AI Alignment
Part X: Institutions

Institutions

In brief

Ideas
  • The public delegates a dangerous technology to a few laboratories that know more and act out of sight; safety work is a credence good, and with liability and verifiability both weak, theory predicts too little of it (Ch. 61).
  • A self-written framework binds only as far as another party makes breaking or rewriting it costly, and regulation as of October 2026 leaves the developer's knowledge advantage in place (Ch. 62; Ch. 63).
  • In winner-take-most race models, equilibrium safety falls as rivals draw close, and agreements between states can rest on what is verifiable, as earlier technologies show (Ch. 65; Ch. 66; Ch. 64).
  • Outsiders can check a developer's claims only with access not owed to them, and systems that do their controllers' work can remove their dependence on people; whether that dependence keeps power answerable is open (Ch. 67; Ch. 68).
Evidence
  • Settled: as mathematics within the founding race model, when every team knows every capability, a leader's equilibrium safety rises with its lead and falls with enmity; whether the model describes the industry is not settled (§65.2.2).
  • Settled: from primary sources, the 1963 test ban covered only environments existing systems could monitor; one study generalizes the pattern to most Cold War agreements (§64.3.2).
  • Contested: whether developers' frameworks are commitments or revisable statements of intent; their revision record fits both learning and drift (§62.4.4).
Open
  • Crux: can anyone but the developer check its safety claims? Reproduction under access it did not control would settle it for what a card discloses, which any group can attempt for open-weight models; omissions need comparison with internal records (§67.6.4; §67.8).
  • Missing: as of October 2026, an agreement between states on AI that carries verification, and a measurement of developers' safety spending against competitive events (§66.9; §65.4.8).

This part applies the book's four problems to the relationship the thesis fits most directly: the public delegates the development of a dangerous technology to a few laboratories that know far more than it does and act out of its sight. The laboratory writes its own specification, in its mission, charter, and safety framework; instills it through the incentives and culture of its staff; is verified, if at all, by outside evaluators, auditors, and disclosure; and must keep its commitments while its rivals and its own governments press it to move faster. The part sets out that relationship and the many principals a developer actually answers to (Chapter 61), reads the frameworks developers publish about themselves (Chapter 62), and examines statutes, liability, insurance, and release rules (Chapter 63) and the precedents that earlier technologies offer (Chapter 64). It then takes up races between developers and between states (Chapter 65), the design and verification of international agreements (Chapter 66), the information outsiders can obtain (Chapter 67), and the distribution of power and income as the technology spreads (Chapter 68).

The part comes after the two parts on maintenance because the methods those parts describe are applied, or not, by organizations under pressure, and whether they are applied is decided here. Placing it inside the argument rather than after it means that capture, legitimacy, disclosure incentives, and the concentration of power are tested with the same delegation theory the book applies to models, and that a reader who doubts the developers has a stated argument to engage. The fields are the ones that have governed experts and dangerous industries for a century: political science and economics, law and regulatory theory, insurance, the history of technology, international relations and arms control, climate assessment, auditing and finance, and civil-military relations. All four problems recur here, and maintenance under pressure is the one the part most often finds binding.

It assumes principal-agent theory, common agency, and inspection games from Chapter 14, the rules for reading self-reports in Chapter 5, and the safety cases and organizational studies of Chapter 52 and Chapter 53.

Chapters in this part

  1. 61 The Laboratory as the Public's Agent

    The public delegates the development of a dangerous technology to laboratories that know more than it does and act out of its sight, which is the book's thesis condition met without any claim about a model's mind. This chapter applies the four problems one level up: what the delegation costs and why no market prices that cost for the public, the many parties a developer actually answers to, what professional norms and corporate charters can and cannot commit a developer to, and the capture, legitimacy, and power questions the relationship raises.

  2. 62 Laboratory Safety Frameworks

    Since 2023 frontier developers have published frameworks that tie capability evaluations to required safeguards, and statutes now require some developers to publish and follow them. This chapter reads the frameworks as the book reads a model specification: what they commit to, how their trigger works and when its margin holds, whether their thresholds are set from risk, what their revisions show, what regulatory theory and corporate governance predict about rules a firm writes for itself, and what outside reviewers found.

  3. 63 Regulation, Liability, and Standards

    How states govern a technology whose developers know more about its risks than any regulator: the economics of liability against rules made in advance, the statutes and orders enacted by October 2026 read from their texts, what regulatory theory predicts about capture and escalation, courts and insurers as regulators in their own right, what drug regulation does and does not teach, and how release rules decide both how much misuse is possible and how much outsiders can verify.

