F. Ortiz, Sarah E. Swiersz, and Laurie A. Dacus.\nSynopsis of Responses to OSTP\u2019s Request for Information on the Use and Governance of Biometric\nTechnologies in the Public and Private Sectors. Science and Technology Policy Institute. Mar. 2022.\nhttps://www.ida.org/-/media/feature/publications/s/sy/synopsis-of-responses-to-request-for\u00ad\ninformation-on-the-use-and-governance-of-biometric-technologies/ida-document-d-33070.ashx\n73", "09e1411f-8588-40fa-9a33-66cb9e9a8933": "WHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\nThe expectations for automated systems are meant to serve as a blueprint for the development of additional \ntechnical standards and practices that are tailored for particular sectors and contexts. \nEnsuring accessibility during design, development, and deployment. Systems should be \ndesigned, developed, and deployed by organizations in ways that ensure accessibility to people with disabili\u00ad\nties. This should include consideration of a wide variety of disabilities, adherence to relevant accessibility \nstandards, and user experience research both before and after deployment to identify and address any accessi\u00ad\nbility barriers to the use or effectiveness of the automated system. \nDisparity assessment. Automated systems should be tested using a broad set of measures to assess wheth\u00ad\ner the system components, both in pre-deployment testing and in-context deployment, produce disparities.", "a1d58349-50d4-45c7-922b-3fb722db0852": "EQUITY: \u201cEquity\u201d means the consistent and systematic fair, just, and impartial treatment of all individuals. \nSystemic, fair, and just treatment must take into account the status of individuals who belong to underserved \ncommunities that have been denied such treatment, such as Black, Latino, and Indigenous and Native American \npersons, Asian Americans and Pacific Islanders and other persons of color; members of religious minorities; \nwomen, girls, and non-binary people; lesbian, gay, bisexual, transgender, queer, and intersex (LGBTQI+) \npersons; older adults; persons with disabilities; persons who live in rural areas; and persons otherwise adversely \naffected by persistent poverty or inequality. \nRIGHTS, OPPORTUNITIES, OR ACCESS: \u201cRights, opportunities, or access\u201d is used to indicate the scoping \nof this framework. It describes the set of: civil rights, civil liberties, and privacy, including freedom of speech,", "9414a260-83d0-4bdc-8083-68512cb56f75": "14 \nGOVERN 1.2: The characteristics of trustworthy AI are integrated into organizational policies, processes, procedures, and practices. \nAction ID \nSuggested Action \nGAI Risks \nGV-1.2-001 \nEstablish transparency policies and processes for documenting the origin and \nhistory of training data and generated data for GAI applications to advance digital \ncontent transparency, while balancing the proprietary nature of training \napproaches. \nData Privacy; Information \nIntegrity; Intellectual Property \nGV-1.2-002 \nEstablish policies to evaluate risk-relevant capabilities of GAI and robustness of \nsafety measures, both prior to deployment and on an ongoing basis, through \ninternal and external evaluations. \nCBRN Information or Capabilities; \nInformation Security \nAI Actor Tasks: Governance and Oversight \n \nGOVERN 1.3: Processes, procedures, and practices are in place to determine the needed level of risk management activities based \non the organization\u2019s risk tolerance. \nAction ID \nSuggested Action \nGAI Risks", "e2a000b0-29a7-49a1-9c87-de674486a78a": "Implementation Pathway. Jun. 2022. https://media.defense.gov/2022/Jun/22/2003022604/-1/-1/0/\nDepartment-of-Defense-Responsible-Artificial-Intelligence-Strategy-and-Implementation\u00ad\nPathway.PDF\n22. Director of National Intelligence. Principles of Artificial Intelligence Ethics for the Intelligence\nCommunity. https://www.dni.gov/index.php/features/2763-principles-of-artificial-intelligence-ethics-for\u00ad\nthe-intelligence-community\n64", "5f733903-c4f4-41c6-8410-033c4e6b3390": "https://cdt.org/insights/how-automated-test-proctoring-software-discriminates-against-disabled\u00ad\nstudents/\n46. Ziad Obermeyer, et al., Dissecting racial bias in an algorithm used to manage the health of\npopulations, 366 Science (2019), https://www.science.org/doi/10.1126/science.aax2342.\n66", "9278423d-7d2c-4d91-8e74-2ff10c9952b1": "requirements and best practices, and re\ufb02ects risk management priorities. Consistent with other AI RMF \npro\ufb01les, this pro\ufb01le o\ufb00ers insights into how risk can be managed across various stages of the AI lifecycle \nand for GAI as a technology.  \nAs GAI covers risks of models or applications that can be used across use cases or sectors, this document \nis an AI RMF cross-sectoral pro\ufb01le. Cross-sectoral pro\ufb01les can be used to govern, map, measure, and \nmanage risks associated with activities or business processes common across sectors, such as the use of \nlarge language models (LLMs), cloud-based services, or acquisition. \nThis document de\ufb01nes risks that are novel to or exacerbated by the use of GAI. After introducing and \ndescribing these risks, the document provides a set of suggested actions to help organizations govern, \nmap, measure, and manage these risks. \n \n \n1 EO 14110 de\ufb01nes Generative AI as \u201cthe class of AI models that emulate the structure and characteristics of input", "c8290368-e6cc-4c11-86e8-211b0f6ff429": "30 \nMEASURE 2.2: Evaluations involving human subjects meet applicable requirements (including human subject protection) and are \nrepresentative of the relevant population. \nAction ID \nSuggested Action \nGAI Risks \nMS-2.2-001 Assess and manage statistical biases related to GAI content provenance through \ntechniques such as re-sampling, re-weighting, or adversarial training. \nInformation Integrity; Information \nSecurity; Harmful Bias and \nHomogenization \nMS-2.2-002 \nDocument how content provenance data is tracked and how that data interacts \nwith privacy and security. Consider: Anonymizing data to protect the privacy of \nhuman subjects; Leveraging privacy output \ufb01lters; Removing any personally \nidenti\ufb01able information (PII) to prevent potential harm or misuse. \nData Privacy; Human AI \nCon\ufb01guration; Information \nIntegrity; Information Security; \nDangerous, Violent, or Hateful \nContent \nMS-2.2-003 Provide human subjects with options to withdraw participation or revoke their", "92689676-f99d-4f3a-aedb-82a851140cf7": "identified users, and impacted populations; the assessment of notice clarity and timeliness; the assessment of \nthe explanation's validity and accessibility; the assessment of the level of risk; and the account and assessment \nof how explanations are tailored, including to the purpose, the recipient of the explanation, and the level of \nrisk. Individualized profile information should be made readily available to the greatest extent possible that \nincludes explanations for any system impacts or inferences. Reporting should be provided in a clear plain \nlanguage and machine-readable manner. \n44", "1ef77bcd-1235-4349-a57f-76304c020694": "consortia have published principles and frameworks to guide the responsible use of automated systems; this \nframework provides a national values statement and toolkit that is sector-agnostic to inform building these \nprotections into policy, practice, or the technological design process.  Where existing law or policy\u2014such as \nsector-specific privacy laws and oversight requirements\u2014do not already provide guidance, the Blueprint for an \nAI Bill of Rights should be used to inform policy decisions.\nLISTENING TO THE AMERICAN PUBLIC\nThe White House Office of Science and Technology Policy has led a year-long process to seek and distill input \nfrom people across the country\u2014from impacted communities and industry stakeholders to technology develop-\ners and other experts across fields and sectors, as well as policymakers throughout the Federal government\u2014on \nthe issue of algorithmic and data-driven harms and potential remedies. Through panel discussions, public listen-", "2d23ffb7-65db-44d5-bb6b-31fffc00e7bc": "RIGHTS, OPPORTUNITIES, OR ACCESS\nCivil rights, civil liberties, and privacy, including freedom of speech, voting, and protections from discrimi\u00ad\nnation, excessive punishment, unlawful surveillance, and violations of privacy and other freedoms in both \npublic and private sector contexts; \nEqual opportunities, including equitable access to education, housing, credit, employment, and other \nprograms; or, \nAccess to critical resources or services, such as healthcare, financial services, safety, social services, \nnon-deceptive information about goods and services, and government benefits. \nA list of examples of automated systems for which these principles should be considered is provided in the \nAppendix. The Technical Companion, which follows, offers supportive guidance for any person or entity that \ncreates, deploys, or oversees automated systems. \nConsidered together, the five principles and associated practices of the Blueprint for an AI Bill of", "47d45fac-167f-4abe-85ba-c592dfc54e76": "31 \nMS-2.3-004 \nUtilize a purpose-built testing environment such as NIST Dioptra to empirically \nevaluate GAI trustworthy characteristics. \nCBRN Information or Capabilities; \nData Privacy; Confabulation; \nInformation Integrity; Information \nSecurity; Dangerous, Violent, or \nHateful Content; Harmful Bias and \nHomogenization \nAI Actor Tasks: AI Deployment, TEVV \n \nMEASURE 2.5: The AI system to be deployed is demonstrated to be valid and reliable. Limitations of the generalizability beyond the \nconditions under which the technology was developed are documented. \nAction ID \nSuggested Action \nRisks \nMS-2.5-001 Avoid extrapolating GAI system performance or capabilities from narrow, non-\nsystematic, and anecdotal assessments. \nHuman-AI Con\ufb01guration; \nConfabulation \nMS-2.5-002 \nDocument the extent to which human domain knowledge is employed to \nimprove GAI system performance, via, e.g., RLHF, \ufb01ne-tuning, retrieval-\naugmented generation, content moderation, business rules. \nHuman-AI Con\ufb01guration", "ba676a38-8c2d-4a8d-9b84-d5dc34be9ad5": "control over the various trade-o\ufb00s and cascading impacts of early-stage model decisions on downstream \nperformance and synthetic outputs. For example, by selecting a watermarking model to prioritize \nrobustness (the durability of a watermark), an AI actor may inadvertently diminish computational \ncomplexity (the resources required to implement watermarking). Organizational risk management \ne\ufb00orts for enhancing content provenance include:  \n\u2022 \nTracking provenance of training data and metadata for GAI systems; \n\u2022 \nDocumenting provenance data limitations within GAI systems;", "f5b7c80b-9987-4c1a-90b7-40725e445d68": "Shared Statement Of Civil Rights Concerns. Jul. 30, 2018. http://civilrightsdocs.info/pdf/criminal-justice/\nPretrial-Risk-Assessment-Short.pdf; https://civilrights.org/edfund/pretrial-risk-assessments/\n29. Idaho Legislature. House Bill 118. Jul. 1, 2019. https://legislature.idaho.gov/sessioninfo/2019/\nlegislation/H0118/\n30. See, e.g., Executive Office of the President. Big Data: A Report on Algorithmic Systems, Opportunity, and\nCivil Rights. May, 2016. https://obamawhitehouse.archives.gov/sites/default/files/microsites/\nostp/2016_0504_data_discrimination.pdf; Cathy O\u2019Neil. Weapons of Math Destruction. Penguin Books.\n2017. https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction; Ruha Benjamin. Race After\nTechnology: Abolitionist Tools for the New Jim Code. Polity. 2019. https://www.ruhabenjamin.com/race\u00ad\nafter-technology\n31. See, e.g., Kashmir Hill. Another Arrest, and Jail Time, Due to a Bad Facial Recognition Match: A New", "1ad6e133-af0d-462b-8fcf-c037919602b6": "who have trouble with the automated system are able to use human consideration and fallback, with the under\u00ad\nstanding that it may be these users who are most likely to need the human assistance. Similarly, it should be \ntested to ensure that users with disabilities are able to find and use human consideration and fallback and also \nrequest reasonable accommodations or modifications. \nConvenient. Mechanisms for human consideration and fallback should not be unreasonably burdensome as \ncompared to the automated system\u2019s equivalent. \n49", "3c014cdb-93a6-4ced-a0b2-4da9ff5e1441": "Integrity; Information Security \nMS-2.6-006 \nVerify that systems properly handle queries that may give rise to inappropriate, \nmalicious, or illegal usage, including facilitating manipulation, extortion, targeted \nimpersonation, cyber-attacks, and weapons creation. \nCBRN Information or Capabilities; \nInformation Security \nMS-2.6-007 Regularly evaluate GAI system vulnerabilities to possible circumvention of safety \nmeasures.  \nCBRN Information or Capabilities; \nInformation Security \nAI Actor Tasks: AI Deployment, AI Impact Assessment, Domain Experts, Operation and Monitoring, TEVV", "cf73a083-880a-4afc-86b6-5667ae73d419": "where possible, available before the harm occurs. Time-critical systems include, but are not limited to, \nvoting-related systems, automated building access and other access systems, systems that form a critical \ncomponent of healthcare, and systems that have the ability to withhold wages or otherwise cause \nimmediate financial penalties. \nEffective. The organizational structure surrounding processes for consideration and fallback should \nbe designed so that if the human decision-maker charged with reassessing a decision determines that it \nshould be overruled, the new decision will be effectively enacted. This includes ensuring that the new \ndecision is entered into the automated system throughout its components, any previous repercussions from \nthe old decision are also overturned, and safeguards are put in place to help ensure that future decisions do \nnot result in the same errors. \nMaintained. The human consideration and fallback process and any associated automated processes", "cb37af2e-5517-4a81-8049-07d3d61ad295": "Information Integrity; Value Chain \nand Component Integration \nGV-6.1-004 \nDraft and maintain well-de\ufb01ned contracts and service level agreements (SLAs) \nthat specify content ownership, usage rights, quality standards, security \nrequirements, and content provenance expectations for GAI systems. \nInformation Integrity; Information \nSecurity; Intellectual Property", "2183508f-9a9e-41b1-a517-f2fc17931b63": "27 \nMP-4.1-010 \nConduct appropriate diligence on training data use to assess intellectual property, \nand privacy, risks, including to examine whether use of proprietary or sensitive \ntraining data is consistent with applicable laws.  \nIntellectual Property; Data Privacy \nAI Actor Tasks: Governance and Oversight, Operation and Monitoring, Procurement, Third-party entities \n \nMAP 5.1: Likelihood and magnitude of each identi\ufb01ed impact (both potentially bene\ufb01cial and harmful) based on expected use, past \nuses of AI systems in similar contexts, public incident reports, feedback from those external to the team that developed or deployed \nthe AI system, or other data are identi\ufb01ed and documented. \nAction ID \nSuggested Action \nGAI Risks \nMP-5.1-001 Apply TEVV practices for content provenance (e.g., probing a system's synthetic \ndata generation capabilities for potential misuse or vulnerabilities. \nInformation Integrity; Information \nSecurity \nMP-5.1-002", "39d7af6a-7298-47bc-a608-55c4a9d09d31": "security, health, foreign relations, the environment, and the technological recovery and use of resources, among \nother topics. OSTP leads interagency science and technology policy coordination efforts, assists the Office of \nManagement and Budget (OMB) with an annual review and analysis of Federal research and development in \nbudgets, and serves as a source of scientific and technological analysis and judgment for the President with \nrespect to major policies, plans, and programs of the Federal Government. \nLegal Disclaimer \nThe Blueprint for an AI Bill of Rights: Making Automated Systems Work for the American People is a white paper \npublished by the White House Office of Science and Technology Policy. It is intended to support the \ndevelopment of policies and practices that protect civil rights and promote democratic values in the building, \ndeployment, and governance of automated systems. \nThe Blueprint for an AI Bill of Rights is non-binding and does not constitute U.S. government policy. It", "7ee6f299-9e32-45b6-8a95-f63af7ab302d": "8 \nTrustworthy AI Characteristics: Accountable and Transparent, Privacy Enhanced, Safe, Secure and \nResilient \n2.5. Environmental Impacts \nTraining, maintaining, and operating (running inference on) GAI systems are resource-intensive activities, \nwith potentially large energy and environmental footprints. Energy and carbon emissions vary based on \nwhat is being done with the GAI model (i.e., pre-training, \ufb01ne-tuning, inference), the modality of the \ncontent, hardware used, and type of task or application. \nCurrent estimates suggest that training a single transformer LLM can emit as much carbon as 300 round-\ntrip \ufb02ights between San Francisco and New York. In a study comparing energy consumption and carbon \nemissions for LLM inference, generative tasks (e.g., text summarization) were found to be more energy- \nand carbon-intensive than discriminative or non-generative tasks (e.g., text classi\ufb01cation).  \nMethods for creating smaller versions of trained models, such as model distillation or compression,", "56387bf7-3970-47f2-a78c-1d685ff6ff3c": "these technologies, various panelists emphasized that transparency is important but is not enough to achieve \naccountability. Some panelists discussed their individual views on additional system needs for validity, and \nagreed upon the importance of advisory boards and compensated community input early in the design process \n(before the technology is built and instituted). Various panelists also emphasized the importance of regulation \nthat includes limits to the type and cost of such technologies. \n56", "9d4dae2d-1304-42fd-853c-5e8a87dfd8ca": "MANAGE 4.1: Post-deployment AI system monitoring plans are implemented, including mechanisms for capturing and evaluating \ninput from users and other relevant AI Actors, appeal and override, decommissioning, incident response, recovery, and change \nmanagement. \nAction ID \nSuggested Action \nGAI Risks \nMG-4.1-001 \nCollaborate with external researchers, industry experts, and community \nrepresentatives to maintain awareness of emerging best practices and \ntechnologies in measuring and managing identi\ufb01ed risks. \nInformation Integrity; Harmful Bias \nand Homogenization \nMG-4.1-002 \nEstablish, maintain, and evaluate e\ufb00ectiveness of organizational processes and \nprocedures for post-deployment monitoring of GAI systems, particularly for \npotential confabulation, CBRN, or cyber risks. \nCBRN Information or Capabilities; \nConfabulation; Information \nSecurity \nMG-4.1-003 \nEvaluate the use of sentiment analysis to gauge user sentiment regarding GAI", "225dc155-5855-48c7-8617-a254366cfdbd": "against Black patients, who generally have less access to medical care and therefore have generated less cost \nthan white patients with similar illness and need. A landmark study documented this pattern and proposed \npractical ways that were shown to reduce this bias, such as focusing specifically on active chronic health \nconditions or avoidable future costs related to emergency visits and hospitalization.54 \nLarge employers have developed best practices to scrutinize the data and models used \nfor hiring. An industry initiative has developed Algorithmic Bias Safeguards for the Workforce, a structured \nquestionnaire that businesses can use proactively when procuring software to evaluate workers. It covers \nspecific technical questions such as the training data used, model training process, biases identified, and \nmitigation steps employed.55 \nStandards organizations have developed guidelines to incorporate accessibility criteria", "4b9f6363-19fe-4e5d-b658-d8ffcacc03d5": "arXiv. https://arxiv.org/pdf/2308.14752 \nPartnership on AI (2023) Building a Glossary for Synthetic Media Transparency Methods, Part 1: Indirect \nDisclosure. https://partnershiponai.org/glossary-for-synthetic-media-transparency-methods-part-1-\nindirect-disclosure/ \nQu, Y. et al. (2023) Unsafe Di\ufb00usion: On the Generation of Unsafe Images and Hateful Memes From Text-\nTo-Image Models. arXiv. https://arxiv.org/pdf/2305.13873 \nRafat, K. et al. (2023) Mitigating carbon footprint for knowledge distillation based deep learning model \ncompression. PLOS One. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0285668 \nSaid, I. et al. (2022) Nonconsensual Distribution of Intimate Images: Exploring the Role of Legal Attitudes \nin Victimization and Perpetration. Sage. \nhttps://journals.sagepub.com/doi/full/10.1177/08862605221122834#bibr47-08862605221122834 \nSandbrink, J. (2023) Arti\ufb01cial intelligence and biological misuse: Di\ufb00erentiating risks of language models", "f3b2640d-2aa6-4a43-bed5-77c9f7e3d4a5": "narrowly defined contexts with clear benefits to the individual and/or society. \nTo this end, automated systems that collect, use, share, or store data related to these sensitive domains should meet \nadditional expectations. Data and metadata are sensitive if they pertain to an individual in a sensitive domain (defined \nbelow); are generated by technologies used in a sensitive domain; can be used to infer data from a sensitive domain or \nsensitive data about an individual (such as disability-related data, genomic data, biometric data, behavioral data, \ngeolocation data, data related to interaction with the criminal justice system, relationship history and legal status such \nas custody and divorce information, and home, work, or school environmental data); or have the reasonable potential \nto be used in ways that are likely to expose individuals to meaningful harm, such as a loss of privacy or financial harm", "1509d387-1fa9-4049-ade6-b412686b43fd": "39 \nMS-3.3-004 \nProvide input for training materials about the capabilities and limitations of GAI \nsystems related to digital content transparency for AI Actors, other \nprofessionals, and the public about the societal impacts of AI and the role of \ndiverse and inclusive content generation. \nHuman-AI Con\ufb01guration; \nInformation Integrity; Harmful Bias \nand Homogenization \nMS-3.3-005 \nRecord and integrate structured feedback about content provenance from \noperators, users, and potentially impacted communities through the use of \nmethods such as user research studies, focus groups, or community forums. \nActively seek feedback on generated content quality and potential biases. \nAssess the general awareness among end users and impacted communities \nabout the availability of these feedback channels. \nHuman-AI Con\ufb01guration; \nInformation Integrity; Harmful Bias \nand Homogenization \nAI Actor Tasks: AI Deployment, A\ufb00ected Individuals and Communities, End-Users, Operation and Monitoring, TEVV", "66b30463-4011-43f5-8112-826208de6c25": "DATA PRIVACY \nWHY THIS PRINCIPLE IS IMPORTANT\nThis section provides a brief summary of the problems which the principle seeks to address and protect \nagainst, including illustrative examples. \n\u2022\nAn insurer might collect data from a person's social media presence as part of deciding what life\ninsurance rates they should be offered.64\n\u2022\nA data broker harvested large amounts of personal data and then suffered a breach, exposing hundreds of\nthousands of people to potential identity theft. 65\n\u2022\nA local public housing authority installed a facial recognition system at the entrance to housing complexes to\nassist law enforcement with identifying individuals viewed via camera when police reports are filed, leading\nthe community, both those living in the housing complex and not, to have videos of them sent to the local\npolice department and made available for scanning by its facial recognition software.66\n\u2022\nCompanies use surveillance software to track employee discussions about union activity and use the", "182ea1c4-9823-4498-8afb-5fed66f8afa4": "A.1.3. Third-Party Considerations \nOrganizations may seek to acquire, embed, incorporate, or use open-source or proprietary third-party \nGAI models, systems, or generated data for various applications across an enterprise. Use of these GAI \ntools and inputs has implications for all functions of the organization \u2013 including but not limited to \nacquisition, human resources, legal, compliance, and IT services \u2013 regardless of whether they are carried \nout by employees or third parties. Many of the actions cited above are relevant and options for \naddressing third-party considerations. \nThird party GAI integrations may give rise to increased intellectual property, data privacy, or information \nsecurity risks, pointing to the need for clear guidelines for transparency and risk management regarding \nthe collection and use of third-party data for model inputs. Organizations may consider varying risk \ncontrols for foundation models, \ufb01ne-tuned models, and embedded tools, enhanced processes for", "4fa78531-4c21-4163-9d75-1fbae52d1d1e": "was demanded and produced.86 The lack of an explanation made it harder for errors to be corrected in a\ntimely manner.\n42", "dae39aa6-9cbc-4da4-8222-ceafa8a0a43d": "in\ufb02uence-humans-too/ \nEpstein, Z. et al. (2023). Art and the science of generative AI. Science. \nhttps://www.science.org/doi/10.1126/science.adh4451 \nFe\ufb00er, M. et al. (2024) Red-Teaming for Generative AI: Silver Bullet or Security Theater? arXiv. \nhttps://arxiv.org/pdf/2401.15897 \nGlazunov, S. et al. (2024) Project Naptime: Evaluating O\ufb00ensive Security Capabilities of Large Language \nModels. Project Zero. https://googleprojectzero.blogspot.com/2024/06/project-naptime.html \nGreshake, K. et al. (2023) Not what you've signed up for: Compromising Real-World LLM-Integrated \nApplications with Indirect Prompt Injection. arXiv. https://arxiv.org/abs/2302.12173 \nHagan, M. (2024) Good AI Legal Help, Bad AI Legal Help: Establishing quality standards for responses to \npeople\u2019s legal problem stories. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4696936 \nHaran, R. (2023) Securing LLM Systems Against Prompt Injection. NVIDIA. \nhttps://developer.nvidia.com/blog/securing-llm-systems-against-prompt-injection/", "33c2c28e-8966-4c61-8bd6-cc54ebe272fd": "45 \nMG-4.1-007 \nVerify that AI Actors responsible for monitoring reported issues can e\ufb00ectively \nevaluate GAI system performance including the application of content \nprovenance data tracking techniques, and promptly escalate issues for response. \nHuman-AI Con\ufb01guration; \nInformation Integrity \nAI Actor Tasks: AI Deployment, A\ufb00ected Individuals and Communities, Domain Experts, End-Users, Human Factors, Operation and \nMonitoring \n \nMANAGE 4.2: Measurable activities for continual improvements are integrated into AI system updates and include regular \nengagement with interested parties, including relevant AI Actors. \nAction ID \nSuggested Action \nGAI Risks \nMG-4.2-001 Conduct regular monitoring of GAI systems and publish reports detailing the \nperformance, feedback received, and improvements made. \nHarmful Bias and Homogenization \nMG-4.2-002 \nPractice and follow incident response plans for addressing the generation of \ninappropriate or harmful content and adapt processes based on \ufb01ndings to", "f926ae48-8dda-479c-9348-124b494c0446": "21 \nGV-6.1-005 \nImplement a use-cased based supplier risk assessment framework to evaluate and \nmonitor third-party entities\u2019 performance and adherence to content provenance \nstandards and technologies to detect anomalies and unauthorized changes; \nservices acquisition and value chain risk management; and legal compliance. \nData Privacy; Information \nIntegrity; Information Security; \nIntellectual Property; Value Chain \nand Component Integration \nGV-6.1-006 Include clauses in contracts which allow an organization to evaluate third-party \nGAI processes and standards.  \nInformation Integrity \nGV-6.1-007 Inventory all third-party entities with access to organizational content and \nestablish approved GAI technology and service provider lists. \nValue Chain and Component \nIntegration \nGV-6.1-008 Maintain records of changes to content made by third parties to promote content \nprovenance, including sources, timestamps, metadata. \nInformation Integrity; Value Chain \nand Component Integration; \nIntellectual Property", "ad86da1d-b377-4e66-ae6e-bf0697f3c5ca": "consent for present or future use of their data in GAI applications.  \nData Privacy; Human-AI \nCon\ufb01guration; Information \nIntegrity \nMS-2.2-004 \nUse techniques such as anonymization, di\ufb00erential privacy or other privacy-\nenhancing technologies to minimize the risks associated with linking AI-generated \ncontent back to individual human subjects. \nData Privacy; Human-AI \nCon\ufb01guration \nAI Actor Tasks: AI Development, Human Factors, TEVV \n \nMEASURE 2.3: AI system performance or assurance criteria are measured qualitatively or quantitatively and demonstrated for \nconditions similar to deployment setting(s). Measures are documented. \nAction ID \nSuggested Action \nGAI Risks \nMS-2.3-001 Consider baseline model performance on suites of benchmarks when selecting a \nmodel for \ufb01ne tuning or enhancement with retrieval-augmented generation. \nInformation Security; \nConfabulation \nMS-2.3-002 Evaluate claims of model capabilities using empirically validated methods. \nConfabulation; Information \nSecurity", "b10e392b-f29b-4aa9-a4d6-339ee55d6518": "Data Privacy; Intellectual \nProperty", "6f6d8ce3-01ef-4bfa-a9e1-20c5125a338a": "or on an existing credit account.\"90 In addition, under the risk-based pricing rule,91 lenders must either inform \nborrowers of their credit score, or else tell consumers when \"they are getting worse terms because of \ninformation in their credit report.\" The CFPB has also asserted that \"[t]he law gives every applicant the right to \na specific explanation if their application for credit was denied, and that right is not diminished simply because \na company uses a complex algorithm that it doesn't understand.\"92 Such explanations illustrate a shared value \nthat certain decisions need to be explained. \nA California law requires that warehouse employees are provided with notice and explana-\ntion about quotas, potentially facilitated by automated systems, that apply to them. Warehous-\ning employers in California that use quota systems (often facilitated by algorithmic monitoring systems) are \nrequired to provide employees with a written description of each quota that applies to the employee, including", "0d87b088-8909-47ef-9705-c44f991c695e": "Table of Contents \n1. \nIntroduction ..............................................................................................................................................1 \n2. \nOverview of Risks Unique to or Exacerbated by GAI .....................................................................2 \n3. \nSuggested Actions to Manage GAI Risks ......................................................................................... 12 \nAppendix A. Primary GAI Considerations ............................................................................................... 47 \nAppendix B. References ................................................................................................................................ 54", "948acbdd-82ea-43ec-b9f4-c20ea2ce234d": "find notices and explanations, read them quickly, and understand and act on them. This includes ensuring that \nnotices and explanations are accessible to users with disabilities and are available in the language(s) and read-\ning level appropriate for the audience. Notices and explanations may need to be available in multiple forms, \n(e.g., on paper, on a physical sign, or online), in order to meet these expectations and to be accessible to the \nAmerican public. \nProvide explanations as to how and why a decision was made or an action was taken by an \nautomated system \nTailored to the purpose. Explanations should be tailored to the specific purpose for which the user is \nexpected to use the explanation, and should clearly state that purpose. An informational explanation might \ndiffer from an explanation provided to allow for the possibility of recourse, an appeal, or one provided in the \ncontext of a dispute or contestation process. For the purposes of this framework, 'explanation' should be", "07b0149e-d8de-4787-a581-784029c5ddd1": "ENDNOTES\n35. Carrie Johnson. Flaws plague a tool meant to help low-risk federal prisoners win early release. NPR.\nJan. 26, 2022. https://www.npr.org/2022/01/26/1075509175/flaws-plague-a-tool-meant-to-help-low\u00ad\nrisk-federal-prisoners-win-early-release.; Carrie Johnson. Justice Department works to curb racial bias\nin deciding who's released from prison. NPR. Apr. 19, 2022. https://\nwww.npr.org/2022/04/19/1093538706/justice-department-works-to-curb-racial-bias-in-deciding\u00ad\nwhos-released-from-pris; National Institute of Justice. 2021 Review and Revalidation of the First Step Act\nRisk Assessment Tool. National Institute of Justice NCJ 303859. Dec., 2021. https://www.ojp.gov/\npdffiles1/nij/303859.pdf\n36. Andrew Thompson. Google\u2019s Sentiment Analyzer Thinks Being Gay Is Bad. Vice. Oct. 25, 2017. https://\nwww.vice.com/en/article/j5jmj8/google-artificial-intelligence-bias\n37. Kaggle. Jigsaw Unintended Bias in Toxicity Classification: Detect toxicity across a diverse range of", "d1f75864-ad74-4188-a2f0-625b3b34dd62": "given a brief, clear notice that they are entitled to opt-out, along with clear instructions for how to opt-out. \nInstructions should be provided in an accessible form and should be easily findable by those impacted by the \nautomated system. The brevity, clarity, and accessibility of the notice and instructions should be assessed (e.g., \nvia user experience research). \nHuman alternatives provided when appropriate. In many scenarios, there is a reasonable expectation \nof human involvement in attaining rights, opportunities, or access. When automated systems make up part of \nthe attainment process, alternative timely human-driven processes should be provided. The use of a human \nalternative should be triggered by an opt-out process. \nTimely and not burdensome human alternative. Opting out should be timely and not unreasonably \nburdensome in both the process of requesting to opt-out and the human-driven alternative provided.", "d5430903-a32f-42c0-908e-1b1b0caa72eb": "Power. Public Affairs. 2019.\n64. Angela Chen. Why the Future of Life Insurance May Depend on Your Online Presence. The Verge. Feb.\n7, 2019.\nhttps://www.theverge.com/2019/2/7/18211890/social-media-life-insurance-new-york-algorithms-big\u00ad\ndata-discrimination-online-records\n68", "8c7c6cd5-965a-408f-b1fc-cba59e93879d": "technical companion is intended to be used as a reference by people across many circumstances \u2013 anyone \nimpacted by automated systems, and anyone developing, designing, deploying, evaluating, or making policy to \ngovern the use of an automated system. \nEach principle is accompanied by three supplemental sections: \n1\n2\nWHY THIS PRINCIPLE IS IMPORTANT: \nThis section provides a brief summary of the problems that the principle seeks to address and protect against, including \nillustrative examples. \nWHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS: \n\u2022 The expectations for automated systems are meant to serve as a blueprint for the development of additional technical\nstandards and practices that should be tailored for particular sectors and contexts.\n\u2022 This section outlines practical steps that can be implemented to realize the vision of the Blueprint for an AI Bill of Rights. The \nexpectations laid out often mirror existing practices for technology development, including pre-deployment testing, ongoing", "e1311e28-6431-4f7d-b026-99aa986c05f9": "capabilities, competencies, demographic groups, domain expertise, educational \nbackgrounds, lived experiences, professions, and skills across the enterprise to \ninform and conduct risk measurement and management functions. \nHuman-AI Con\ufb01guration; Harmful \nBias and Homogenization \nMP-1.2-002 \nVerify that data or benchmarks used in risk measurement, and users, \nparticipants, or subjects involved in structured GAI public feedback exercises \nare representative of diverse in-context user populations. \nHuman-AI Con\ufb01guration; Harmful \nBias and Homogenization \nAI Actor Tasks: AI Deployment", "22760b2b-f237-4c9b-8e4b-6c86d4043388": "evaluation methods (e.g., human oversight and automated evaluation, proven \ncryptographic techniques, review of content inputs). \nInformation Integrity", "714b25fc-f9c6-4d83-b067-6f0c22b4a6f0": "65. See, e.g., Scott Ikeda. Major Data Broker Exposes 235 Million Social Media Profiles in Data Lead: Info\nAppears to Have Been Scraped Without Permission. CPO Magazine. Aug. 28, 2020. https://\nwww.cpomagazine.com/cyber-security/major-data-broker-exposes-235-million-social-media-profiles\u00ad\nin-data-leak/; Lily Hay Newman. 1.2 Billion Records Found Exposed Online in a Single Server. WIRED,\nNov. 22, 2019. https://www.wired.com/story/billion-records-exposed-online/\n66. Lola Fadulu. Facial Recognition Technology in Public Housing Prompts Backlash. New York Times.\nSept. 24, 2019.\nhttps://www.nytimes.com/2019/09/24/us/politics/facial-recognition-technology-housing.html\n67. Jo Constantz. \u2018They Were Spying On Us\u2019: Amazon, Walmart, Use Surveillance Technology to Bust\nUnions. Newsweek. Dec. 13, 2021.\nhttps://www.newsweek.com/they-were-spying-us-amazon-walmart-use-surveillance-technology-bust\u00ad\nunions-1658603\n68. See, e.g., enforcement actions by the FTC against the photo storage app Everalbaum", "08545214-7d84-4218-a3c8-92b8a4f288d8": "organization\u2019s business processes or other activities, system goals, any human-run procedures that form a \npart of the system, and specific performance expectations; a description of any data used to train machine \nlearning models or for other purposes, including how data sources were processed and interpreted, a \nsummary of what data might be missing, incomplete, or erroneous, and data relevancy justifications; the \nresults of public consultation such as concerns raised and any decisions made due to these concerns; risk \nidentification and management assessments and any steps taken to mitigate potential harms; the results of \nperformance testing including, but not limited to, accuracy, differential demographic impact, resulting \nerror rates (overall and per demographic group), and comparisons to previously deployed systems; \nongoing monitoring procedures and regular performance testing reports, including monitoring frequency,", "4318fa7a-1dda-469f-9fb2-e36092d0bb7b": "Integration \nMP-4.1-008 \nRe-evaluate risks when adapting GAI models to new domains. Additionally, \nestablish warning systems to determine if a GAI system is being used in a new \ndomain where previous assumptions (relating to context of use or mapped risks \nsuch as security, and safety) may no longer hold.  \nCBRN Information or Capabilities; \nIntellectual Property; Harmful Bias \nand Homogenization; Dangerous, \nViolent, or Hateful Content; Data \nPrivacy \nMP-4.1-009 Leverage approaches to detect the presence of PII or sensitive data in generated \noutput text, image, video, or audio. \nData Privacy", "d282c21a-510c-4f1c-b774-28375bfd6162": "https://arxiv.org/pdf/2308.13387 \nWardle, C. et al. (2017) Information Disorder: Toward an interdisciplinary framework for research and \npolicy making. Council of Europe. https://rm.coe.int/information-disorder-toward-an-interdisciplinary-\nframework-for-researc/168076277c \nWeatherbed, J. (2024) Trolls have \ufb02ooded X with graphic Taylor Swift AI fakes. The Verge. \nhttps://www.theverge.com/2024/1/25/24050334/x-twitter-taylor-swift-ai-fake-images-trending \nWei, J. et al. (2024) Long Form Factuality in Large Language Models. arXiv. \nhttps://arxiv.org/pdf/2403.18802 \nWeidinger, L. et al. (2021) Ethical and social risks of harm from Language Models. arXiv. \nhttps://arxiv.org/pdf/2112.04359 \nWeidinger, L. et al. (2023) Sociotechnical Safety Evaluation of Generative AI Systems. arXiv. \nhttps://arxiv.org/pdf/2310.11986 \nWeidinger, L. et al. (2022) Taxonomy of Risks posed by Language Models. FAccT \u201922. \nhttps://dl.acm.org/doi/pdf/10.1145/3531146.3533088", "e24fe8bc-2648-4d4a-8e40-01161440f8fe": "35 \nMEASURE 2.9: The AI model is explained, validated, and documented, and AI system output is interpreted within its context \u2013 as \nidenti\ufb01ed in the MAP function \u2013 to inform responsible use and governance. \nAction ID \nSuggested Action \nGAI Risks \nMS-2.9-001 \nApply and document ML explanation results such as: Analysis of embeddings, \nCounterfactual prompts, Gradient-based attributions, Model \ncompression/surrogate models, Occlusion/term reduction. \nConfabulation \nMS-2.9-002 \nDocument GAI model details including: Proposed use and organizational value; \nAssumptions and limitations, Data collection methodologies; Data provenance; \nData quality; Model architecture (e.g., convolutional neural network, \ntransformers, etc.); Optimization objectives; Training algorithms; RLHF \napproaches; Fine-tuning or retrieval-augmented generation approaches; \nEvaluation data; Ethical considerations; Legal and regulatory requirements. \nInformation Integrity; Harmful Bias \nand Homogenization", "a7a1ff30-7a4a-40c5-8ed2-58fc42094e5c": "SAFE AND EFFECTIVE \nSYSTEMS \nWHY THIS PRINCIPLE IS IMPORTANT\nThis section provides a brief summary of the problems which the principle seeks to address and protect \nagainst, including illustrative examples. \nWhile technologies are being deployed to solve problems across a wide array of issues, our reliance on technology can \nalso lead to its use in situations where it has not yet been proven to work\u2014either at all or within an acceptable range \nof error. In other cases, technologies do not work as intended or as promised, causing substantial and unjustified harm. \nAutomated systems sometimes rely on data from other systems, including historical data, allowing irrelevant informa\u00ad\ntion from past decisions to infect decision-making in unrelated situations.  In some cases, technologies are purposeful\u00ad\nly designed to violate the safety of others, such as technologies designed to facilitate stalking; in other cases, intended \nor unintended uses lead to unintended harms.", "c4246db7-6c73-48a5-aba8-2216ba9a71d5": "moving principles into practice. \nThe expectations given in the Technical Companion are meant to serve as a blueprint for the development of \nadditional technical standards and practices that should be tailored for particular sectors and contexts. While \nexisting laws informed the development of the Blueprint for an AI Bill of Rights, this framework does not detail \nthose laws beyond providing them as examples, where appropriate, of existing protective measures. This \nframework instead shares a broad, forward-leaning vision of recommended principles for automated system \ndevelopment and use to inform private and public involvement with these systems where they have the poten\u00ad\ntial to meaningfully impact rights, opportunities, or access. Additionally, this framework does not analyze or \ntake a position on legislative and regulatory proposals in municipal, state, and federal government, or those in \nother countries.", "d0d99450-83ba-48c6-8f9e-3935192d7a48": "monitoring, and governance structures for automated systems, but also go further to address unmet needs for change and offer \nconcrete directions for how those changes can be made. \n\u2022 Expectations about reporting are intended for the entity developing or using the automated system. The resulting reports can \nbe provided to the public, regulators, auditors, industry standards groups, or others engaged in independent review, and should \nbe made public as much as possible consistent with law, regulation, and policy, and noting that intellectual property, law \nenforcement, or national security considerations may prevent public release. Where public reports are not possible, the \ninformation should be provided to oversight bodies and privacy, civil liberties, or other ethics officers charged with safeguard \ning individuals\u2019 rights. These reporting expectations are important for transparency, so the American people can have", "3836563b-34f7-43bb-be66-5bf8842759b9": "10 \nGAI systems can ease the unintentional production or dissemination of false, inaccurate, or misleading \ncontent (misinformation) at scale, particularly if the content stems from confabulations.  \nGAI systems can also ease the deliberate production or dissemination of false or misleading information \n(disinformation) at scale, where an actor has the explicit intent to deceive or cause harm to others. Even \nvery subtle changes to text or images can manipulate human and machine perception. \nSimilarly, GAI systems could enable a higher degree of sophistication for malicious actors to produce \ndisinformation that is targeted towards speci\ufb01c demographics. Current and emerging multimodal models \nmake it possible to generate both text-based disinformation and highly realistic \u201cdeepfakes\u201d \u2013 that is, \nsynthetic audiovisual content and photorealistic images.12 Additional disinformation threats could be \nenabled by future GAI models trained on new data modalities.", "0c4eee0b-95f6-4546-9277-8d41b2128ead": "Human-AI Con\ufb01guration; \nConfabulation \nAI Actor Tasks: AI Design, AI Impact Assessment, A\ufb00ected Individuals and Communities, Governance and Oversight \n \nGOVERN 6.1: Policies and procedures are in place that address AI risks associated with third-party entities, including risks of \ninfringement of a third-party\u2019s intellectual property or other rights. \nAction ID \nSuggested Action \nGAI Risks \nGV-6.1-001 Categorize di\ufb00erent types of GAI content with associated third-party rights (e.g., \ncopyright, intellectual property, data privacy). \nData Privacy; Intellectual \nProperty; Value Chain and \nComponent Integration \nGV-6.1-002 Conduct joint educational activities and events in collaboration with third parties \nto promote best practices for managing GAI risks.  \nValue Chain and Component \nIntegration \nGV-6.1-003 \nDevelop and validate approaches for measuring the success of content \nprovenance management e\ufb00orts with third parties (e.g., incidents detected and \nresponse times). \nInformation Integrity; Value Chain", "03c8bb9f-e7b9-4e4f-93d6-3a31ac3c4348": "access needs. \nReporting. When members of the public wish to know what data about them is being used in a system, the \nentity responsible for the development of the system should respond quickly with a report on the data it has \ncollected or stored about them. Such a report should be machine-readable, understandable by most users, and \ninclude, to the greatest extent allowable under law, any data and metadata about them or collected from them, \nwhen and how their data and metadata were collected, the specific ways that data or metadata are being used, \nwho has access to their data and metadata, and what time limitations apply to these data. In cases where a user \nlogin is not available, identity verification may need to be performed before providing such a report to ensure \nuser privacy. Additionally, summary reporting should be proactively made public with general information \nabout how peoples\u2019 data and metadata is used, accessed, and stored. Summary reporting should include the", "913ec1ef-ecb8-499f-bbd0-c79b8355fd1c": "Applying The Blueprint for an AI Bill of Rights \nDEFINITIONS\nALGORITHMIC DISCRIMINATION: \u201cAlgorithmic discrimination\u201d occurs when automated systems \ncontribute to unjustified different treatment or impacts disfavoring people based on their race, color, ethnicity, \nsex (including pregnancy, childbirth, and related medical conditions, gender identity, intersex status, and sexual \norientation), religion, age, national origin, disability, veteran status, genetic information, or any other classifica-\ntion protected by law. Depending on the specific circumstances, such algorithmic discrimination may violate \nlegal protections. Throughout this framework the term \u201calgorithmic discrimination\u201d takes this meaning (and \nnot a technical understanding of discrimination as distinguishing between items). \nAUTOMATED SYSTEM: An \"automated system\" is any system, software, or process that uses computation as \nwhole or part of a system to determine outcomes, make or aid decisions, inform policy implementation, collect", "81258dfa-876d-4eae-befc-9ecdeb596c38": "12 \nCSAM. Even when trained on \u201cclean\u201d data, increasingly capable GAI models can synthesize or produce \nsynthetic NCII and CSAM. Websites, mobile apps, and custom-built models that generate synthetic NCII \nhave moved from niche internet forums to mainstream, automated, and scaled online businesses.  \nTrustworthy AI Characteristics: Fair with Harmful Bias Managed, Safe, Privacy Enhanced \n2.12. \nValue Chain and Component Integration \nGAI value chains involve many third-party components such as procured datasets, pre-trained models, \nand software libraries. These components might be improperly obtained or not properly vetted, leading \nto diminished transparency or accountability for downstream users. While this is a risk for traditional AI \nsystems and some other digital technologies, the risk is exacerbated for GAI due to the scale of the \ntraining data, which may be too large for humans to vet; the di\ufb03culty of training foundation models,", "db999b51-bd0e-46d4-9202-cff81afad964": "38 \nMEASURE 2.13: E\ufb00ectiveness of the employed TEVV metrics and processes in the MEASURE function are evaluated and \ndocumented. \nAction ID \nSuggested Action \nGAI Risks \nMS-2.13-001 \nCreate measurement error models for pre-deployment metrics to demonstrate \nconstruct validity for each metric (i.e., does the metric e\ufb00ectively operationalize \nthe desired concept): Measure or estimate, and document, biases or statistical \nvariance in applied metrics or structured human feedback processes; Leverage \ndomain expertise when modeling complex societal constructs such as hateful \ncontent. \nConfabulation; Information \nIntegrity; Harmful Bias and \nHomogenization \nAI Actor Tasks: AI Deployment, Operation and Monitoring, TEVV \n \nMEASURE 3.2: Risk tracking approaches are considered for settings where AI risks are di\ufb03cult to assess using currently available \nmeasurement techniques or where metrics are not yet available. \nAction ID \nSuggested Action \nGAI Risks \nMS-3.2-001", "45268e73-21c7-4a9a-b026-a97f0f1e299b": "prevent future occurrences. Conduct post-mortem analyses of incidents with \nrelevant AI Actors, to understand the root causes and implement preventive \nmeasures. \nHuman-AI Con\ufb01guration; \nDangerous, Violent, or Hateful \nContent \nMG-4.2-003 Use visualizations or other methods to represent GAI model behavior to ease \nnon-technical stakeholders understanding of GAI system functionality. \nHuman-AI Con\ufb01guration \nAI Actor Tasks: AI Deployment, AI Design, AI Development, A\ufb00ected Individuals and Communities, End-Users, Operation and \nMonitoring, TEVV \n \nMANAGE 4.3: Incidents and errors are communicated to relevant AI Actors, including a\ufb00ected communities. Processes for tracking, \nresponding to, and recovering from incidents and errors are followed and documented. \nAction ID \nSuggested Action \nGAI Risks \nMG-4.3-001 \nConduct after-action assessments for GAI system incidents to verify incident \nresponse and recovery processes are followed and e\ufb00ective, including to follow", "c8d3ea4b-63fa-4698-b7c2-63895c628511": "in whole or in part may not be appropriate given the intended use of automated systems to achieve government \nagency missions. Future sector-specific guidance will likely be necessary and important for guiding the use of \nautomated systems in certain settings such as AI systems used as part of school building security or automated \nhealth diagnostic systems. \nThe Blueprint for an AI Bill of Rights recognizes that law enforcement activities require a balancing of \nequities, for example, between the protection of sensitive law enforcement information and the principle of \nnotice; as such, notice may not be appropriate, or may need to be adjusted to protect sources, methods, and \nother law enforcement equities. Even in contexts where these principles may not apply in whole or in part, \nfederal departments and agencies remain subject to judicial, privacy, and civil liberties oversight as well as \nexisting policies and safeguards that govern automated systems, including, for example, Executive Order 13960,", "51e515fd-fd17-447c-a07f-ff68b43cc751": "https://www.mandiant.com/resources/blog/securing-ai-pipeline \nBurgess, M. (2024) Generative AI\u2019s Biggest Security Flaw Is Not Easy to Fix. WIRED. \nhttps://www.wired.com/story/generative-ai-prompt-injection-hacking/ \nBurtell, M. et al. (2024) The Surprising Power of Next Word Prediction: Large Language Models \nExplained, Part 1. Georgetown Center for Security and Emerging Technology. \nhttps://cset.georgetown.edu/article/the-surprising-power-of-next-word-prediction-large-language-\nmodels-explained-part-1/ \nCanadian Centre for Cyber Security (2023) Generative arti\ufb01cial intelligence (AI) - ITSAP.00.041. \nhttps://www.cyber.gc.ca/en/guidance/generative-arti\ufb01cial-intelligence-ai-itsap00041 \nCarlini, N., et al. (2021) Extracting Training Data from Large Language Models. Usenix. \nhttps://www.usenix.org/conference/usenixsecurity21/presentation/carlini-extracting \nCarlini, N. et al. (2023) Quantifying Memorization Across Neural Language Models. ICLR 2023. \nhttps://arxiv.org/pdf/2202.07646", "89295981-fe45-4788-b206-98c5e10f6bcf": "Advocate and Floor Captain, Atlantic Plaza Towers Tenants Association\nThe individual panelists described the ways in which AI systems and other technologies are increasingly being \nused to limit access to equal opportunities in education, housing, and employment. Education-related \nconcerning uses included the increased use of remote proctoring systems, student location and facial \nrecognition tracking, teacher evaluation systems, robot teachers, and more. Housing-related concerning uses \nincluding automated tenant background screening and facial recognition-based controls to enter or exit \nhousing complexes. Employment-related concerning uses included discrimination in automated hiring \nscreening and workplace surveillance. Various panelists raised the limitations of existing privacy law as a key \nconcern, pointing out that students should be able to reinvent themselves and require privacy of their student", "d91a4739-1860-4e2f-a88d-921afc9e58ad": "22 \nGV-6.2-003 \nEstablish incident response plans for third-party GAI technologies: Align incident \nresponse plans with impacts enumerated in MAP 5.1; Communicate third-party \nGAI incident response plans to all relevant AI Actors; De\ufb01ne ownership of GAI \nincident response functions; Rehearse third-party GAI incident response plans at \na regular cadence; Improve incident response plans based on retrospective \nlearning; Review incident response plans for alignment with relevant breach \nreporting, data protection, data privacy, or other laws. \nData Privacy; Human-AI \nCon\ufb01guration; Information \nSecurity; Value Chain and \nComponent Integration; Harmful \nBias and Homogenization \nGV-6.2-004 \nEstablish policies and procedures for continuous monitoring of third-party GAI \nsystems in deployment. \nValue Chain and Component \nIntegration \nGV-6.2-005 \nEstablish policies and procedures that address GAI data redundancy, including \nmodel weights and other system artifacts. \nHarmful Bias and Homogenization \nGV-6.2-006", "0c855fa7-f69e-4584-8664-653671650fc2": "answer itself is incorrect. Similarly, an LLM could falsely assert that it is human or has human traits, \npotentially deceiving humans into believing they are speaking with another human. \nThe extent to which humans can be deceived by LLMs, the mechanisms by which this may occur, and the \npotential risks from adversarial prompting of such behavior are emerging areas of study. Given the wide \nrange of downstream impacts of GAI, it is di\ufb03cult to estimate the downstream scale and impact of \nconfabulations. \nTrustworthy AI Characteristics: Fair with Harmful Bias Managed, Safe, Valid and Reliable, Explainable \nand Interpretable \n2.3. Dangerous, Violent, or Hateful Content \nGAI systems can produce content that is inciting, radicalizing, or threatening, or that glori\ufb01es violence, \nwith greater ease and scale than other technologies. LLMs have been reported to generate dangerous or \nviolent recommendations, and some models have generated actionable instructions for dangerous or", "60b017ce-e6fe-4811-834f-795d4a12c364": "results of any surveillance pre-deployment assessment, including disparity assessment in the real-world \ndeployment context, the specific identified goals of any data collection, and the assessment done to ensure \nonly the minimum required data is collected. It should also include documentation about the scope limit \nassessments, including data retention timelines and associated justification, and an assessment of the \nimpact of surveillance or data collection on rights, opportunities, and access. Where possible, this \nassessment of the impact of surveillance should be done by an independent party. Reporting should be \nprovided in a clear and machine-readable manner.  \n35", "3d60073b-d973-4f20-8886-8710331b996e": "appropriately and meaningfully given. Any consent requests should be brief, \nbe understandable in plain language, and give you agency over data collection \nand the specific context of use; current hard-to-understand no\u00ad\ntice-and-choice practices for broad uses of data should be changed. Enhanced \nprotections and restrictions for data and inferences related to sensitive do\u00ad\nmains, including health, work, education, criminal justice, and finance, and \nfor data pertaining to youth should put you first. In sensitive domains, your \ndata and related inferences should only be used for necessary functions, and \nyou should be protected by ethical review and use prohibitions. You and your \ncommunities should be free from unchecked surveillance; surveillance tech\u00ad\nnologies should be subject to heightened oversight that includes at least \npre-deployment assessment of their potential harms and scope limits to pro\u00ad\ntect privacy and civil liberties. Continuous surveillance and monitoring", "fee5c143-dc56-4cc6-ba07-552465ae2b72": "You should be able to opt out, where appropriate, and \nhave access to a person who can quickly consider and \nremedy problems you encounter. You should be able to opt \nout from automated systems in favor of a human alternative, where \nappropriate. Appropriateness should be determined based on rea\u00ad\nsonable expectations in a given context and with a focus on ensuring \nbroad accessibility and protecting the public from especially harm\u00ad\nful impacts. In some cases, a human or other alternative may be re\u00ad\nquired by law. You should have access to timely human consider\u00ad\nation and remedy by a fallback and escalation process if an automat\u00ad\ned system fails, it produces an error, or you would like to appeal or \ncontest its impacts on you. Human consideration and fallback \nshould be accessible, equitable, effective, maintained, accompanied \nby appropriate operator training, and should not impose an unrea\u00ad\nsonable burden on the public. Automated systems with an intended", "e1dc1672-fbcf-4551-aa8d-4896cc302aef": "and biological design tools. arXiv. https://arxiv.org/pdf/2306.13952", "eb4a5bf4-cad4-46d7-9ca0-a93e194b65eb": "standards may require instituting mitigation procedures and other protective measures to address \nalgorithmic discrimination, avoid meaningful harm, and achieve equity goals. \nOngoing monitoring and mitigation. Automated systems should be regularly monitored to assess algo\u00ad\nrithmic discrimination that might arise from unforeseen interactions of the system with inequities not \naccounted for during the pre-deployment testing, changes to the system after deployment, or changes to the \ncontext of use or associated data. Monitoring and disparity assessment should be performed by the entity \ndeploying or using the automated system to examine whether the system has led to algorithmic discrimina\u00ad\ntion when deployed. This assessment should be performed regularly and whenever a pattern of unusual \nresults is occurring. It can be performed using a variety of approaches, taking into account whether and how \ndemographic information of impacted people is available, for example via testing with a sample of users or via", "44763663-ed9a-43f0-84a5-ada3a7da3066": "9 \nand reduced content diversity). Overly homogenized outputs can themselves be incorrect, or they may \nlead to unreliable decision-making or amplify harmful biases. These phenomena can \ufb02ow from \nfoundation models to downstream models and systems, with the foundation models acting as \n\u201cbottlenecks,\u201d or single points of failure.  \nOverly homogenized content can contribute to \u201cmodel collapse.\u201d Model collapse can occur when model \ntraining over-relies on synthetic data, resulting in data points disappearing from the distribution of the \nnew model\u2019s outputs. In addition to threatening the robustness of the model overall, model collapse \ncould lead to homogenized outputs, including by amplifying any homogenization from the model used to \ngenerate the synthetic training data. \nTrustworthy AI Characteristics: Fair with Harmful Bias Managed, Valid and Reliable \n2.7. Human-AI Con\ufb01guration \nGAI system use can involve varying risks of miscon\ufb01gurations and poor interactions between a system", "dcfe160e-c7b2-4341-8d39-762060034476": "SAFE AND EFFECTIVE \nSYSTEMS \nHOW THESE PRINCIPLES CAN MOVE INTO PRACTICE\nReal-life examples of how these principles can become reality, through laws, policies, and practical \ntechnical and sociotechnical approaches to protecting rights, opportunities, and access. \u00ad\nSome U.S government agencies have developed specific frameworks for ethical use of AI \nsystems. The Department of Energy (DOE) has activated the AI Advancement Council that oversees coordina-\ntion and advises on implementation of the DOE AI Strategy and addresses issues and/or escalations on the \nethical use and development of AI systems.20 The Department of Defense has adopted Artificial Intelligence \nEthical Principles, and tenets for Responsible Artificial Intelligence specifically tailored to its national \nsecurity and defense activities.21 Similarly, the U.S. Intelligence Community (IC) has developed the Principles", "fabb9ed6-5dfa-413e-bcf5-2c9e1edb6d58": "the AI lifecycle; or other issues that diminish transparency or accountability for downstream \nusers. \n2.1. CBRN Information or Capabilities \nIn the future, GAI may enable malicious actors to more easily access CBRN weapons and/or relevant \nknowledge, information, materials, tools, or technologies that could be misused to assist in the design, \ndevelopment, production, or use of CBRN weapons or other dangerous materials or agents. While \nrelevant biological and chemical threat knowledge and information is often publicly accessible, LLMs \ncould facilitate its analysis or synthesis, particularly by individuals without formal scienti\ufb01c training or \nexpertise.  \nRecent research on this topic found that LLM outputs regarding biological threat creation and attack \nplanning provided minimal assistance beyond traditional search engine queries, suggesting that state-of-\nthe-art LLMs at the time these studies were conducted do not substantially increase the operational", "63006b69-c2c6-4bab-9d11-2b7976bea75b": "SECTION TITLE\n \n \n \n \n \n \nApplying The Blueprint for an AI Bill of Rights \nRELATIONSHIP TO EXISTING LAW AND POLICY\nThere are regulatory safety requirements for medical devices, as well as sector-, population-, or technology-spe\u00ad\ncific privacy and security protections. Ensuring some of the additional protections proposed in this framework \nwould require new laws to be enacted or new policies and practices to be adopted. In some cases, exceptions to \nthe principles described in the Blueprint for an AI Bill of Rights may be necessary to comply with existing law, \nconform to the practicalities of a specific use case, or balance competing public interests. In particular, law \nenforcement, and other regulatory contexts may require government actors to protect civil rights, civil liberties, \nand privacy in a manner consistent with, but using alternate mechanisms to, the specific principles discussed in \nthis framework. The Blueprint for an AI Bill of Rights is meant to assist governments and the private sector in", "0f4c5c5a-f8dc-43af-85f2-45a85fba36ca": "APPENDIX\nSystems that impact the safety of communities such as automated traffic control systems, elec \n-ctrical grid controls, smart city technologies, and industrial emissions and environmental\nimpact control algorithms; and\nSystems related to access to benefits or services or assignment of penalties such as systems that\nsupport decision-makers who adjudicate benefits such as collating or analyzing information or\nmatching records, systems which similarly assist in the adjudication of administrative or criminal\npenalties, fraud detection algorithms, services or benefits access control algorithms, biometric\nsystems used as access control, and systems which make benefits or services related decisions on a\nfully or partially autonomous basis (such as a determination to revoke benefits).\n54", "76064db3-f7c4-4ded-bee2-739ed588ce64": "purpose speci\ufb01cation. For example, most model developers do not disclose speci\ufb01c data sources on \nwhich models were trained, limiting user awareness of whether personally identi\ufb01ably information (PII) \nwas trained on and, if so, how it was collected.  \nModels may leak, generate, or correctly infer sensitive information about individuals. For example, \nduring adversarial attacks, LLMs have revealed sensitive information (from the public domain) that was \nincluded in their training data. This problem has been referred to as data memorization, and may pose \nexacerbated privacy risks even for data present only in a small number of training samples.  \nIn addition to revealing sensitive information in GAI training data, GAI models may be able to correctly \ninfer PII or sensitive data that was not in their training data nor disclosed by the user by stitching \ntogether information from disparate sources. These inferences can have negative impact on an individual", "cfd1017b-b416-4a90-a926-b0851ad24488": "52 \n\u2022 \nMonitoring system capabilities and limitations in deployment through rigorous TEVV processes; \n\u2022 \nEvaluating how humans engage, interact with, or adapt to GAI content (especially in decision \nmaking tasks informed by GAI content), and how they react to applied provenance techniques \nsuch as overt disclosures. \nOrganizations can document and delineate GAI system objectives and limitations to identify gaps where \nprovenance data may be most useful. For instance, GAI systems used for content creation may require \nrobust watermarking techniques and corresponding detectors to identify the source of content or \nmetadata recording techniques and metadata management tools and repositories to trace content \norigins and modi\ufb01cations. Further narrowing of GAI task de\ufb01nitions to include provenance data can \nenable organizations to maximize the utility of provenance data and risk management e\ufb00orts. \nA.1.7. Enhancing Content Provenance through Structured Public Feedback", "0a829510-5812-4f88-bd78-9bd5eb4f0632": "2 \nThis work was informed by public feedback and consultations with diverse stakeholder groups as part of NIST\u2019s \nGenerative AI Public Working Group (GAI PWG). The GAI PWG was an open, transparent, and collaborative \nprocess, facilitated via a virtual workspace, to obtain multistakeholder input on GAI risk management and to \ninform NIST\u2019s approach. \nThe focus of the GAI PWG was limited to four primary considerations relevant to GAI: Governance, Content \nProvenance, Pre-deployment Testing, and Incident Disclosure (further described in Appendix A). As such, the \nsuggested actions in this document primarily address these considerations. \nFuture revisions of this pro\ufb01le will include additional AI RMF subcategories, risks, and suggested actions based \non additional considerations of GAI as the space evolves and empirical evidence indicates additional risks. A \nglossary of terms pertinent to GAI risk management will be developed and hosted on NIST\u2019s Trustworthy &", "1233b7f3-d931-4995-86d7-fcdf13a0ea42": "Information Technology Industry Council (2024) Authenticating AI-Generated Content. \nhttps://www.itic.org/policy/ITI_AIContentAuthorizationPolicy_122123.pdf \nJain, S. et al. (2023) Algorithmic Pluralism: A Structural Approach To Equal Opportunity. arXiv. \nhttps://arxiv.org/pdf/2305.08157 \nJi, Z. et al (2023) Survey of Hallucination in Natural Language Generation. ACM Comput. Surv. 55, 12, \nArticle 248. https://doi.org/10.1145/3571730 \nJones-Jang, S. et al. (2022) How do people react to AI failure? Automation bias, algorithmic aversion, and \nperceived controllability. Oxford. https://academic.oup.com/jcmc/article/28/1/zmac029/6827859] \nJussupow, E. et al. (2020) Why Are We Averse Towards Algorithms? A Comprehensive Literature Review \non Algorithm Aversion. ECIS 2020. https://aisel.aisnet.org/ecis2020_rp/168/ \nKalai, A., et al. (2024) Calibrated Language Models Must Hallucinate. arXiv. \nhttps://arxiv.org/pdf/2311.14648", "6adeab1c-726d-44b7-a091-4c8f57d78efe": "technologies and data, and contractors, consultants, and other third-party \npersonnel. \nIntellectual Property; Value Chain \nand Component Integration \nAI Actor Tasks: Operation and Monitoring, Procurement, Third-party entities \n \nGOVERN 6.2: Contingency processes are in place to handle failures or incidents in third-party data or AI systems deemed to be \nhigh-risk. \nAction ID \nSuggested Action \nGAI Risks \nGV-6.2-001 \nDocument GAI risks associated with system value chain to identify over-reliance \non third-party data and to identify fallbacks. \nValue Chain and Component \nIntegration \nGV-6.2-002 \nDocument incidents involving third-party GAI data and systems, including open-\ndata and open-source software. \nIntellectual Property; Value Chain \nand Component Integration", "d4dbc93f-1c23-4106-a8a8-aea5eab30df5": "any automated component is used to determine an action or decision. It should also include expectations about \nreporting described throughout this framework, such as the algorithmic impact assessments described as \npart of Algorithmic Discrimination Protections. \nAccountable. Notices should clearly identify the entity responsible for designing each component of the \nsystem and the entity using it. \nTimely and up-to-date. Users should receive notice of the use of automated systems in advance of using or \nwhile being impacted by the technology. An explanation should be available with the decision itself, or soon \nthereafter. Notice should be kept up-to-date and people impacted by the system should be notified of use case \nor key functionality changes. \nBrief and clear. Notices and explanations should be assessed, such as by research on users\u2019 experiences, \nincluding user testing, to ensure that the people using or impacted by the automated system are able to easily", "37e1195e-1f2b-4a57-9c67-44f8fd137203": "While some of these described capabilities lie beyond the reach of existing GAI tools, ongoing \nassessments of this risk would be enhanced by monitoring both the ability of AI tools to facilitate CBRN \nweapons planning and GAI systems\u2019 connection or access to relevant data and tools. \nTrustworthy AI Characteristic: Safe, Explainable and Interpretable", "8f766e05-5499-4c8d-b6f1-e64c9bc1b6fe": "and critical services. The American public deserves the assurance that, when rights, opportunities, or access are \nmeaningfully at stake and there is a reasonable expectation of an alternative to an automated system, they can conve\u00ad\nniently opt out of an automated system and will not be disadvantaged for that choice. In some cases, such a human or \nother alternative may be required by law, for example it could be required as \u201creasonable accommodations\u201d for people \nwith disabilities. \nIn addition to being able to opt out and use a human alternative, the American public deserves a human fallback \nsystem in the event that an automated system fails or causes harm. No matter how rigorously an automated system is \ntested, there will always be situations for which the system fails. The American public deserves protection via human \nreview against these outlying or unexpected scenarios. In the case of time-critical systems, the public should not have", "4c2995c2-8cf4-4666-8cae-2cddab5c0aa1": "About this Document \nThe Blueprint for an AI Bill of Rights: Making Automated Systems Work for the American People was \npublished by the White House Office of Science and Technology Policy in October 2022. This framework was \nreleased one year after OSTP announced the launch of a process to develop \u201ca bill of rights for an AI-powered \nworld.