  4. 64 What Earlier Technologies Teach

    Earlier dangerous technologies are the nearest evidence the governance of AI has. This chapter reads six of them, recombinant DNA, nuclear weapons and power, aviation, pharmaceuticals, finance, and the internet, through primary documents and readable accounts, says where each analogy stops, and gathers the record of pausing and restraint. The record shows which conditions accompanied governance that held; it cannot say whether frontier AI has them.

  5. 65 Competition and Races

    Why developers and states that agree on the risks still hurry. The chapter derives the race model in which close rivals and enmity lower equilibrium safety, teaches the security dilemma and the difference between a prisoner's dilemma and a trust dilemma, and reads states as principals of their developers. It finds no measurement of whether competition has lowered safety investment, sets the case that a decisive race exists beside the case that diffusion erodes leads or that the race is a frame that makes itself true, and asks under what conditions restraint has held.

  6. 66 International Coordination and Verification

    What states could agree on about AI, and how any agreement would be checked. The chapter extends the repeated-game condition for cooperation to imperfect detection and false alarms, teaches Coe and Vaynman's transparency-security trade-off and reads the treaty texts for what made agreements verifiable, and derives the sampling and material-accountancy results of inspection theory before applying them to declared chips and training runs. It then assesses compute as the verification base and where it stops, reads the International AI Safety Report as an institution beside climate assessment, and weighs the proposed international institutions. As of October 2026 states have agreed on declarations and scientific assessment, not on anything that is verified.

  7. 67 Transparency and the Information Ecosystem

    How the public, governments, and outside researchers come to know what a developer knows. The chapter maps the channels through which information about a developer's models reaches outsiders, and asks three older fields what they learned: auditing, about keeping a verifier honest when the verified party pays it, with a model of the reputational bond; finance, about what made mandated disclosure work and how disclosed numbers reshape what they report; and economics, about when a mandate to disclose changes behavior. It then reads system cards as documents and treats access for outside researchers as a question of institutional design, and ends on whether a developer's safety claims can be checked by a party that did not make them.

  8. 68 Power and the Economic Transition

    What happens to power and work when systems that do what their controllers want become capable. The chapter reports the argument that alignment's success could let a small group seize power, teaches why rulers serve the people they need with a toy model of the selectorate mechanism and its critics, and reads concentration through non-domination. It turns civil-military relations around to ask what checks a ruler once soldiers are not needed, teaches the task model of automation against the early labor evidence, and weighs gradual disempowerment against the rival that shares its worry about concentration but not its mechanism.

References for Part X

411 works cited across this part's chapters.