\u201d Its release follows a year of public engagement to inform this initiative. The framework is available \nonline at: https://www.whitehouse.gov/ostp/ai-bill-of-rights \nAbout the Office of Science and Technology Policy \nThe Office of Science and Technology Policy (OSTP) was established by the National Science and Technology \nPolicy, Organization, and Priorities Act of 1976 to provide the President and others within the Executive Office \nof the President with advice on the scientific, engineering, and technological aspects of the economy, national", "ed293c39-a2c7-4e96-bdb7-43ea102ba174": "29 \nMS-1.1-006 \nImplement continuous monitoring of GAI system impacts to identify whether GAI \noutputs are equitable across various sub-populations. Seek active and direct \nfeedback from a\ufb00ected communities via structured feedback mechanisms or red-\nteaming to monitor and improve outputs.  \nHarmful Bias and Homogenization \nMS-1.1-007 \nEvaluate the quality and integrity of data used in training and the provenance of \nAI-generated content, for example by employing techniques like chaos \nengineering and seeking stakeholder feedback. \nInformation Integrity \nMS-1.1-008 \nDe\ufb01ne use cases, contexts of use, capabilities, and negative impacts where \nstructured human feedback exercises, e.g., GAI red-teaming, would be most \nbene\ufb01cial for GAI risk measurement and management based on the context of \nuse. \nHarmful Bias and \nHomogenization; CBRN \nInformation or Capabilities \nMS-1.1-009 \nTrack and document risks or opportunities related to all GAI risks that cannot be", "9feea339-e568-4440-96ce-ba269c40347f": "issues in conversations with chatbots \u2013 and that users exhibit negative reactions to unhelpful responses \nfrom these chatbots during situations of distress. \nThis risk encompasses di\ufb03culty controlling creation of and public exposure to o\ufb00ensive or hateful \nlanguage, and denigrating or stereotypical content generated by AI. This kind of speech may contribute \nto downstream harm such as fueling dangerous or violent behaviors. The spread of denigrating or \nstereotypical content can also further exacerbate representational harms (see Harmful Bias and \nHomogenization below).  \nTrustworthy AI Characteristics: Safe, Secure and Resilient \n2.4. Data Privacy \nGAI systems raise several risks to privacy. GAI system training requires large volumes of data, which in \nsome cases may include personal data. The use of personal data for GAI training raises risks to widely \naccepted privacy principles, including to transparency, individual participation (including consent), and", "0dae095f-3616-47ba-9b4c-f495fbe42c2f": "necessary functions should be optional, i.e., should not be required, incentivized, or coerced in order to \nreceive opportunities or access to services. In cases where data is provided to an entity (e.g., health insurance \ncompany) in order to facilitate payment for such a need, that data should only be used for that purpose. \nEthical review and use prohibitions. Any use of sensitive data or decision process based in part on sensi-\ntive data that might limit rights, opportunities, or access, whether the decision is automated or not, should go \nthrough a thorough ethical review and monitoring, both in advance and by periodic review (e.g., via an indepen-\ndent ethics committee or similarly robust process). In some cases, this ethical review may determine that data \nshould not be used or shared for specific uses even with consent. Some novel uses of automated systems in this \ncontext, where the algorithm is dynamically developing and where the science behind the use case is not well", "3061ca42-f18e-4a76-9b9b-e378dc162984": "Bias and Homogenization; CBRN \nInformation or Capabilities \nMS-1.3-002 \nEngage in internal and external evaluations, GAI red-teaming, impact \nassessments, or other structured human feedback exercises in consultation \nwith representative AI Actors with expertise and familiarity in the context of \nuse, and/or who are representative of the populations associated with the \ncontext of use. \nHuman-AI Con\ufb01guration; Harmful \nBias and Homogenization; CBRN \nInformation or Capabilities \nMS-1.3-003 \nVerify those conducting structured human feedback exercises are not directly \ninvolved in system development tasks for the same GAI model. \nHuman-AI Con\ufb01guration; Data \nPrivacy \nAI Actor Tasks: AI Deployment, AI Development, AI Impact Assessment, A\ufb00ected Individuals and Communities, Domain Experts, \nEnd-Users, Operation and Monitoring, TEVV", "c8465ca6-885a-48c9-9b62-5449f084b0ce": "into technology design processes. The most prevalent in the United States is the Access Board\u2019s Section \n508 regulations,56 which are the technical standards for federal information communication technology (software, \nhardware, and web). Other standards include those issued by the International Organization for \nStandardization,57 and the World Wide Web Consortium Web Content Accessibility Guidelines,58 a globally \nrecognized voluntary consensus standard for web content and other information and communications \ntechnology. \nNIST has released Special Publication 1270, Towards a Standard for Identifying and Managing Bias \nin Artificial Intelligence.59 The special publication: describes the stakes and challenges of bias in artificial \nintelligence and provides examples of how and why it can chip away at public trust; identifies three categories \nof bias in AI \u2013 systemic, statistical, and human \u2013 and describes how and where they contribute to harms; and", "0c1c5568-2fbb-4c5b-b79a-6cbe6c17f209": "history of content. Provenance data tracking and synthetic content detection can help facilitate greater \ninformation access about both authentic and synthetic content to users, enabling better knowledge of \ntrustworthiness in AI systems. When combined with other organizational accountability mechanisms, \ndigital content transparency approaches can enable processes to trace negative outcomes back to their \nsource, improve information integrity, and uphold public trust. Provenance data tracking and synthetic \ncontent detection mechanisms provide information about the origin and history of content to assist in \nGAI risk management e\ufb00orts. \nProvenance metadata can include information about GAI model developers or creators of GAI content, \ndate/time of creation, location, modi\ufb01cations, and sources. Metadata can be tracked for text, images, \nvideos, audio, and underlying datasets. The implementation of provenance data tracking techniques can", "980b42a4-0ff2-437f-bc3f-e021380c4904": "that may potentially arise in more advanced, future GAI systems are not considered. Future updates may \nincorporate additional risks or provide further details on the risks identi\ufb01ed below. \nTo guide organizations in identifying and managing GAI risks, a set of risks unique to or exacerbated by \nthe development and use of GAI are de\ufb01ned below.5 Each risk is labeled according to the outcome, \nobject, or source of the risk (i.e., some are risks \u201cto\u201d a subject or domain and others are risks \u201cof\u201d or \n\u201cfrom\u201d an issue or theme). These risks provide a lens through which organizations can frame and execute \nrisk management e\ufb00orts. To help streamline risk management e\ufb00orts, each risk is mapped in Section 3 \n(as well as in tables in Appendix B) to relevant Trustworthy AI Characteristics identi\ufb01ed in the AI RMF.  \n \n \n5 These risks can be further categorized by organizations depending on their unique approaches to risk de\ufb01nition", "1f602c98-0f78-4112-bd8d-1948ae89882d": "opportunities\u2026, or benefits.\u201d \nNIST\u2019s Privacy Framework provides a comprehensive, detailed and actionable approach for \norganizations to manage privacy risks. The NIST Framework gives organizations ways to identify and \ncommunicate their privacy risks and goals to support ethical decision-making in system, product, and service \ndesign or deployment, as well as the measures they are taking to demonstrate compliance with applicable laws \nor regulations. It has been voluntarily adopted by organizations across many different sectors around the world.78\nA school board\u2019s attempt to surveil public school students\u2014undertaken without \nadequate community input\u2014sparked a state-wide biometrics moratorium.79 Reacting to a plan in \nthe city of Lockport, New York, the state\u2019s legislature banned the use of facial recognition systems and other \n\u201cbiometric identifying technology\u201d in schools until July 1, 2022.80 The law additionally requires that a report on", "d0a26208-636c-4214-90a7-aa53131b8919": "does not supersede, modify, or direct an interpretation of any existing statute, regulation, policy, or \ninternational instrument. It does not constitute binding guidance for the public or Federal agencies and \ntherefore does not require compliance with the principles described herein. It also is not determinative of what \nthe U.S. government\u2019s position will be in any international negotiation. Adoption of these principles may not \nmeet the requirements of existing statutes, regulations, policies, or international instruments, or the \nrequirements of the Federal agencies that enforce them. These principles are not intended to, and do not, \nprohibit or limit any lawful activity of a government agency, including law enforcement, national security, or \nintelligence activities. \nThe appropriate application of the principles set forth in this white paper depends significantly on the \ncontext in which automated systems are being utilized. In some circumstances, application of these principles", "ee563e5c-3618-435e-8a28-e9c8655c8d6e": "these systems and use associated human-driven mechanisms instead, ensuring timeliness of benefit payments, \nand providing clear notice about the use of these systems and clear explanations of how and what the \ntechnologies are doing. Some panelists suggested that technology should be used to help people receive \nbenefits, e.g., by pushing benefits to those in need and ensuring automated decision-making systems are only \nused to provide a positive outcome; technology shouldn't be used to take supports away from people who need \nthem. \nPanel 6: The Healthcare System. This event explored current and emerging uses of technology in the \nhealthcare system and consumer products related to health. \nWelcome:\n\u2022\nAlondra Nelson, Deputy Director for Science and Society, White House Office of Science and Technology\nPolicy\n\u2022\nPatrick Gaspard, President and CEO, Center for American Progress\nModerator: Micky Tripathi, National Coordinator for Health Information Technology, U.S Department of \nHealth and Human Services.", "73123dea-1304-4967-8f32-c8c9484ff477": "SAFE AND EFFECTIVE \nSYSTEMS \nWHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\nThe expectations for automated systems are meant to serve as a blueprint for the development of additional \ntechnical standards and practices that are tailored for particular sectors and contexts. \nDerived data sources tracked and reviewed carefully. Data that is derived from other data through \nthe use of algorithms, such as data derived or inferred from prior model outputs, should be identified and \ntracked, e.g., via a specialized type in a data schema. Derived data should be viewed as potentially high-risk \ninputs that may lead to feedback loops, compounded harm, or inaccurate results. Such sources should be care\u00ad\nfully validated against the risk of collateral consequences. \nData reuse limits in sensitive domains. Data reuse, and especially data reuse in a new context, can result \nin the spreading and scaling of harms. Data from some domains, including criminal justice data and data indi\u00ad", "41c0457c-0232-44b5-852a-d481ca70ce21": "16 \nGOVERN 1.5: Ongoing monitoring and periodic review of the risk management process and its outcomes are planned, and \norganizational roles and responsibilities are clearly de\ufb01ned, including determining the frequency of periodic review. \nAction ID \nSuggested Action \nGAI Risks \nGV-1.5-001 De\ufb01ne organizational responsibilities for periodic review of content provenance \nand incident monitoring for GAI systems. \nInformation Integrity \nGV-1.5-002 \nEstablish organizational policies and procedures for after action reviews of GAI \nsystem incident response and incident disclosures, to identify gaps; Update \nincident response and incident disclosure processes as required. \nHuman-AI Con\ufb01guration; \nInformation Security \nGV-1.5-003 \nMaintain a document retention policy to keep history for test, evaluation, \nvalidation, and veri\ufb01cation (TEVV), and digital content transparency methods for \nGAI. \nInformation Integrity; Intellectual \nProperty \nAI Actor Tasks: Governance and Oversight, Operation and Monitoring", "96a6d0c5-2e52-417f-a2db-56555912e00c": "Based Participatory Research Program developed by the National Institutes of Health and the participatory \ntechnology assessments developed by the National Oceanic and Atmospheric Administration.18\nThe National Institute of Standards and Technology (NIST) is developing a risk \nmanagement framework to better manage risks posed to individuals, organizations, and \nsociety by AI.19 The NIST AI Risk Management Framework, as mandated by Congress, is intended for \nvoluntary use to help incorporate trustworthiness considerations into the design, development, use, and \nevaluation of AI products, services, and systems. The NIST framework is being developed through a consensus-\ndriven, open, transparent, and collaborative process that includes workshops and other opportunities to provide \ninput. The NIST framework aims to foster the development of innovative approaches to address \ncharacteristics of trustworthiness including accuracy, explainability and interpretability, reliability, privacy,", "3118d718-c7c5-4e30-a48f-6da5e0f06528": "or unintended uses lead to unintended harms. \nMany of the harms resulting from these technologies are preventable, and actions are already being taken to protect \nthe public. Some companies have put in place safeguards that have prevented harm from occurring by ensuring that \nkey development decisions are vetted by an ethics review; others have identified and mitigated harms found through \npre-deployment testing and ongoing monitoring processes. Governments at all levels have existing public consulta\u00ad\ntion processes that may be applied when considering the use of new automated systems, and existing product develop\u00ad\nment and testing practices already protect the American public from many potential harms. \nStill, these kinds of practices are deployed too rarely and unevenly. Expanded, proactive protections could build on \nthese existing practices, increase confidence in the use of automated systems, and protect the American public. Inno\u00ad", "56e73190-3953-4683-bd63-8c163f90136b": "SAFE AND EFFECTIVE \nSYSTEMS \nWHY THIS PRINCIPLE IS IMPORTANT\nThis section provides a brief summary of the problems which the principle seeks to address and protect \nagainst, including illustrative examples. \n\u2022\nAI-enabled \u201cnudification\u201d technology that creates images where people appear to be nude\u2014including apps that\nenable non-technical users to create or alter images of individuals without their consent\u2014has proliferated at an\nalarming rate. Such technology is becoming a common form of image-based abuse that disproportionately\nimpacts women. As these tools become more sophisticated, they are producing altered images that are increasing\u00ad\nly realistic and are difficult for both humans and AI to detect as inauthentic. Regardless of authenticity, the expe\u00ad\nrience of harm to victims of non-consensual intimate images can be devastatingly real\u2014affecting their personal\nand professional lives, and impacting their mental and physical health.10\n\u2022", "c3309604-8e53-406d-871b-1186ac575409": "Virginia Doellgast and Sean O'Brady. Making Call Center Jobs Better: The Relationship between\nManagement Practices and Worker Stress. A Report for the CWA. June 2020. https://\nhdl.handle.net/1813/74307\n62. See, e.g., Federal Trade Commission. Data Brokers: A Call for Transparency and Accountability. May\n2014.\nhttps://www.ftc.gov/system/files/documents/reports/data-brokers-call-transparency-accountability\u00ad\nreport-federal-trade-commission-may-2014/140527databrokerreport.pdf; Cathy O\u2019Neil.\nWeapons of Math Destruction. Penguin Books. 2017.\nhttps://en.wikipedia.org/wiki/Weapons_of_Math_Destruction\n63. See, e.g., Rachel Levinson-Waldman, Harsha Pandurnga, and Faiza Patel. Social Media Surveillance by\nthe U.S. Government. Brennan Center for Justice. Jan. 7, 2022.\nhttps://www.brennancenter.org/our-work/research-reports/social-media-surveillance-us-government;\nShoshana Zuboff. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of\nPower. Public Affairs. 2019.", "0fdf9b30-0b9a-4ac0-b691-44357de98eb0": "roughly in the order in which they would be instituted. \nProtect the public from algorithmic discrimination in a proactive and ongoing manner \nProactive assessment of equity in design. Those responsible for the development, use, or oversight of \nautomated systems should conduct proactive equity assessments in the design phase of the technology \nresearch and development or during its acquisition to review potential input data, associated historical \ncontext, accessibility for people with disabilities, and societal goals to identify potential discrimination and \neffects on equity resulting from the introduction of the technology. The assessed groups should be as inclusive \nas possible of the underserved communities mentioned in the equity definition:  Black, Latino, and Indigenous \nand Native American persons, Asian Americans and Pacific Islanders and other persons of color; members of \nreligious minorities; women, girls, and non-binary people; lesbian, gay, bisexual, transgender, queer, and inter-", "52a90a9b-df34-446c-99d7-913e6f4bffb5": "privacy, peaceful assembly, speech, or association, in a way that limits the exercise of civil rights or civil liber\u00ad\nties. Information about or algorithmically-determined assumptions related to identity should be carefully \nlimited if used to target or guide surveillance systems in order to avoid algorithmic discrimination; such iden\u00ad\ntity-related information includes group characteristics or affiliations, geographic designations, location-based \nand association-based inferences, social networks, and biometrics. Continuous surveillance and monitoring \nsystems should not be used in physical or digital workplaces (regardless of employment status), public educa\u00ad\ntional institutions, and public accommodations. Continuous surveillance and monitoring systems should not \nbe used in a way that has the effect of limiting access to critical resources or services or suppressing the exer\u00ad\ncise of rights, even where the organization is not under a particular duty to protect those rights.", "050a041d-1482-4d8c-afc2-0475b0eafa28": "validity and reasonable use of automated systems. \n\u2022\nA lawyer representing an older client with disabilities who had been cut off from Medicaid-funded home\nhealth-care assistance couldn't determine why, especially since the decision went against historical access\npractices. In a court hearing, the lawyer learned from a witness that the state in which the older client\nlived had recently adopted a new algorithm to determine eligibility.83 The lack of a timely explanation made it\nharder to understand and contest the decision.\n\u2022\nA formal child welfare investigation is opened against a parent based on an algorithm and without the parent\never being notified that data was being collected and used as part of an algorithmic child maltreatment\nrisk assessment.84 The lack of notice or an explanation makes it harder for those performing child\nmaltreatment assessments to validate the risk assessment and denies parents knowledge that could help them\ncontest a decision.\n41", "2b47e851-40e8-454f-b9d4-bcc6db94d988": "Rights form an overlapping set of backstops against potential harms. This purposefully overlapping \nframework, when taken as a whole, forms a blueprint to help protect the public from harm. \nThe measures taken to realize the vision set forward in this framework should be proportionate \nwith the extent and nature of the harm, or risk of harm, to people's rights, opportunities, and \naccess. \nRELATIONSHIP TO EXISTING LAW AND POLICY\nThe Blueprint for an AI Bill of Rights is an exercise in envisioning a future where the American public is \nprotected from the potential harms, and can fully enjoy the benefits, of automated systems. It describes princi\u00ad\nples that can help ensure these protections. Some of these protections are already required by the U.S. Constitu\u00ad\ntion or implemented under existing U.S. laws. For example, government surveillance, and data search and \nseizure are subject to legal requirements and judicial oversight. There are Constitutional requirements for", "4b3441f0-0254-424b-ba91-cba271cc448a": "34 \nMS-2.7-009 Regularly assess and verify that security measures remain e\ufb00ective and have not \nbeen compromised. \nInformation Security \nAI Actor Tasks: AI Deployment, AI Impact Assessment, Domain Experts, Operation and Monitoring, TEVV \n \nMEASURE 2.8: Risks associated with transparency and accountability \u2013 as identi\ufb01ed in the MAP function \u2013 are examined and \ndocumented. \nAction ID \nSuggested Action \nGAI Risks \nMS-2.8-001 \nCompile statistics on actual policy violations, take-down requests, and intellectual \nproperty infringement for organizational GAI systems: Analyze transparency \nreports across demographic groups, languages groups. \nIntellectual Property; Harmful Bias \nand Homogenization \nMS-2.8-002 Document the instructions given to data annotators or AI red-teamers. \nHuman-AI Con\ufb01guration \nMS-2.8-003 \nUse digital content transparency solutions to enable the documentation of each \ninstance where content is generated, modi\ufb01ed, or shared to provide a tamper-", "fe0a25b0-d293-453b-82a9-e3b1fa922e0a": "Formal Methods in the Field26 program supports research on rigorous formal verification and analysis of \nautomated systems and machine learning, and the Designing Accountable Software Systems27 program supports \nresearch on rigorous and reproducible methodologies for developing software systems with legal and regulatory \ncompliance in mind. \nSome state legislatures have placed strong transparency and validity requirements on \nthe use of pretrial risk assessments. The use of algorithmic pretrial risk assessments has been a \ncause of concern for civil rights groups.28 Idaho Code Section 19-1910, enacted in 2019,29 requires that any \npretrial risk assessment, before use in the state, first be \"shown to be free of bias against any class of \nindividuals protected from discrimination by state or federal law\", that any locality using a pretrial risk \nassessment must first formally validate the claim of its being free of bias, that \"all documents, records, and", "15634080-f043-4a89-8422-a66280a2b0e6": "technical standards and certi\ufb01cations \u2013 are de\ufb01ned, assessed, and documented. \nAction ID \nSuggested Action \nGAI Risks \nMP-3.4-001 \nEvaluate whether GAI operators and end-users can accurately understand \ncontent lineage and origin. \nHuman-AI Con\ufb01guration; \nInformation Integrity \nMP-3.4-002 Adapt existing training programs to include modules on digital content \ntransparency. \nInformation Integrity \nMP-3.4-003 Develop certi\ufb01cation programs that test pro\ufb01ciency in managing GAI risks and \ninterpreting content provenance, relevant to speci\ufb01c industry and context. \nInformation Integrity \nMP-3.4-004 Delineate human pro\ufb01ciency tests from tests of GAI capabilities. \nHuman-AI Con\ufb01guration \nMP-3.4-005 Implement systems to continually monitor and track the outcomes of human-GAI \ncon\ufb01gurations for future re\ufb01nement and improvements. \nHuman-AI Con\ufb01guration; \nInformation Integrity \nMP-3.4-006 \nInvolve the end-users, practitioners, and operators in GAI system in prototyping", "5c9c0bbc-8122-4c8c-986a-cdf7c4d63e34": "exam using biometric markers.73 These systems have the potential to limit student freedom to express a range\nof emotions at school and may inappropriately flag students with disabilities who need accommodations or\nuse screen readers or dictation software as cheating.74\n\u2022\nLocation data, acquired from a data broker, can be used to identify people who visit abortion clinics.75\n\u2022\nCompanies collect student data such as demographic information, free or reduced lunch status, whether\nthey've used drugs, or whether they've expressed interest in LGBTQI+ groups, and then use that data to \nforecast student success.76 Parents and education experts have expressed concern about collection of such\nsensitive data without express parental consent, the lack of transparency in how such data is being used, and\nthe potential for resulting discriminatory impacts.\n\u2022 Many employers transfer employee data to third party job verification services. This information is then used", "00048035-8497-42d2-80a6-8e8be91e9e20": "Human-AI Con\ufb01guration \nAI Actor Tasks: AI Development, AI Deployment, AI Impact Assessment, Operation and Monitoring \n \nMANAGE 2.2: Mechanisms are in place and applied to sustain the value of deployed AI systems. \nAction ID \nSuggested Action \nGAI Risks \nMG-2.2-001 \nCompare GAI system outputs against pre-de\ufb01ned organization risk tolerance, \nguidelines, and principles, and review and test AI-generated content against \nthese guidelines. \nCBRN Information or Capabilities; \nObscene, Degrading, and/or \nAbusive Content; Harmful Bias and \nHomogenization; Dangerous, \nViolent, or Hateful Content \nMG-2.2-002 \nDocument training data sources to trace the origin and provenance of AI-\ngenerated content. \nInformation Integrity \nMG-2.2-003 \nEvaluate feedback loops between GAI system content provenance and human \nreviewers, and update where needed. Implement real-time monitoring systems \nto a\ufb03rm that content provenance protocols remain e\ufb00ective.  \nInformation Integrity \nMG-2.2-004", "78698c18-fad9-4e5a-8247-59113eab63c6": "Model Cards for Model Reporting. In Proceedings of the Conference on Fairness, Accountability, and\nTransparency (FAT* '19). Association for Computing Machinery, New York, NY, USA, 220\u2013229. https://\ndl.acm.org/doi/10.1145/3287560.3287596\n90. Sarah Ammermann. Adverse Action Notice Requirements Under the ECOA and the FCRA. Consumer\nCompliance Outlook. Second Quarter 2013.\nhttps://consumercomplianceoutlook.org/2013/second-quarter/adverse-action-notice-requirements\u00ad\nunder-ecoa-fcra/\n91. Federal Trade Commission. Using Consumer Reports for Credit Decisions: What to Know About\nAdverse Action and Risk-Based Pricing Notices. Accessed May 2, 2022.\nhttps://www.ftc.gov/business-guidance/resources/using-consumer-reports-credit-decisions-what\u00ad\nknow-about-adverse-action-risk-based-pricing-notices#risk\n92. Consumer Financial Protection Bureau. CFPB Acts to Protect the Public from Black-Box Credit\nModels Using Complex Algorithms. May 26, 2022.", "4b917f4a-d442-4e69-a9a6-1ddff3471c4b": "\u2022 \nStage of the AI lifecycle: Risks can arise during design, development, deployment, operation, \nand/or decommissioning. \n\u2022 \nScope: Risks may exist at individual model or system levels, at the application or implementation \nlevels (i.e., for a speci\ufb01c use case), or at the ecosystem level \u2013 that is, beyond a single system or \norganizational context. Examples of the latter include the expansion of \u201calgorithmic \nmonocultures,3\u201d resulting from repeated use of the same model, or impacts on access to \nopportunity, labor markets, and the creative economies.4 \n\u2022 \nSource of risk: Risks may emerge from factors related to the design, training, or operation of the \nGAI model itself, stemming in some cases from GAI model or system inputs, and in other cases, \nfrom GAI system outputs. Many GAI risks, however, originate from human behavior, including \n \n \n3 \u201cAlgorithmic monocultures\u201d refers to the phenomenon in which repeated use of the same model or algorithm in", "8d05f043-5126-4ba3-841b-52609cbb7433": "interacting with external GAI technologies or service providers. Organizations can apply standard or \nexisting risk controls and processes to proprietary or open-source GAI technologies, data, and third-party \nservice providers, including acquisition and procurement due diligence, requests for software bills of \nmaterials (SBOMs), application of service level agreements (SLAs), and statement on standards for \nattestation engagement (SSAE) reports to help with third-party transparency and risk management for \nGAI systems. \nA.1.4. Pre-Deployment Testing \nOverview \nThe diverse ways and contexts in which GAI systems may be developed, used, and repurposed \ncomplicates risk mapping and pre-deployment measurement e\ufb00orts. Robust test, evaluation, validation, \nand veri\ufb01cation (TEVV) processes can be iteratively applied \u2013 and documented \u2013 in early stages of the AI \nlifecycle and informed by representative AI Actors (see Figure 3 of the AI RMF). Until new and rigorous", "76c4d456-13da-43be-890b-72a103ef2db3": "1 \n1. \nIntroduction \nThis document is a cross-sectoral pro\ufb01le of and companion resource for the AI Risk Management \nFramework (AI RMF 1.0) for Generative AI,1 pursuant to President Biden\u2019s Executive Order (EO) 14110 on \nSafe, Secure, and Trustworthy Arti\ufb01cial Intelligence.2 The AI RMF was released in January 2023, and is \nintended for voluntary use and to improve the ability of organizations to incorporate trustworthiness \nconsiderations into the design, development, use, and evaluation of AI products, services, and systems.  \nA pro\ufb01le is an implementation of the AI RMF functions, categories, and subcategories for a speci\ufb01c \nsetting, application, or technology \u2013 in this case, Generative AI (GAI) \u2013 based on the requirements, risk \ntolerance, and resources of the Framework user. AI RMF pro\ufb01les assist organizations in deciding how to \nbest manage AI risks in a manner that is well-aligned with their goals, considers legal/regulatory", "3db4d91b-029a-4782-8c7b-acecc3a4a75a": "Algorithmic \nDiscrimination \nProtections \nWHY THIS PRINCIPLE IS IMPORTANT\nThis section provides a brief summary of the problems which the principle seeks to address and protect \nagainst, including illustrative examples. \nThere is extensive evidence showing that automated systems can produce inequitable outcomes and amplify \nexisting inequity.30 Data that fails to account for existing systemic biases in American society can result in a range of \nconsequences. For example, facial recognition technology that can contribute to wrongful and discriminatory \narrests,31 hiring algorithms that inform discriminatory decisions, and healthcare algorithms that discount \nthe severity of certain diseases in Black Americans. Instances of discriminatory practices built into and \nresulting from AI and other automated systems exist across many industries, areas, and contexts. While automated \nsystems have the capacity to drive extraordinary advances and innovations, algorithmic discrimination", "29854fee-d0ae-47b0-9612-fceb12868283": "HUMAN ALTERNATIVES, \nCONSIDERATION, AND \nFALLBACK \nHOW THESE PRINCIPLES CAN MOVE INTO PRACTICE\nReal-life examples of how these principles can become reality, through laws, policies, and practical \ntechnical and sociotechnical approaches to protecting rights, opportunities, and access. \nHealthcare \u201cnavigators\u201d help people find their way through online signup forms to choose \nand obtain healthcare. A Navigator is \u201can individual or organization that's trained and able to help \nconsumers, small businesses, and their employees as they look for health coverage options through the \nMarketplace (a government web site), including completing eligibility and enrollment forms.\u201d106 For \nthe 2022 plan year, the Biden-Harris Administration increased funding so that grantee organizations could \n\u201ctrain and certify more than 1,500 Navigators to help uninsured consumers find affordable and comprehensive \nhealth coverage.\u201d107", "b83ad31a-ed48-4afc-9e7e-8561388c0a01": "of Artificial Intelligence Ethics for the Intelligence Community to guide personnel on whether and how to \ndevelop and use AI in furtherance of the IC's mission, as well as an AI Ethics Framework to help implement \nthese principles.22\nThe National Science Foundation (NSF) funds extensive research to help foster the \ndevelopment of automated systems that adhere to and advance their safety, security and \neffectiveness. Multiple NSF programs support research that directly addresses many of these principles: \nthe National AI Research Institutes23 support research on all aspects of safe, trustworthy, fair, and explainable \nAI algorithms and systems; the Cyber Physical Systems24 program supports research on developing safe \nautonomous and cyber physical systems with AI components; the Secure and Trustworthy Cyberspace25 \nprogram supports research on cybersecurity and privacy enhancing technologies in automated systems; the", "de752b0d-82c7-4ad6-b01d-86406280913d": "SAFE AND EFFECTIVE \nSYSTEMS \nWHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\nThe expectations for automated systems are meant to serve as a blueprint for the development of additional \ntechnical standards and practices that are tailored for particular sectors and contexts. \nOngoing monitoring. Automated systems should have ongoing monitoring procedures, including recalibra\u00ad\ntion procedures, in place to ensure that their performance does not fall below an acceptable level over time, \nbased on changing real-world conditions or deployment contexts, post-deployment modification, or unexpect\u00ad\ned conditions. This ongoing monitoring should include continuous evaluation of performance metrics and \nharm assessments, updates of any systems, and retraining of any machine learning models as necessary, as well \nas ensuring that fallback mechanisms are in place to allow reversion to a previously working system. Monitor\u00ad", "ebca47da-e839-4e2f-bea2-317ac8d5564c": "groups and have di\ufb03culty producing non-stereotyped content even when the prompt speci\ufb01cally \nrequests image features that are inconsistent with the stereotypes. Harmful bias in GAI models, which \nmay stem from their training data, can also cause representational harms or perpetuate or exacerbate \nbias based on race, gender, disability, or other protected classes.  \nHarmful bias in GAI systems can also lead to harms via disparities between how a model performs for \ndi\ufb00erent subgroups or languages (e.g., an LLM may perform less well for non-English languages or \ncertain dialects). Such disparities can contribute to discriminatory decision-making or ampli\ufb01cation of \nexisting societal biases. In addition, GAI systems may be inappropriately trusted to perform similarly \nacross all subgroups, which could leave the groups facing underperformance with worse outcomes than \nif no GAI system were used. Disparate or reduced performance for lower-resource languages also", "de9ab1ca-89c7-42ee-b32e-4c1c51b99ef7": "101. Andrew Kenney. 'I'm shocked that they need to have a smartphone': System for unemployment\nbenefits exposes digital divide. USA Today. May 2, 2021.\nhttps://www.usatoday.com/story/tech/news/2021/05/02/unemployment-benefits-system-leaving\u00ad\npeople-behind/4915248001/\n102. Allie Gross. UIA lawsuit shows how the state criminalizes the unemployed. Detroit Metro-Times.\nSep. 18, 2015.\nhttps://www.metrotimes.com/news/uia-lawsuit-shows-how-the-state-criminalizes-the\u00ad\nunemployed-2369412\n103. Maia Szalavitz. The Pain Was Unbearable. So Why Did Doctors Turn Her Away? Wired. Aug. 11,\n2021. https://www.wired.com/story/opioid-drug-addiction-algorithm-chronic-pain/\n104. Spencer Soper. Fired by Bot at Amazon: \"It's You Against the Machine\". Bloomberg, Jun. 28, 2021.\nhttps://www.bloomberg.com/news/features/2021-06-28/fired-by-bot-amazon-turns-to-machine\u00ad\nmanagers-and-workers-are-losing-out\n105. Definitions of \u2018equity\u2019 and \u2018underserved communities\u2019 can be found in the Definitions section of", "fc720adf-5fb7-4872-b139-9068225b9ec9": "42 \nMG-2.4-002 \nEstablish and maintain procedures for escalating GAI system incidents to the \norganizational risk management authority when speci\ufb01c criteria for deactivation \nor disengagement is met for a particular context of use or for the GAI system as a \nwhole. \nInformation Security \nMG-2.4-003 \nEstablish and maintain procedures for the remediation of issues which trigger \nincident response processes for the use of a GAI system, and provide stakeholders \ntimelines associated with the remediation plan. \nInformation Security \n \nMG-2.4-004 Establish and regularly review speci\ufb01c criteria that warrants the deactivation of \nGAI systems in accordance with set risk tolerances and appetites. \nInformation Security \n \nAI Actor Tasks: AI Deployment, Governance and Oversight, Operation and Monitoring \n \nMANAGE 3.1: AI risks and bene\ufb01ts from third-party resources are regularly monitored, and risk controls are applied and \ndocumented. \nAction ID \nSuggested Action \nGAI Risks \nMG-3.1-001", "10868542-61ec-47eb-ab65-71788898bc00": "Responsible AI Resource Center (AIRC), and added to The Language of Trustworthy AI: An In-Depth Glossary of \nTerms. \nThis document was also informed by public comments and consultations from several Requests for Information. \n \n2. \nOverview of Risks Unique to or Exacerbated by GAI \nIn the context of the AI RMF, risk refers to the composite measure of an event\u2019s probability (or \nlikelihood) of occurring and the magnitude or degree of the consequences of the corresponding event. \nSome risks can be assessed as likely to materialize in a given context, particularly those that have been \nempirically demonstrated in similar contexts. Other risks may be unlikely to materialize in a given \ncontext, or may be more speculative and therefore uncertain. \nAI risks can di\ufb00er from or intensify traditional software risks. Likewise, GAI can exacerbate existing AI \nrisks, and creates unique risks. GAI risks can vary along many dimensions: \n\u2022", "b99b4a4b-8d84-4830-86d5-d78ebfff7f8a": "teenager-2022-03-30/\n42. Miranda Bogen. All the Ways Hiring Algorithms Can Introduce Bias. Harvard Business Review. May\n6, 2019. https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias\n43. Arli Christian. Four Ways the TSA Is Making Flying Easier for Transgender People. American Civil\nLiberties Union. Apr. 5, 2022. https://www.aclu.org/news/lgbtq-rights/four-ways-the-tsa-is-making\u00ad\nflying-easier-for-transgender-people\n44. U.S. Transportation Security Administration. Transgender/ Non Binary / Gender Nonconforming\nPassengers. TSA. Accessed Apr. 21, 2022. https://www.tsa.gov/transgender-passengers\n45. See, e.g., National Disabled Law Students Association. Report on Concerns Regarding Online\nAdministration of Bar Exams. Jul. 29, 2020. https://ndlsa.org/wp-content/uploads/2020/08/\nNDLSA_Online-Exam-Concerns-Report1.pdf; Lydia X. Z. Brown. How Automated Test Proctoring\nSoftware Discriminates Against Disabled Students. Center for Democracy and Technology. Nov. 16, 2020.", "4f4414a0-d193-43d9-9f8d-d7d21770b1db": "apply to every suggested action in the subcategory (i.e., some apply to AI development and \nothers apply to AI deployment).  \nThe tables below begin with the AI RMF subcategory, shaded in blue, followed by suggested actions.  \n \nGOVERN 1.1: Legal and regulatory requirements involving AI are understood, managed, and documented.  \nAction ID \nSuggested Action \nGAI Risks \nGV-1.1-001 Align GAI development and use with applicable laws and regulations, including \nthose related to data privacy, copyright and intellectual property law. \nData Privacy; Harmful Bias and \nHomogenization; Intellectual \nProperty \nAI Actor Tasks: Governance and Oversight \n \n \n \n14 AI Actors are de\ufb01ned by the OECD as \u201cthose who play an active role in the AI system lifecycle, including \norganizations and individuals that deploy or operate AI.\u201d See Appendix A of the AI RMF for additional descriptions \nof AI Actors and AI Actor Tasks.", "39990922-0c0a-4008-a84a-ab498e27827f": "West, D. (2023) AI poses disproportionate risks to women. Brookings. \nhttps://www.brookings.edu/articles/ai-poses-disproportionate-risks-to-women/ \nWu, K. et al. (2024) How well do LLMs cite relevant medical references? An evaluation framework and \nanalyses. arXiv. https://arxiv.org/pdf/2402.02008 \nYin, L. et al. (2024) OpenAI\u2019s GPT Is A Recruiter\u2019s Dream Tool. Tests Show There\u2019s Racial Bias. Bloomberg. \nhttps://www.bloomberg.com/graphics/2024-openai-gpt-hiring-racial-discrimination/ \nYu, Z. et al. (March 2024) Don\u2019t Listen To Me: Understanding and Exploring Jailbreak Prompts of Large \nLanguage Models. arXiv. https://arxiv.org/html/2403.17336v1 \nZaugg, I. et al. (2022) Digitally-disadvantaged languages. Policy Review. \nhttps://policyreview.info/pdf/policyreview-2022-2-1654.pdf", "0159af88-d877-4a4a-8cd2-c1341841cb58": "but are not limited to: \n\u2022 \nParticipatory Engagement Methods: Methods used to solicit feedback from civil society groups, \na\ufb00ected communities, and users, including focus groups, small user studies, and surveys. \n\u2022 \nField Testing: Methods used to determine how people interact with, consume, use, and make \nsense of AI-generated information, and subsequent actions and e\ufb00ects, including UX, usability, \nand other structured, randomized experiments.  \n\u2022 \nAI Red-teaming: A structured testing exercise used to probe an AI system to \ufb01nd \ufb02aws and \nvulnerabilities such as inaccurate, harmful, or discriminatory outputs, often in a controlled \nenvironment and in collaboration with system developers. \nInformation gathered from structured public feedback can inform design, implementation, deployment \napproval, maintenance, or decommissioning decisions. Results and insights gleaned from these exercises \ncan serve multiple purposes, including improving data quality and preprocessing, bolstering governance", "62055a37-ec25-45b3-ba6c-327cd1a68fb4": "for individuals to be able to access any of their individual information stored in a federal system of records, if not \nincluded under one of the systems of records exempted pursuant to the Privacy Act. In these cases, federal agen\u00ad\ncies must provide a method for an individual to determine if their personal information is stored in a particular \nsystem of records, and must provide procedures for an individual to contest the contents of a record about them. \nFurther, the Privacy Act allows for a cause of action for an individual to seek legal relief if a federal agency does not \ncomply with the Privacy Act\u2019s requirements. Among other things, a court may order a federal agency to amend or \ncorrect an individual\u2019s information in its records or award monetary damages if an inaccurate, irrelevant, untimely, \nor incomplete record results in an adverse determination about an individual\u2019s \u201cqualifications, character, rights, \u2026 \nopportunities\u2026, or benefits.\u201d", "f2534337-c301-44f5-b42c-5472d130b0b2": "presents challenges to model adoption, inclusion, and accessibility, and may make preservation of \nendangered languages more di\ufb03cult if GAI systems become embedded in everyday processes that would \notherwise have been opportunities to use these languages.  \nBias is mutually reinforcing with the problem of undesired homogenization, in which GAI systems \nproduce skewed distributions of outputs that are overly uniform (for example, repetitive aesthetic styles", "fbee7ad0-9a74-472c-9305-bef84494cbac": "should be kept up-to-date and people impacted by the system should be notified of significant use case or key \nfunctionality changes. You should know how and why an outcome impacting you was determined by an \nautomated system, including when the automated system is not the sole input determining the outcome. \nAutomated systems should provide explanations that are technically valid, meaningful and useful to you and to \nany operators or others who need to understand the system, and calibrated to the level of risk based on the \ncontext. Reporting that includes summary information about these automated systems in plain language and \nassessments of the clarity and quality of the notice and explanations should be made public whenever possible. \n6", "ef45de44-4305-4bd2-9488-5cfefcb0e8f0": "for an AI Bill of Rights is fully consistent with these principles and with the direction in Executive Order 13985 \non Advancing Racial Equity and Support for Underserved Communities Through the Federal Government. \nThese principles find kinship in the Fair Information Practice Principles (FIPPs), derived from the 1973 report \nof an advisory committee to the U.S. Department of Health, Education, and Welfare, Records, Computers, \nand the Rights of Citizens.4 While there is no single, universal articulation of the FIPPs, these core \nprinciples for managing information about individuals have been incorporated into data privacy laws and \npolicies across the globe.5 The Blueprint for an AI Bill of Rights embraces elements of the FIPPs that are \nparticularly relevant to automated systems, without articulating a specific set of FIPPs or scoping \napplicability or the interests served to a single particular domain, like privacy, civil rights and civil liberties,", "9137db7a-37b4-4e69-bcdb-cb521f287b3e": "Reporting. Entities responsible for the development or use of automated systems should provide \nreporting of an appropriately designed algorithmic impact assessment,50 with clear specification of who \nperforms the assessment, who evaluates the system, and how corrective actions are taken (if necessary) in \nresponse to the assessment. This algorithmic impact assessment should include at least: the results of any \nconsultation, design stage equity assessments (potentially including qualitative analysis), accessibility \ndesigns and testing, disparity testing, document any remaining disparities, and detail any mitigation \nimplementation and assessments. This algorithmic impact assessment should be made public whenever \npossible. Reporting should be provided in a clear and machine-readable manner using plain language to \nallow for more straightforward public accountability. \n28\nAlgorithmic \nDiscrimination \nProtections", "f1df5b88-dbcd-43e5-9438-c511d20b3a85": "HUMAN ALTERNATIVES, \nCONSIDERATION, AND \nFALLBACK \nWHY THIS PRINCIPLE IS IMPORTANT\nThis section provides a brief summary of the problems which the principle seeks to address and protect \nagainst, including illustrative examples. \n\u2022\nAn unemployment benefits system in Colorado required, as a condition of accessing benefits, that applicants\nhave a smartphone in order to verify their identity. No alternative human option was readily available,\nwhich denied many people access to benefits.101\n\u2022\nA fraud detection system for unemployment insurance distribution incorrectly flagged entries as fraudulent,\nleading to people with slight discrepancies or complexities in their files having their wages withheld and tax\nreturns seized without any chance to explain themselves or receive a review by a person.102\n\u2022 A patient was wrongly denied access to pain medication when the hospital\u2019s software confused her medica\u00ad", "70eba8ef-45d4-4747-9f08-4658cbede511": "even if the inferences are not accurate (e.g., confabulations), and especially if they reveal information \nthat the individual considers sensitive or that is used to disadvantage or harm them. \nBeyond harms from information exposure (such as extortion or dignitary harm), wrong or inappropriate \ninferences of PII can contribute to downstream or secondary harmful impacts. For example, predictive \ninferences made by GAI models based on PII or protected attributes can contribute to adverse decisions, \nleading to representational or allocative harms to individuals or groups (see Harmful Bias and \nHomogenization below).", "45015a61-5cbb-4192-a277-099739b8931d": "NOTICE & \nEXPLANATION \nWHY THIS PRINCIPLE IS IMPORTANT\nThis section provides a brief summary of the problems which the principle seeks to address and protect \nagainst, including illustrative examples. \nAutomated systems now determine opportunities, from employment to credit, and directly shape the American \npublic\u2019s experiences, from the courtroom to online classrooms, in ways that profoundly impact people\u2019s lives. But this \nexpansive impact is not always visible. An applicant might not know whether a person rejected their resume or a \nhiring algorithm moved them to the bottom of the list. A defendant in the courtroom might not know if a judge deny\u00ad\ning their bail is informed by an automated system that labeled them \u201chigh risk.\u201d From correcting errors to contesting \ndecisions, people are often denied the knowledge they need to address the impact of automated systems on their lives.", "0614bcc7-9305-496b-bd3e-a1802f15a833": "and a human who is interacting with it. Humans bring their unique perspectives, experiences, or domain-\nspeci\ufb01c expertise to interactions with AI systems but may not have detailed knowledge of AI systems and \nhow they work. As a result, human experts may be unnecessarily \u201caverse\u201d to GAI systems, and thus \ndeprive themselves or others of GAI\u2019s bene\ufb01cial uses.  \nConversely, due to the complexity and increasing reliability of GAI technology, over time, humans may \nover-rely on GAI systems or may unjusti\ufb01ably perceive GAI content to be of higher quality than that \nproduced by other sources. This phenomenon is an example of automation bias, or excessive deference \nto automated systems. Automation bias can exacerbate other risks of GAI, such as risks of confabulation \nor risks of bias or homogenization. \nThere may also be concerns about emotional entanglement between humans and GAI systems, which \ncould lead to negative psychological impacts.", "3ba1fc2a-6637-4894-9ed8-e02f197b2e39": "and mitigation proportionate with those impacts. Automated systems with the intended purpose of violating \nthe safety of others should not be developed or used; systems with such safety violations as identified unin\u00ad\ntended consequences should not be used until the risk can be mitigated. Ongoing risk mitigation may necessi\u00ad\ntate rollback or significant modification to a launched automated system. \n18", "a0ca0e56-c1af-4533-a94f-456e90ab52f4": "SECTION TITLE\nDATA PRIVACY\nYou should be protected from abusive data practices via built-in protections and you \nshould have agency over how data about you is used. You should be protected from violations of \nprivacy through design choices that ensure such protections are included by default, including ensuring that \ndata collection conforms to reasonable expectations and that only data strictly necessary for the specific \ncontext is collected. Designers, developers, and deployers of automated systems should seek your permission \nand respect your decisions regarding collection, use, access, transfer, and deletion of your data in appropriate \nways and to the greatest extent possible; where not possible, alternative privacy by design safeguards should be \nused. Systems should not employ user experience and design decisions that obfuscate user choice or burden \nusers with defaults that are privacy invasive. Consent should only be used to justify collection of data in cases", "f2565463-e689-404b-8348-06ab3fef9462": "Information Integrity \nMG-2.2-004 \nEvaluate GAI content and data for representational biases and employ \ntechniques such as re-sampling, re-ranking, or adversarial training to mitigate \nbiases in the generated content. \nInformation Security; Harmful Bias \nand Homogenization \nMG-2.2-005 \nEngage in due diligence to analyze GAI output for harmful content, potential \nmisinformation, and CBRN-related or NCII content. \nCBRN Information or Capabilities; \nObscene, Degrading, and/or \nAbusive Content; Harmful Bias and \nHomogenization; Dangerous, \nViolent, or Hateful Content", "e24cd6c2-55a9-4c13-994c-7aa012bae660": "requests should be used so that users understand for what use contexts, time span, and entities they are \nproviding data and metadata consent. User experience research should be performed to ensure these consent \nrequests meet performance standards for readability and comprehension. This includes ensuring that consent \nrequests are accessible to users with disabilities and are available in the language(s) and reading level appro\u00ad\npriate for the audience.  User experience design choices that intentionally obfuscate or manipulate user \nchoice (i.e., \u201cdark patterns\u201d) should be not be used. \n34", "695adda2-bf04-4a04-9e8d-646121be4bbc": "3 \nthe abuse, misuse, and unsafe repurposing by humans (adversarial or not), and others result \nfrom interactions between a human and an AI system.  \n\u2022 \nTime scale: GAI risks may materialize abruptly or across extended periods. Examples include \nimmediate (and/or prolonged) emotional harm and potential risks to physical safety due to the \ndistribution of harmful deepfake images, or the long-term e\ufb00ect of disinformation on societal \ntrust in public institutions. \nThe presence of risks and where they fall along the dimensions above will vary depending on the \ncharacteristics of the GAI model, system, or use case at hand. These characteristics include but are not \nlimited to GAI model or system architecture, training mechanisms and libraries, data types used for \ntraining or \ufb01ne-tuning, levels of model access or availability of model weights, and application or use \ncase context. \nOrganizations may choose to tailor how they measure GAI risks based on these characteristics. They may", "fbac8185-c770-4b0d-bb3b-cdb1deafa299": "Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government (December 2020). \nThis white paper recognizes that national security (which includes certain law enforcement and \nhomeland security activities) and defense activities are of increased sensitivity and interest to our nation\u2019s \nadversaries and are often subject to special requirements, such as those governing classified information and \nother protected data. Such activities require alternative, compatible safeguards through existing policies that \ngovern automated systems and AI, such as the Department of Defense (DOD) AI Ethical Principles and \nResponsible AI Implementation Pathway and the Intelligence Community (IC) AI Ethics Principles and \nFramework. The implementation of these policies to national security and defense activities can be informed by \nthe Blueprint for an AI Bill of Rights where feasible. \nThe Blueprint for an AI Bill of Rights is not intended to, and does not, create any legal right, benefit, or", "6f2b4b9f-4cac-46f9-99ef-3bc4cb1aaf37": "taking place regarding the use or emulation of personal identity, likeness, or voice without permission.  \nTrustworthy AI Characteristics: Accountable and Transparent, Fair with Harmful Bias Managed, Privacy \nEnhanced  \n2.11. \nObscene, Degrading, and/or Abusive Content \nGAI can ease the production of and access to illegal non-consensual intimate imagery (NCII) of adults, \nand/or child sexual abuse material (CSAM). GAI-generated obscene, abusive or degrading content can \ncreate privacy, psychological and emotional, and even physical harms, and in some cases may be illegal.  \nGenerated explicit or obscene AI content may include highly realistic \u201cdeepfakes\u201d of real individuals, \nincluding children. The spread of this kind of material can have downstream negative consequences: in \nthe context of CSAM, even if the generated images do not resemble speci\ufb01c individuals, the prevalence \nof such images can divert time and resources from e\ufb00orts to \ufb01nd real-world victims. Outside of CSAM,", "54c7a44a-c1ee-4ef5-b189-1ef365323d0b": "records and education-related data in order to do so. The overarching concerns of surveillance in these \ndomains included concerns about the chilling effects of surveillance on student expression, inappropriate \ncontrol of tenants via surveillance, and the way that surveillance of workers blurs the boundary between work \nand life and exerts extreme and potentially damaging control over workers' lives. Additionally, some panelists \npointed out ways that data from one situation was misapplied in another in a way that limited people's \nopportunities, for example data from criminal justice settings or previous evictions being used to block further \naccess to housing. Throughout, various panelists emphasized that these technologies are being used to shift the \nburden of oversight and efficiency from employers to workers, schools to students, and landlords to tenants, in \nways that diminish and encroach on equality of opportunity; assessment of these technologies should include", "1742ef3f-905c-4f93-b448-e55fe12fd9df": "human review of criminal investigative matters and statutory requirements for judicial review. Civil rights laws \nprotect the American people against discrimination. \n8", "ed0d3bdd-4d2e-4e05-acd1-0bbb37d3c500": "and testing activities. Make sure these tests cover various scenarios, such as crisis \nsituations or ethically sensitive contexts. \nHuman-AI Con\ufb01guration; \nInformation Integrity; Harmful Bias \nand Homogenization; Dangerous, \nViolent, or Hateful Content \nAI Actor Tasks: AI Design, AI Development, Domain Experts, End-Users, Human Factors, Operation and Monitoring", "a4951da4-180d-4dde-b64b-6b70ab5c71e7": "detailed steps toward actualizing these principles in the technological design process. These principles help \nprovide guidance whenever automated systems can meaningfully impact the public\u2019s rights, opportunities, \nor access to critical needs. \n3", "573cc872-ae49-416d-8065-83f04ba76d18": "72. Jack Gillum and Jeff Kao. Aggression Detectors: The Unproven, Invasive Surveillance Technology\nSchools are Using to Monitor Students. ProPublica. Jun. 25, 2019.\nhttps://features.propublica.org/aggression-detector/the-unproven-invasive-surveillance-technology\u00ad\nschools-are-using-to-monitor-students/\n73. Drew Harwell. Cheating-detection companies made millions during the pandemic. Now students are\nfighting back. Washington Post. Nov. 12, 2020.\nhttps://www.washingtonpost.com/technology/2020/11/12/test-monitoring-student-revolt/\n74. See, e.g., Heather Morrison. Virtual Testing Puts Disabled Students at a Disadvantage. Government\nTechnology. May 24, 2022.\nhttps://www.govtech.com/education/k-12/virtual-testing-puts-disabled-students-at-a-disadvantage;\nLydia X. Z. Brown, Ridhi Shetty, Matt Scherer, and Andrew Crawford. Ableism And Disability\nDiscrimination In New Surveillance Technologies: How new surveillance technologies in education,", "9322efea-331d-4996-9474-cccaa4df697d": "APPENDIX\n\u2022 OSTP conducted meetings with a variety of stakeholders in the private sector and civil society. Some of these\nmeetings were specifically focused on providing ideas related to the development of the Blueprint for an AI\nBill of Rights while others provided useful general context on the positive use cases, potential harms, and/or\noversight possibilities for these technologies. Participants in these conversations from the private sector and\ncivil society included:\nAdobe \nAmerican Civil Liberties Union \n(ACLU) \nThe Aspen Commission on \nInformation Disorder \nThe Awood Center \nThe Australian Human Rights \nCommission \nBiometrics Institute \nThe Brookings Institute \nBSA | The Software Alliance \nCantellus Group \nCenter for American Progress \nCenter for Democracy and \nTechnology \nCenter on Privacy and Technology \nat Georgetown Law \nChristiana Care \nColor of Change \nCoworker \nData Robot \nData Trust Alliance \nData and Society Research Institute \nDeepmind \nEdSAFE AI Alliance \nElectronic Privacy Information", "b4e35127-be78-433a-b6aa-b7e222864503": "ed by default. Privacy risks should be assessed throughout the development life cycle, including privacy risks \nfrom reidentification, and appropriate technical and policy mitigation measures should be implemented. This \nincludes potential harms to those who are not users of the automated system, but who may be harmed by \ninferred data, purposeful privacy violations, or community surveillance or other community harms. Data \ncollection should be minimized and clearly communicated to the people whose data is collected. Data should \nonly be collected or used for the purposes of training or testing machine learning models if such collection and \nuse is legal and consistent with the expectations of the people whose data is collected. User experience \nresearch should be conducted to confirm that people understand what data is being collected about them and \nhow it will be used, and that this collection matches their expectations and desires.", "20f0980c-bd47-44c4-b835-82832c82da3b": "construed broadly. An explanation need not be a plain-language statement about causality but could consist of \nany mechanism that allows the recipient to build the necessary understanding and intuitions to achieve the \nstated purpose. Tailoring should be assessed (e.g., via user experience research). \nTailored to the target of the explanation. Explanations should be targeted to specific audiences and \nclearly state that audience. An explanation provided to the subject of a decision might differ from one provided \nto an advocate, or to a domain expert or decision maker. Tailoring should be assessed (e.g., via user experience \nresearch). \n43", "ab80b8f9-d569-40f7-a6e3-8d305b06893a": "intended to imply that the entities, materials, or equipment are necessarily the best available for the \npurpose. Any mention of commercial, non-pro\ufb01t, academic partners, or their products, or references is \nfor information only; it is not intended to imply endorsement or recommendation by any U.S. \nGovernment agency.", "410d1dad-982f-4e6c-acfc-8c4393c47fb4": "and Homogenization \nAI Actor Tasks: AI Deployment, AI Impact Assessment, Domain Experts, End-Users, Operation and Monitoring, TEVV \n \nMEASURE 2.10: Privacy risk of the AI system \u2013 as identi\ufb01ed in the MAP function \u2013 is examined and documented. \nAction ID \nSuggested Action \nGAI Risks \nMS-2.10-001 \nConduct AI red-teaming to assess issues such as: Outputting of training data \nsamples, and subsequent reverse engineering, model extraction, and \nmembership inference risks; Revealing biometric, con\ufb01dential, copyrighted, \nlicensed, patented, personal, proprietary, sensitive, or trade-marked information; \nTracking or revealing location information of users or members of training \ndatasets. \nHuman-AI Con\ufb01guration; \nInformation Integrity; Intellectual \nProperty \nMS-2.10-002 \nEngage directly with end-users and other stakeholders to understand their \nexpectations and concerns regarding content provenance. Use this feedback to \nguide the design of provenance data-tracking techniques. \nHuman-AI Con\ufb01guration;", "31f4ccdf-832e-4dfa-96e7-a006d2b27a92": "DATA PRIVACY \nWHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\nThe expectations for automated systems are meant to serve as a blueprint for the development of additional \ntechnical standards and practices that are tailored for particular sectors and contexts. \nTraditional terms of service\u2014the block of text that the public is accustomed to clicking through when using a web\u00ad\nsite or digital app\u2014are not an adequate mechanism for protecting privacy. The American public should be protect\u00ad\ned via built-in privacy protections, data minimization, use and collection limitations, and transparency, in addition \nto being entitled to clear mechanisms to control access to and use of their data\u2014including their metadata\u2014in a \nproactive, informed, and ongoing way. Any automated system collecting, using, sharing, or storing personal data \nshould meet these expectations. \nProtect privacy by design and by default \nPrivacy by design and by default. Automated systems should be designed and built with privacy protect\u00ad", "2542b1d9-a513-4744-a0e8-2073dd6969bf": "Human-AI Con\ufb01guration; \nInformation Integrity \nMS-2.10-003 Verify deduplication of GAI training data samples, particularly regarding synthetic \ndata. \nHarmful Bias and Homogenization \nAI Actor Tasks: AI Deployment, AI Impact Assessment, Domain Experts, End-Users, Operation and Monitoring, TEVV", "97dc3796-6c1d-4071-a96e-444a6e76f758": "other countries. \nWe have seen modest progress in recent years, with some state and local governments responding to these prob\u00ad\nlems with legislation, and some courts extending longstanding statutory protections to new and emerging tech\u00ad\nnologies. There are companies working to incorporate additional protections in their design and use of auto\u00ad\nmated systems, and researchers developing innovative guardrails. Advocates, researchers, and government \norganizations have proposed principles for the ethical use of AI and other automated systems. These include \nthe Organization for Economic Co-operation and Development\u2019s (OECD\u2019s) 2019 Recommendation on Artificial \nIntelligence, which includes principles for responsible stewardship of trustworthy AI and which the United \nStates adopted, and Executive Order 13960 on Promoting the Use of Trustworthy Artificial Intelligence in the \nFederal Government, which sets out principles that govern the federal government\u2019s use of AI. The Blueprint", "a15c2582-15b2-4587-b765-f5f0457f9f91": "automated systems in an equitable way. The guardrails protecting the public from discrimination in their daily \nlives should include their digital lives and impacts\u2014basic safeguards against abuse, bias, and discrimination to \nensure that all people are treated fairly when automated systems are used. This includes all dimensions of their \nlives, from hiring to loan approvals, from medical treatment and payment to encounters with the criminal \njustice system. Ensuring equity should also go beyond existing guardrails to consider the holistic impact that \nautomated systems make on underserved communities and to institute proactive protections that support these \ncommunities. \n\u2022\nAn automated system using nontraditional factors such as educational attainment and employment history as\npart of its loan underwriting and pricing model was found to be much more likely to charge an applicant who\nattended a Historically Black College or University (HBCU) higher loan prices for refinancing a student loan", "93c33081-e2b6-4d06-afb4-8419e8ac265e": "25 \nMP-2.3-002 Review and document accuracy, representativeness, relevance, suitability of data \nused at di\ufb00erent stages of AI life cycle. \nHarmful Bias and Homogenization; \nIntellectual Property \nMP-2.3-003 \nDeploy and document fact-checking techniques to verify the accuracy and \nveracity of information generated by GAI systems, especially when the \ninformation comes from multiple (or unknown) sources. \nInformation Integrity  \nMP-2.3-004 Develop and implement testing techniques to identify GAI produced content (e.g., \nsynthetic media) that might be indistinguishable from human-generated content. Information Integrity \nMP-2.3-005 Implement plans for GAI systems to undergo regular adversarial testing to identify \nvulnerabilities and potential manipulation or misuse. \nInformation Security \nAI Actor Tasks: AI Development, Domain Experts, TEVV \n \nMAP 3.4: Processes for operator and practitioner pro\ufb01ciency with AI system performance and trustworthiness \u2013 and relevant", "07584cae-264c-4ad9-abdf-caa426b1af9d": "Meaningful access to examine the system. Designers, developers, and deployers of automated \nsystems should consider limited waivers of confidentiality (including those related to trade secrets) where \nnecessary in order to provide meaningful oversight of systems used in sensitive domains, incorporating mea\u00ad\nsures to protect intellectual property and trade secrets from unwarranted disclosure as appropriate. This \nincludes (potentially private and protected) meaningful access to source code, documentation, and related \ndata during any associated legal discovery, subject to effective confidentiality or court orders. Such meaning\u00ad\nful access should include (but is not limited to) adhering to the principle on Notice and Explanation using the \nhighest level of risk so the system is designed with built-in explanations; such systems should use fully-trans\u00ad\nparent models where the model itself can be understood by people needing to directly examine it.", "354bd225-ca88-41ce-8470-abeebfc7da3b": "orientation), religion, age, national origin, disability, veteran status, genetic information, or any other \nclassification protected by law. Depending on the specific circumstances, such algorithmic discrimination \nmay violate legal protections. Designers, developers, and deployers of automated systems should take \nproactive \nand \ncontinuous \nmeasures \nto \nprotect \nindividuals \nand \ncommunities \nfrom algorithmic \ndiscrimination and to use and design systems in an equitable way. This protection should include proactive \nequity assessments as part of the system design, use of representative data and protection against proxies \nfor demographic features, ensuring accessibility for people with disabilities in design and development, \npre-deployment and ongoing disparity testing and mitigation, and clear organizational oversight. Independent \nevaluation and plain language reporting in the form of an algorithmic impact assessment, including", "9cd96ad0-9958-440d-ac65-a2b4614d7539": "courts have found that such cure procedures are constitutionally required.110 \nBallot \ncuring processes vary among states, and include direct phone calls, emails, or mail contact by election \nofficials.111 Voters are asked to provide alternative information or a new signature to verify the validity of their \nballot. \n52", "73903c5d-1dba-43d0-b85d-443cf758da6c": "a system to counter discrimination) runs a high risk of leading to algorithmic discrimination and should be \navoided. In many cases, attributes that are highly correlated with demographic features, known as proxies, can \ncontribute to algorithmic discrimination. In cases where use of the demographic features themselves would \nlead to illegal algorithmic discrimination, reliance on such proxies in decision-making (such as that facilitated \nby an algorithm) may also be prohibited by law. Proactive testing should be performed to identify proxies by \ntesting for correlation between demographic information and attributes in any data used as part of system \ndesign, development, or use. If a proxy is identified, designers, developers, and deployers should remove the \nproxy; if needed, it may be possible to identify alternative attributes that can be used instead. At a minimum, \norganizations should ensure a proxy feature is not given undue weight and should monitor the system closely", "9a9a9238-61cf-4a36-afef-3d7c4632f4ae": "awareness of their limitations in the context(s) of use; Standard measurement \nand structured human feedback approaches; Anticipated human-AI \ncon\ufb01gurations. \nHuman-AI Con\ufb01guration; Harmful \nBias and Homogenization; \nDangerous, Violent, or Hateful \nContent \nMP-1.1-004 \nIdentify and document foreseeable illegal uses or applications of the GAI system \nthat surpass organizational risk tolerances. \nCBRN Information or Capabilities; \nDangerous, Violent, or Hateful \nContent; Obscene, Degrading, \nand/or Abusive Content \nAI Actor Tasks: AI Deployment \n \nMAP 1.2: Interdisciplinary AI Actors, competencies, skills, and capacities for establishing context re\ufb02ect demographic diversity and \nbroad domain and user experience expertise, and their participation is documented. Opportunities for interdisciplinary \ncollaboration are prioritized. \nAction ID \nSuggested Action \nGAI Risks \nMP-1.2-001 \nEstablish and empower interdisciplinary teams that re\ufb02ect a wide range of", "3ab19783-41cc-4d8b-9dd5-65034b1c3360": "on democratic processes, unknown long-term performance characteristics of GAI. \nInformation Integrity; Dangerous, \nViolent, or Hateful Content; CBRN \nInformation or Capabilities \nGV-1.3-007 Devise a plan to halt development or deployment of a GAI system that poses \nunacceptable negative risk. \nCBRN Information and Capability; \nInformation Security; Information \nIntegrity \nAI Actor Tasks: Governance and Oversight \n \nGOVERN 1.4: The risk management process and its outcomes are established through transparent policies, procedures, and other \ncontrols based on organizational risk priorities. \nAction ID \nSuggested Action \nGAI Risks \nGV-1.4-001 \nEstablish policies and mechanisms to prevent GAI systems from generating \nCSAM, NCII or content that violates the law.  \nObscene, Degrading, and/or \nAbusive Content; Harmful Bias \nand Homogenization; \nDangerous, Violent, or Hateful \nContent \nGV-1.4-002 \nEstablish transparent acceptable use policies for GAI that address illegal use or \napplications of GAI.", "eadf745e-b710-4384-9248-a774a534b3da": "GOVERN 2.1: Roles and responsibilities and lines of communication related to mapping, measuring, and managing AI risks are \ndocumented and are clear to individuals and teams throughout the organization. \nAction ID \nSuggested Action \nGAI Risks \nGV-2.1-001 \nEstablish organizational roles, policies, and procedures for communicating GAI \nincidents and performance to AI Actors and downstream stakeholders (including \nthose potentially impacted), via community or o\ufb03cial resources (e.g., AI incident \ndatabase, AVID, CVE, NVD, or OECD AI incident monitor). \nHuman-AI Con\ufb01guration; Value \nChain and Component Integration \nGV-2.1-002 Establish procedures to engage teams for GAI system incident response with \ndiverse composition and responsibilities based on the particular incident type. \nHarmful Bias and Homogenization \nGV-2.1-003 Establish processes to verify the AI Actors conducting GAI incident response tasks \ndemonstrate and maintain the appropriate skills and training. \nHuman-AI Con\ufb01guration", "95c4db5f-ccbc-4cb6-937b-2e6690f89320": "ately to identified risks. Appropriate responses include determining not to process data when the privacy risks \noutweigh the benefits or implementing measures to mitigate acceptable risks. Appropriate responses do not \ninclude sharing or transferring the privacy risks to users via notice or consent requests where users could not \nreasonably be expected to understand the risks without further support. \nPrivacy-preserving security. Entities creating, using, or governing automated systems should follow \nprivacy and security best practices designed to ensure data and metadata do not leak beyond the specific \nconsented use case. Best practices could include using privacy-enhancing cryptography or other types of \nprivacy-enhancing technologies or fine-grained permissions and access control mechanisms, along with \nconventional system security protocols. \n33", "28b833ba-4e82-47fc-9206-2b9e593d4569": "Summaries of Panel Discussions: \nPanel 1: Consumer Rights and Protections. This event explored the opportunities and challenges for \nindividual consumers and communities in the context of a growing ecosystem of AI-enabled consumer \nproducts, advanced platforms and services, \u201cInternet of Things\u201d (IoT) devices, and smart city products and \nservices. \nWelcome:\n\u2022\nRashida Richardson, Senior Policy Advisor for Data and Democracy, White House Office of Science and\nTechnology Policy\n\u2022\nKaren Kornbluh, Senior Fellow and Director of the Digital Innovation and Democracy Initiative, German\nMarshall Fund\nModerator: \nDevin E. Willis, Attorney, Division of Privacy and Identity Protection, Bureau of Consumer Protection, Federal \nTrade Commission \nPanelists: \n\u2022\nTamika L. Butler, Principal, Tamika L. Butler Consulting\n\u2022\nJennifer Clark, Professor and Head of City and Regional Planning, Knowlton School of Engineering, Ohio\nState University\n\u2022\nCarl Holshouser, Senior Vice President for Operations and Strategic Initiatives, TechNet", "38bddc3e-d00f-4b32-8f06-51bf7ee089bd": "ENDNOTES\n96. National Science Foundation. NSF Program on Fairness in Artificial Intelligence in Collaboration\nwith Amazon (FAI). Accessed July 20, 2022.\nhttps://www.nsf.gov/pubs/2021/nsf21585/nsf21585.htm\n97. Kyle Wiggers. Automatic signature verification software threatens to disenfranchise U.S. voters.\nVentureBeat. Oct. 25, 2020.\nhttps://venturebeat.com/2020/10/25/automatic-signature-verification-software-threatens-to\u00ad\ndisenfranchise-u-s-voters/\n98. Ballotpedia. Cure period for absentee and mail-in ballots. Article retrieved Apr 18, 2022.\nhttps://ballotpedia.org/Cure_period_for_absentee_and_mail-in_ballots\n99. Larry Buchanan and Alicia Parlapiano. Two of these Mail Ballot Signatures are by the Same Person.\nWhich Ones? New York Times. Oct. 7, 2020.\nhttps://www.nytimes.com/interactive/2020/10/07/upshot/mail-voting-ballots-signature\u00ad\nmatching.html\n100. Rachel Orey and Owen Bacskai. The Low Down on Ballot Curing. Nov. 04, 2020.\nhttps://bipartisanpolicy.org/blog/the-low-down-on-ballot-curing/", "2524a0ed-cf1b-48e3-a937-7968cf441df0": "Confabulation; Information \nSecurity \nMS-2.3-003 Share results of pre-deployment testing with relevant GAI Actors, such as those \nwith system release approval authority. \nHuman-AI Con\ufb01guration", "30631e3d-b2e2-4cd1-a586-710dc192aae0": "Administration Review. Vol. 39, No. 4. Jul.-Aug., 1979. https://www.jstor.org/stable/976213?seq=1\n16. The US Department of Transportation has publicly described the health and other benefits of these\n\u201ctraffic calming\u201d measures. See, e.g.: U.S. Department of Transportation. Traffic Calming to Slow Vehicle\nSpeeds. Accessed Apr. 17, 2022. https://www.transportation.gov/mission/health/Traffic-Calming-to-Slow\u00ad\nVehicle-Speeds\n17. Karen Hao. Worried about your firm\u2019s AI ethics? These startups are here to help.\nA growing ecosystem of \u201cresponsible AI\u201d ventures promise to help organizations monitor and fix their AI\nmodels. MIT Technology Review. Jan 15., 2021.\nhttps://www.technologyreview.com/2021/01/15/1016183/ai-ethics-startups/; Disha Sinha. Top Progressive\nCompanies Building Ethical AI to Look Out for in 2021. Analytics Insight. June 30, 2021. https://\nwww.analyticsinsight.net/top-progressive-companies-building-ethical-ai-to-look-out-for\u00ad", "4495ecb5-1247-453e-aa68-1f4395d7fa9b": "Lee, H. et al. (2024) Deepfakes, Phrenology, Surveillance, and More! A Taxonomy of AI Privacy Risks. \narXiv. https://arxiv.org/pdf/2310.07879 \nLenaerts-Bergmans, B. (2024) Data Poisoning: The Exploitation of Generative AI. Crowdstrike. \nhttps://www.crowdstrike.com/cybersecurity-101/cyberattacks/data-poisoning/ \nLiang, W. et al. (2023) GPT detectors are biased against non-native English writers. arXiv. \nhttps://arxiv.org/abs/2304.02819 \nLuccioni, A. et al. (2023) Power Hungry Processing: Watts Driving the Cost of AI Deployment? arXiv. \nhttps://arxiv.org/pdf/2311.16863 \nMouton, C. et al. (2024) The Operational Risks of AI in Large-Scale Biological Attacks. RAND. \nhttps://www.rand.org/pubs/research_reports/RRA2977-2.html. \nNicoletti, L. et al. (2023) Humans Are Biased. Generative Ai Is Even Worse. Bloomberg. \nhttps://www.bloomberg.com/graphics/2023-generative-ai-bias/. \nNational Institute of Standards and Technology (2024) Adversarial Machine Learning: A Taxonomy and", "6c879ac1-2edb-4dc7-aa39-4b70b06464e0": "rograms, and surveillance of classes (whether online or in-person); \nHousing-related systems such as tenant screening algorithms, automated valuation systems that  \n    estimate the value of homes used in mortgage underwriting or home insurance, and automated  \n    valuations from online aggregator websites; and \nEmployment-related systems such as workplace algorithms that inform all aspects of the terms  \n    and conditions of employment including, but not limited to, pay or promotion, hiring or termina- \n   tion algorithms, virtual or augmented reality workplace training programs, and electronic work \nplace surveillance and management systems. \n\u2022 Access to critical resources and services, including but not limited to:\nHealth  and health insurance technologies such as medical AI systems and devices, AI-assisted \n    diagnostic tools, algorithms or predictive models used to support clinical decision making, medical", "35c66776-cca0-4456-a747-9298ba25ad21": "information used to build or validate the risk assessment shall be open to public inspection,\" and that assertions \nof trade secrets cannot be used \"to quash discovery in a criminal matter by a party to a criminal case.\" \n22", "7ce689a3-f85d-494d-895c-ec39ee9cf4c1": "Data collection and use-case scope limits. Data collection should be limited in scope, with specific, \nnarrow identified goals, to avoid \"mission creep.\"  Anticipated data collection should be determined to be \nstrictly necessary to the identified goals and should be minimized as much as possible. Data collected based on \nthese identified goals and for a specific context should not be used in a different context without assessing for \nnew privacy risks and implementing appropriate mitigation measures, which may include express consent. \nClear timelines for data retention should be established, with data deleted as soon as possible in accordance \nwith legal or policy-based limitations. Determined data retention timelines should be documented and justi\u00ad\nfied. \nRisk identification and mitigation. Entities that collect, use, share, or store sensitive data should \nattempt to proactively identify harms and seek to manage them so as to avoid, mitigate, and respond appropri\u00ad", "4094bae5-4a0f-4a9a-9b12-570c472171b2": "13 \n\u2022 \nNot every suggested action applies to every AI Actor14 or is relevant to every AI Actor Task. For \nexample, suggested actions relevant to GAI developers may not be relevant to GAI deployers. \nThe applicability of suggested actions to relevant AI actors should be determined based on \norganizational considerations and their unique uses of GAI systems. \nEach table of suggested actions includes: \n\u2022 \nAction ID: Each Action ID corresponds to the relevant AI RMF function and subcategory (e.g., GV-\n1.1-001 corresponds to the \ufb01rst suggested action for Govern 1.1, GV-1.1-002 corresponds to the \nsecond suggested action for Govern 1.1). AI RMF functions are tagged as follows: GV = Govern; \nMP = Map; MS = Measure; MG = Manage. \n\u2022 \nSuggested Action: Steps an organization or AI actor can take to manage GAI risks.  \n\u2022 \nGAI Risks: Tags linking suggested actions with relevant GAI risks.  \n\u2022 \nAI Actor Tasks: Pertinent AI Actor Tasks for each subcategory. Not every AI Actor Task listed will", "55a2ceec-a531-4aac-946c-eabc0b541811": "Suggested Action \nGAI Risks \nMP-2.2-001 \nIdentify and document how the system relies on upstream data sources, \nincluding for content provenance, and if it serves as an upstream dependency for \nother systems. \nInformation Integrity; Value Chain \nand Component Integration \nMP-2.2-002 \nObserve and analyze how the GAI system interacts with external networks, and \nidentify any potential for negative externalities, particularly where content \nprovenance might be compromised. \nInformation Integrity \nAI Actor Tasks: End Users \n \nMAP 2.3: Scienti\ufb01c integrity and TEVV considerations are identi\ufb01ed and documented, including those related to experimental \ndesign, data collection and selection (e.g., availability, representativeness, suitability), system trustworthiness, and construct \nvalidation \nAction ID \nSuggested Action \nGAI Risks \nMP-2.3-001 \nAssess the accuracy, quality, reliability, and authenticity of GAI output by \ncomparing it to a set of known ground truth data and by using a variety of", "c9d0711a-004e-4887-bef2-e4af6d5b3361": "in some cases. Many states have also enacted consumer data privacy protection regimes to address some of these \nharms. \nHowever, these are not yet standard practices, and the United States lacks a comprehensive statutory or regulatory \nframework governing the rights of the public when it comes to personal data. While a patchwork of laws exists to \nguide the collection and use of personal data in specific contexts, including health, employment, education, and credit, \nit can be unclear how these laws apply in other contexts and in an increasingly automated society. Additional protec\u00ad\ntions would assure the American public that the automated systems they use are not monitoring their activities, \ncollecting information on their lives, or otherwise surveilling them without context-specific consent or legal authori\u00ad\nty. \n31", "a09d22ae-57cd-4d06-a965-34970ccc4ea9": "11 \nvalue chain (e.g., data inputs, processing, GAI training, or deployment environments), conventional \ncybersecurity practices may need to adapt or evolve. \nFor instance, prompt injection involves modifying what input is provided to a GAI system so that it \nbehaves in unintended ways. In direct prompt injections, attackers might craft malicious prompts and \ninput them directly to a GAI system, with a variety of downstream negative consequences to \ninterconnected systems. Indirect prompt injection attacks occur when adversaries remotely (i.e., without \na direct interface) exploit LLM-integrated applications by injecting prompts into data likely to be \nretrieved. Security researchers have already demonstrated how indirect prompt injections can exploit \nvulnerabilities by stealing proprietary data or running malicious code remotely on a machine. Merely \nquerying a closed production model can elicit previously undisclosed information about that model.", "d2d7fc43-f0e0-4838-86a3-f9dcbd56064c": "assessments as part of the system design, use of representative data \nand protection against proxies for demographic features, ensuring \naccessibility for people with disabilities in design and development, \npre-deployment and ongoing disparity testing and mitigation, and \nclear organizational oversight. Independent evaluation and plain \nlanguage reporting in the form of an algorithmic impact assessment, \nincluding disparity testing results and mitigation information, \nshould be performed and made public whenever possible to confirm \nthese protections.\n23", "86c2b8cb-0b7b-4629-a4bd-6c66a3f84cd7": "APPENDIX\nExamples of Automated Systems \nThe below examples are meant to illustrate the breadth of automated systems that, insofar as they have the \npotential to meaningfully impact rights, opportunities, or access to critical resources or services, should \nbe covered by the Blueprint for an AI Bill of Rights. These examples should not be construed to limit that \nscope, which includes automated systems that may not yet exist, but which fall under these criteria. \nExamples of automated systems for which the Blueprint for an AI Bill of Rights should be considered include \nthose that have the potential to meaningfully impact: \n\u2022 Civil rights, civil liberties, or privacy, including but not limited to:\nSpeech-related systems such as automated content moderation tools; \nSurveillance and criminal justice system algorithms such as risk assessments, predictive  \n    policing, automated license plate readers, real-time facial recognition systems (especially", "4c0a384a-4c92-42cf-a63d-a48998f437d3": "most intimate sphere, including political opinions, sex life, or criminal convictions.  \n8 The notion of harm presumes some baseline scenario that the harmful factor (e.g., a GAI model) makes worse. \nWhen the mechanism for potential harm is a disparity between groups, it can be di\ufb03cult to establish what the \nmost appropriate baseline is to compare against, which can result in divergent views on when a disparity between \nAI behaviors for di\ufb00erent subgroups constitutes a harm. In discussing harms from disparities such as biased \nbehavior, this document highlights examples where someone\u2019s situation is worsened relative to what it would have \nbeen in the absence of any AI system, making the outcome unambiguously a harm of the system.", "1a1445dc-a483-4689-a196-3fe2e2191059": "Disparity mitigation. When a disparity assessment identifies a disparity against an assessed group, it may \nbe appropriate to take steps to mitigate or eliminate the disparity. In some cases, mitigation or elimination of \nthe disparity may be required by law. \nDisparities that have the potential to lead to algorithmic \ndiscrimination, cause meaningful harm, or violate equity49 goals should be mitigated. When designing and \nevaluating an automated system, steps should be taken to evaluate multiple models and select the one that \nhas the least adverse impact, modify data input choices, or otherwise identify a system with fewer \ndisparities. If adequate mitigation of the disparity is not possible, then the use of the automated system \nshould be reconsidered. One of the considerations in whether to use the system should be the validity of any \ntarget measure; unobservable targets may result in the inappropriate use of proxies. Meeting these", "7e2c9d15-c47a-4453-961d-8f3eaca062a8": "Homogenization \nMS-2.11-004 \nReview, document, and measure sources of bias in GAI training and TEVV data: \nDi\ufb00erences in distributions of outcomes across and within groups, including \nintersecting groups; Completeness, representativeness, and balance of data \nsources; demographic group and subgroup coverage in GAI system training \ndata; Forms of latent systemic bias in images, text, audio, embeddings, or other \ncomplex or unstructured data; Input data features that may serve as proxies for \ndemographic group membership (i.e., image metadata, language dialect) or \notherwise give rise to emergent bias within GAI systems; The extent to which \nthe digital divide may negatively impact representativeness in GAI system \ntraining and TEVV data; Filtering of hate speech or content in GAI system \ntraining data; Prevalence of GAI-generated data in GAI system training data. \nHarmful Bias and Homogenization \n \n \n15 Winogender Schemas is a sample set of paired sentences which di\ufb00er only by gender of the pronouns used,", "c1da5b2f-e1bd-424d-ab63-6f4b46cf6b46": "and management. One possible way to further categorize these risks, derived in part from the UK\u2019s International \nScienti\ufb01c Report on the Safety of Advanced AI, could be: 1) Technical / Model risks (or risk from malfunction): \nConfabulation; Dangerous or Violent Recommendations; Data Privacy; Value Chain and Component Integration; \nHarmful Bias, and Homogenization; 2) Misuse by humans (or malicious use): CBRN Information or Capabilities; \nData Privacy; Human-AI Con\ufb01guration; Obscene, Degrading, and/or Abusive Content; Information Integrity; \nInformation Security; 3) Ecosystem / societal risks (or systemic risks): Data Privacy; Environmental; Intellectual \nProperty. We also note that some risks are cross-cutting between these categories.", "73710384-8ad5-4f95-a5aa-6db21daa851a": "for any resulting algorithmic discrimination.   \n26\nAlgorithmic \nDiscrimination \nProtections", "44a8cf7b-bf66-4022-ac2c-84893ff96c86": "ENDNOTES\n85. Mick Dumke and Frank Main. A look inside the watch list Chicago police fought to keep secret. The\nChicago Sun Times. May 18, 2017.\nhttps://chicago.suntimes.com/2017/5/18/18386116/a-look-inside-the-watch-list-chicago-police-fought\u00ad\nto-keep-secret\n86. Jay Stanley. Pitfalls of Artificial Intelligence Decisionmaking Highlighted In Idaho ACLU Case.\nACLU. Jun. 2, 2017.\nhttps://www.aclu.org/blog/privacy-technology/pitfalls-artificial-intelligence-decisionmaking\u00ad\nhighlighted-idaho-aclu-case\n87. Illinois General Assembly. Biometric Information Privacy Act. Effective Oct. 3, 2008.\nhttps://www.ilga.gov/legislation/ilcs/ilcs3.asp?ActID=3004&ChapterID=57\n88. Partnership on AI. ABOUT ML Reference Document. Accessed May 2, 2022.\nhttps://partnershiponai.org/paper/about-ml-reference-document/1/\n89. See, e.g., the model cards framework: Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker\nBarnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru.", "3bc0010a-dd64-4488-aa13-f4356b278088": "NOTICE & \nEXPLANATION \nHOW THESE PRINCIPLES CAN MOVE INTO PRACTICE\nReal-life examples of how these principles can become reality, through laws, policies, and practical \ntechnical and sociotechnical approaches to protecting rights, opportunities, and access. \u00ad\u00ad\u00ad\u00ad\u00ad\nPeople in Illinois are given written notice by the private sector if their biometric informa-\ntion is used. The Biometric Information Privacy Act enacted by the state contains a number of provisions \nconcerning the use of individual biometric data and identifiers. Included among them is a provision that no private \nentity may \"collect, capture, purchase, receive through trade, or otherwise obtain\" such information about an \nindividual, unless written notice is provided to that individual or their legally appointed representative. 87\nMajor technology companies are piloting new ways to communicate with the public about", "9b458a26-9b4a-4d70-917c-6720e9cdbac8": "health coverage.\u201d107\nThe customer service industry has successfully integrated automated services such as \nchat-bots and AI-driven call response systems with escalation to a human support \nteam.108 Many businesses now use partially automated customer service platforms that help answer customer \nquestions and compile common problems for human agents to review. These integrated human-AI \nsystems allow companies to provide faster customer care while maintaining human agents to answer \ncalls or otherwise respond to complicated requests. Using both AI and human agents is viewed as key to \nsuccessful customer service.109\nBallot curing laws in at least 24 states require a fallback system that allows voters to \ncorrect their ballot and have it counted in the case that a voter signature matching \nalgorithm incorrectly flags their ballot as invalid or there is another issue with their \nballot, and review by an election official does not rectify the problem. Some federal", "4275e423-4206-4cdc-8dcf-31803c65173d": "by potential future employers, banks, or landlords. In one case, a former employee alleged that a\ncompany supplied false data about her job title which resulted in a job offer being revoked.77\n37", "6cd901b5-7e7c-473d-8147-818cf0bc5701": "generation of artificially intelligent partners.95 The National Science Foundation\u2019s program on Fairness in \nArtificial Intelligence also includes a specific interest in research foundations for explainable AI.96\n45", "c4e8bd7d-0329-4e14-9a73-3b0d73e40ed5": "cating adverse outcomes in domains such as finance, employment, and housing, is especially sensitive, and in \nsome cases its reuse is limited by law. Accordingly, such data should be subject to extra oversight to ensure \nsafety and efficacy. Data reuse of sensitive domain data in other contexts (e.g., criminal data reuse for civil legal \nmatters or private sector use) should only occur where use of such data is legally authorized and, after examina\u00ad\ntion, has benefits for those impacted by the system that outweigh identified risks and, as appropriate, reason\u00ad\nable measures have been implemented to mitigate the identified risks. Such data should be clearly labeled to \nidentify contexts for limited reuse based on sensitivity. Where possible, aggregated datasets may be useful for \nreplacing individual-level sensitive data. \nDemonstrate the safety and effectiveness of the system \nIndependent evaluation. Automated systems should be designed to allow for independent evaluation (e.g.,", "c0a4891f-9c78-444c-b309-abba336abc39": "ENDNOTES\n23. National Science Foundation. National Artificial Intelligence Research Institutes. Accessed Sept. 12,\n2022. https://beta.nsf.gov/funding/opportunities/national-artificial-intelligence-research-institutes\n24. National Science Foundation. Cyber-Physical Systems. Accessed Sept. 12, 2022. https://beta.nsf.gov/\nfunding/opportunities/cyber-physical-systems-cps\n25. National Science Foundation. Secure and Trustworthy Cyberspace. Accessed Sept. 12, 2022. https://\nbeta.nsf.gov/funding/opportunities/secure-and-trustworthy-cyberspace-satc\n26. National Science Foundation. Formal Methods in the Field. Accessed Sept. 12, 2022. https://\nbeta.nsf.gov/funding/opportunities/formal-methods-field-fmitf\n27. National Science Foundation. Designing Accountable Software Systems. Accessed Sept. 12, 2022.\nhttps://beta.nsf.gov/funding/opportunities/designing-accountable-software-systems-dass\n28. The Leadership Conference Education Fund. The Use Of Pretrial \u201cRisk Assessment\u201d Instruments: A", "2f83cb98-b4f1-4c32-85c6-9372b78cdd82": "tion history with that of her dog\u2019s. Even after she tracked down an explanation for the problem, doctors\nwere afraid to override the system, and she was forced to go without pain relief due to the system\u2019s error.103\n\u2022 A large corporation automated performance evaluation and other HR functions, leading to workers being\nfired by an automated system without the possibility of human review, appeal or other form of recourse.104 \n48", "b83971f2-8769-4a69-b89a-4eb71d1a867b": "informed by representative AI Actors. \nHuman-AI Con\ufb01guration; Harmful \nBias and Homogenization; CBRN \nInformation or Capabilities \nMS-1.1-005 \nEvaluate novel methods and technologies for the measurement of GAI-related \nrisks including in content provenance, o\ufb00ensive cyber, and CBRN, while \nmaintaining the models\u2019 ability to produce valid, reliable, and factually accurate \noutputs. \nInformation Integrity; CBRN \nInformation or Capabilities; \nObscene, Degrading, and/or \nAbusive Content", "93135040-675d-4b43-855e-a1606a30e1a7": "5 \noperations, or other cyberattacks; increased attack surface for targeted cyberattacks, which may \ncompromise a system\u2019s availability or the con\ufb01dentiality or integrity of training data, code, or \nmodel weights.  \n10. Intellectual Property: Eased production or replication of alleged copyrighted, trademarked, or \nlicensed content without authorization (possibly in situations which do not fall under fair use); \neased exposure of trade secrets; or plagiarism or illegal replication.  \n11. Obscene, Degrading, and/or Abusive Content: Eased production of and access to obscene, \ndegrading, and/or abusive imagery which can cause harm, including synthetic child sexual abuse \nmaterial (CSAM), and nonconsensual intimate images (NCII) of adults. \n12. Value Chain and Component Integration: Non-transparent or untraceable integration of \nupstream third-party components, including data that has been improperly obtained or not \nprocessed and cleaned due to increased automation from GAI; improper supplier vetting across", "0e9f5217-a16b-4485-b733-ab139fed5db0": "or insurance health risk assessments, drug addiction risk assessments and associated access alg \n-orithms, wearable technologies, wellness apps, insurance care allocation algorithms, and health\ninsurance cost and underwriting algorithms;\nFinancial system algorithms such as loan allocation algorithms, financial system access determi-\nnation algorithms, credit scoring systems, insurance algorithms including risk assessments, auto\n-mated interest rate determinations, and financial algorithms that apply penalties (e.g., that can\ngarnish wages or withhold tax returns);\n53", "f4d5686d-1caf-40d9-9401-c84e128b0a30": "SAFE AND EFFECTIVE SYSTEMS \nYou should be protected from unsafe or ineffective sys\u00ad\ntems. Automated systems should be developed with consultation \nfrom diverse communities, stakeholders, and domain experts to iden\u00ad\ntify concerns, risks, and potential impacts of the system. Systems \nshould undergo pre-deployment testing, risk identification and miti\u00ad\ngation, and ongoing monitoring that demonstrate they are safe and \neffective based on their intended use, mitigation of unsafe outcomes \nincluding those beyond the intended use, and adherence to do\u00ad\nmain-specific standards. Outcomes of these protective measures \nshould include the possibility of not deploying the system or remov\u00ad\ning a system from use. Automated systems should not be designed \nwith an intent or reasonably foreseeable possibility of endangering \nyour safety or the safety of your community. They should be designed \nto proactively protect you from harms stemming from unintended,", "46776766-3bdc-4e9c-a580-130ca26e7504": "ENDNOTES\n47. Darshali A. Vyas et al., Hidden in Plain Sight \u2013 Reconsidering the Use of Race Correction in Clinical\nAlgorithms, 383 N. Engl. J. Med.874, 876-78 (Aug. 27, 2020), https://www.nejm.org/doi/full/10.1056/\nNEJMms2004740.\n48. The definitions of 'equity' and 'underserved communities' can be found in the Definitions section of\nthis framework as well as in Section 2 of The Executive Order On Advancing Racial Equity and Support\nfor Underserved Communities Through the Federal Government. https://www.whitehouse.gov/\nbriefing-room/presidential-actions/2021/01/20/executive-order-advancing-racial-equity-and-support\u00ad\nfor-underserved-communities-through-the-federal-government/\n49. Id.\n50. Various organizations have offered proposals for how such assessments might be designed. See, e.g.,\nEmanuel Moss, Elizabeth Anne Watkins, Ranjit Singh, Madeleine Clare Elish, and Jacob Metcalf.\nAssembling Accountability: Algorithmic Impact Assessment for the Public Interest. Data & Society", "36392958-09c9-4300-9271-e4655423509a": "SECTION TITLE\u00ad\nFOREWORD\nAmong the great challenges posed to democracy today is the use of technology, data, and automated systems in \nways that threaten the rights of the American public. Too often, these tools are used to limit our opportunities and \nprevent our access to critical resources or services. These problems are well documented. In America and around \nthe world, systems supposed to help with patient care have proven unsafe, ineffective, or biased. Algorithms used \nin hiring and credit decisions have been found to reflect and reproduce existing unwanted inequities or embed \nnew harmful bias and discrimination. Unchecked social media data collection has been used to threaten people\u2019s \nopportunities, undermine their privacy, or pervasively track their activity\u2014often without their knowledge or \nconsent. \nThese outcomes are deeply harmful\u2014but they are not inevitable. Automated systems have brought about extraor-", "b6584983-93a2-4fe2-bdca-aa01408352d1": "data in order to generate derived synthetic content. This can include images, videos, audio, text, and other digital \ncontent.\u201d While not all GAI is derived from foundation models, for purposes of this document, GAI generally refers \nto generative foundation models. The foundation model subcategory of \u201cdual-use foundation models\u201d is de\ufb01ned by \nEO 14110 as \u201can AI model that is trained on broad data; generally uses self-supervision; contains at least tens of \nbillions of parameters; is applicable across a wide range of contexts.\u201d  \n2 This pro\ufb01le was developed per Section 4.1(a)(i)(A) of EO 14110, which directs the Secretary of Commerce, acting \nthrough the Director of the National Institute of Standards and Technology (NIST), to develop a companion \nresource to the AI RMF, NIST AI 100\u20131, for generative AI.", "dd97552e-cc7d-4c14-a4cc-1c23c836536c": "decision making, and enhancing system documentation and debugging practices. When implementing \nfeedback activities, organizations should follow human subjects research requirements and best \npractices such as informed consent and subject compensation.", "3380d726-bb80-484e-ae21-fb3eac80028a": "Software & Information Industry \nAssociation \nStephanie Dinkins and the Future \nHistories Studio at Stony Brook \nUniversity \nTechNet \nThe Alliance for Media Arts and \nCulture, MIT Open Documentary \nLab and Co-Creation Studio, and \nImmerse \nThe International Brotherhood of \nTeamsters \nThe Leadership Conference on \nCivil and Human Rights \nThorn \nU.S. Chamber of Commerce\u2019s \nTechnology Engagement Center \nUber Technologies \nUniversity of Pittsburgh \nUndergraduate Student \nCollaborative \nUpturn \nUS Technology Policy Committee \nof the Association of Computing \nMachinery \nVirginia Puccio \nVisar Berisha and Julie Liss \nXR Association \nXR Safety Initiative \n\u2022 As an additional effort to reach out to stakeholders regarding the RFI, OSTP conducted two listening sessions\nfor members of the public. The listening sessions together drew upwards of 300 participants. The Science and\nTechnology Policy Institute produced a synopsis of both the RFI submissions and the feedback at the listening\nsessions.115\n61", "9fff3b99-08a8-4b76-bff6-66d7574d47c2": "19 \nGV-4.1-003 \nEstablish policies, procedures, and processes for oversight functions (e.g., senior \nleadership, legal, compliance, including internal evaluation) across the GAI \nlifecycle, from problem formulation and supply chains to system decommission. \nValue Chain and Component \nIntegration \nAI Actor Tasks: AI Deployment, AI Design, AI Development, Operation and Monitoring \n \nGOVERN 4.2: Organizational teams document the risks and potential impacts of the AI technology they design, develop, deploy, \nevaluate, and use, and they communicate about the impacts more broadly. \nAction ID \nSuggested Action \nGAI Risks \nGV-4.2-001 \nEstablish terms of use and terms of service for GAI systems. \nIntellectual Property; Dangerous, \nViolent, or Hateful Content; \nObscene, Degrading, and/or \nAbusive Content \nGV-4.2-002 \nInclude relevant AI Actors in the GAI system risk identi\ufb01cation process. \nHuman-AI Con\ufb01guration \nGV-4.2-003 \nVerify that downstream GAI system impacts (such as the use of third-party", "8e850453-d994-4bbd-9857-bff1ebc1c2f0": "DATA PRIVACY \nWHY THIS PRINCIPLE IS IMPORTANT\nThis section provides a brief summary of the problems which the principle seeks to address and protect \nagainst, including illustrative examples. \nData privacy is a foundational and cross-cutting principle required for achieving all others in this framework. Surveil\u00ad\nlance and data collection, sharing, use, and reuse now sit at the foundation of business models across many industries, \nwith more and more companies tracking the behavior of the American public, building individual profiles based on \nthis data, and using this granular-level information as input into automated systems that further track, profile, and \nimpact the American public. Government agencies, particularly law enforcement agencies, also use and help develop \na variety of technologies that enhance and expand surveillance capabilities, which similarly collect data used as input", "3a4199c4-2b01-412a-b7c5-d9e83cddf2f9": "consequential decision-making settings like employment and lending can result in increased susceptibility by \nsystems to correlated failures (like unexpected shocks), due to multiple actors relying on the same algorithm.  \n4 Many studies have projected the impact of AI on the workforce and labor markets. Fewer studies have examined \nthe impact of GAI on the labor market, though some industry surveys indicate that that both employees and \nemployers are pondering this disruption.", "3732bb56-dad5-418a-bc2f-796ccdd31a0e": "5. Environmental Impacts: Impacts due to high compute resource utilization in training or \noperating GAI models, and related outcomes that may adversely impact ecosystems.  \n6. Harmful Bias or Homogenization: Ampli\ufb01cation and exacerbation of historical, societal, and \nsystemic biases; performance disparities8 between sub-groups or languages, possibly due to \nnon-representative training data, that result in discrimination, ampli\ufb01cation of biases, or \nincorrect presumptions about performance; undesired homogeneity that skews system or model \noutputs, which may be erroneous, lead to ill-founded decision-making, or amplify harmful \nbiases.  \n7. Human-AI Con\ufb01guration: Arrangements of or interactions between a human and an AI system \nwhich can result in the human inappropriately anthropomorphizing GAI systems or experiencing \nalgorithmic aversion, automation bias, over-reliance, or emotional entanglement with GAI \nsystems.", "8ef39111-e7ab-41c7-894a-f4b19f7e92fd": "and user perceptions of content authenticity. Analyze user feedback to identify \nconcerns and/or current literacy levels related to content provenance and \nunderstanding of labels on content. \nHuman-AI Con\ufb01guration; \nInformation Integrity \nMS-2.7-004 \nIdentify metrics that re\ufb02ect the e\ufb00ectiveness of security measures, such as data \nprovenance, the number of unauthorized access attempts, inference, bypass, \nextraction, penetrations, or provenance veri\ufb01cation. \nInformation Integrity; Information \nSecurity \nMS-2.7-005 \nMeasure reliability of content authentication methods, such as watermarking, \ncryptographic signatures, digital \ufb01ngerprints, as well as access controls, \nconformity assessment, and model integrity veri\ufb01cation, which can help support \nthe e\ufb00ective implementation of content provenance techniques. Evaluate the \nrate of false positives and false negatives in content provenance, as well as true \npositives and true negatives for veri\ufb01cation. \nInformation Integrity \nMS-2.7-006", "b4dfe088-8bb2-4a98-b320-22a7dd07c65c": "You should know that an automated system is being used, \nand understand how and why it contributes to outcomes \nthat impact you. Designers, developers, and deployers of automat\u00ad\ned systems should provide generally accessible plain language docu\u00ad\nmentation including clear descriptions of the overall system func\u00ad\ntioning and the role automation plays, notice that such systems are in \nuse, the individual or organization responsible for the system, and ex\u00ad\nplanations of outcomes that are clear, timely, and accessible. Such \nnotice should be kept up-to-date and people impacted by the system \nshould be notified of significant use case or key functionality chang\u00ad\nes. You should know how and why an outcome impacting you was de\u00ad\ntermined by an automated system, including when the automated \nsystem is not the sole input determining the outcome. Automated \nsystems should provide explanations that are technically valid, \nmeaningful and useful to you and to any operators or others who", "a0be6da2-7bf3-45f6-81b9-30d724b4dd3f": "WHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\nThe expectations for automated systems are meant to serve as a blueprint for the development of additional \ntechnical standards and practices that are tailored for particular sectors and contexts. \nAny automated system should be tested to help ensure it is free from algorithmic discrimination before it can be \nsold or used. Protection against algorithmic discrimination should include designing to ensure equity, broadly \nconstrued.  Some algorithmic discrimination is already prohibited under existing anti-discrimination law. The \nexpectations set out below describe proactive technical and policy steps that can be taken to not only \nreinforce those legal protections but extend beyond them to ensure equity for underserved communities48 \neven in circumstances where a specific legal protection may not be clearly established. These protections \nshould be instituted throughout the design, development, and deployment process and are described below", "e1358306-678d-4e98-9775-74065ea4ad8e": "HUMAN ALTERNATIVES, \nCONSIDERATION, AND \nFALLBACK \nWHY THIS PRINCIPLE IS IMPORTANT\nThis section provides a brief summary of the problems which the principle seeks to address and protect \nagainst, including illustrative examples. \nThere are many reasons people may prefer not to use an automated system: the system can be flawed and can lead to \nunintended outcomes; it may reinforce bias or be inaccessible; it may simply be inconvenient or unavailable; or it may \nreplace a paper or manual process to which people had grown accustomed. Yet members of the public are often \npresented with no alternative, or are forced to endure a cumbersome process to reach a human decision-maker once \nthey decide they no longer want to deal exclusively with the automated system or be impacted by its results. As a result \nof this lack of human reconsideration, many receive delayed access, or lose access, to rights, opportunities, benefits,", "702acaa9-737f-44b6-a74c-929662b0fa66": "Suggested Action \nGAI Risks \nMS-3.2-001 \nEstablish processes for identifying emergent GAI system risks including \nconsulting with external AI Actors. \nHuman-AI Con\ufb01guration; \nConfabulation  \nAI Actor Tasks: AI Impact Assessment, Domain Experts, Operation and Monitoring, TEVV \n \nMEASURE 3.3: Feedback processes for end users and impacted communities to report problems and appeal system outcomes are \nestablished and integrated into AI system evaluation metrics. \nAction ID \nSuggested Action \nGAI Risks \nMS-3.3-001 \nConduct impact assessments on how AI-generated content might a\ufb00ect \ndi\ufb00erent social, economic, and cultural groups. \nHarmful Bias and Homogenization \nMS-3.3-002 \nConduct studies to understand how end users perceive and interact with GAI \ncontent and accompanying content provenance within context of use. Assess \nwhether the content aligns with their expectations and how they may act upon \nthe information presented. \nHuman-AI Con\ufb01guration; \nInformation Integrity \nMS-3.3-003", "657cf38d-9798-4c12-83e4-12695c9d7a54": "plugins) are included in the impact documentation process. \nValue Chain and Component \nIntegration \nAI Actor Tasks: AI Deployment, AI Design, AI Development, Operation and Monitoring \n \nGOVERN 4.3: Organizational practices are in place to enable AI testing, identi\ufb01cation of incidents, and information sharing. \nAction ID \nSuggested Action \nGAI Risks \nGV4.3--001 \nEstablish policies for measuring the e\ufb00ectiveness of employed content \nprovenance methodologies (e.g., cryptography, watermarking, steganography, \netc.) \nInformation Integrity \nGV-4.3-002 \nEstablish organizational practices to identify the minimum set of criteria \nnecessary for GAI system incident reporting such as: System ID (auto-generated \nmost likely), Title, Reporter, System/Source, Data Reported, Date of Incident, \nDescription, Impact(s), Stakeholder(s) Impacted. \nInformation Security"}}