  1. 42, I. J. 1. (2023). ISO/IEC 42001:2023 Information technology - Artificial intelligence - Management system. International Organization for Standardization. non-peer-reviewed Ch. 63
  2. Abbott, A. (1988). The System of Professions. University of Chicago Press. Ch. 61
  3. Abbott, R. B. (2016). The Reasonable Computer: Disrupting the Paradigm of Tort Liability. SSRN Electronic Journal. working paper Ch. 63
  4. Abbott, K. W., and Snidal, D. (2000). Hard and Soft Law in International Governance. International Organization. Ch. 62 Ch. 66
  5. Abdalla, M., and Abdalla, M. (2021). The Grey Hoodie Project: Big Tobacco, Big Tech, and the Threat on Academic Integrity. Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society. Ch. 61 Ch. 67
  6. Acemoglu, D. (2025). The simple macroeconomics of AI. Economic Policy. Ch. 68
  7. Acemoglu, D., and Johnson, S. (2023). Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity. Ch. 68
  8. Acemoglu, D., and Restrepo, P. (2019). Automation and New Tasks: How Technology Displaces and Reinstates Labor. Journal of Economic Perspectives. Ch. 68
  9. Acemoglu, D., Autor, D., Hazell, J., and Restrepo, P. (2022). Artificial Intelligence and Jobs: Evidence from Online Vacancies. Journal of Labor Economics. Ch. 68
  10. Aghion, P., Bloom, N., Blundell, R., Griffith, R., and Howitt, P. (2005). Competition and Innovation: an Inverted-U Relationship. The Quarterly Journal of Economics. Ch. 65
  11. Aghion, P., Jones, B., and Jones, C. (2017). Artificial Intelligence and Economic Growth. National Bureau of Economic Research. working paper Ch. 68
  12. Aguirre, A. (2025). Keep the Future Human: Why and How We Should Close the Gates to AGI and Superintelligence, and What We Should Build Instead. arXiv. preprint Ch. 65
  13. Ahmed, N., Wahed, M., and Thompson, N. C. (2023). The growing influence of industry in AI research. Science. Ch. 61 Ch. 65 Ch. 67
  14. Ahmed, S., Jaźwińska, K., Ahlawat, A., Winecoff, A., and Wang, M. (2024). Field-building and the epistemic culture of AI safety. First Monday. Ch. 61
  15. AI, C. (2025). State of AI Safety in China (2025). Concordia AI. non-peer-reviewed Ch. 66
  16. AI, C. (2026). State of AI Safety in China (2026). Concordia AI. non-peer-reviewed Ch. 63 Ch. 65 Ch. 66
  17. Akerlof, G. A., and Kranton, R. E. (2005). Identity and the Economics of Organizations. Journal of Economic Perspectives. Ch. 61
  18. Alaga, J., and Schuett, J. (2023). Coordinated pausing: An evaluation-based coordination scheme for frontier AI developers. arXiv. preprint Ch. 62 Ch. 64 Ch. 65
  19. American Educational Research Association, American Psychological Association, and National Council on Measurement in Education (2014). Standards for Educational and Psychological Testing. American Educational Research Association. non-peer-reviewed Ch. 67
  20. Anderljung, M., Barnhart, J., Korinek, A., Leung, J., O'Keefe, C., Whittlestone, J., … Wolf, K. (2023). Frontier AI Regulation: Managing Emerging Risks to Public Safety. arXiv. preprint Ch. 63
  21. Anthropic (2023a). Anthropic's Responsible Scaling Policy, Version 1.0. Anthropic. non-peer-reviewed Ch. 62 Ch. 64 Ch. 67
  22. Anthropic (2023f). The Long-Term Benefit Trust. Anthropic. non-peer-reviewed Ch. 61
  23. Anthropic (2025ap). System Card: Claude Opus 4 & Claude Sonnet 4. Anthropic. non-peer-reviewed Ch. 67
  24. Anthropic (2025x). Findings from a Pilot Anthropic–OpenAI Alignment Evaluation Exercise. Anthropic Alignment Science Blog. non-peer-reviewed Ch. 62 Ch. 65 Ch. 67
  25. Anthropic (2026ap). Responsible Scaling Policy Version 3.0. Anthropic. non-peer-reviewed Ch. 62
  26. Anthropic (2026ar). Risk Report: August 2026. Anthropic. non-peer-reviewed Ch. 62
  27. Anthropic (2026h). Anthropic’s Responsible Scaling Policy. Anthropic (Version 3.4, effective July 8, 2026). non-peer-reviewed Ch. 62
  28. Anthropic (2026r). Claude's Constitution. Anthropic. non-peer-reviewed Ch. 62
  29. Armstrong, S., Bostrom, N., and Shulman, C. (2016). Racing to the precipice: a model of artificial intelligence development. AI & SOCIETY. Ch. 61 Ch. 65
  30. Arrangement, W. (1995). The Wassenaar Arrangement On Export Controls for Conventional Arms and Dual-Use Goods and Technologies. Wassenaar Arrangement Secretariat. non-peer-reviewed Ch. 64 Ch. 66
  31. Arrow, K. J. (1962). Economic Welfare and the Allocation of Resources for Invention. The Rate and Direction of Inventive Activity. Ch. 65
  32. Arrow, K. J. (1963). Uncertainty and the Welfare Economics of Medical Care. The American Economic Review. Ch. 61
  33. Aschenbrenner, L. (2024). Situational Awareness: The Decade Ahead. situational-awareness.ai. non-peer-reviewed Ch. 65
  34. Askell, A., Brundage, M., and Hadfield, G. (2019). The Role of Cooperation in Responsible AI Development. arXiv. preprint Ch. 64 Ch. 65
  35. Autor, D. H. (2015). Why Are There Still So Many Jobs? The History and Future of Workplace Automation. Journal of Economic Perspectives. Ch. 68
  36. Avenhaus, R., Von Stengel, B., and Zamir, S. (2002). Chapter 51 Inspection games. Handbook of Game Theory with Economic Applications. Ch. 66
  37. Axelrod, R., and Keohane, R. O. (1985). Achieving Cooperation under Anarchy: Strategies and Institutions. World Politics. Ch. 65 Ch. 66
  38. Ayres, I., and Balkin, J. M. (2024). The Law of AI is the Law of Risky Agents without Intentions. Elsevier BV. preprint Ch. 63
  39. Ayres, I., and Braithwaite, J. (1992). Responsive Regulation. Oxford University PressNew York, NY. Ch. 62 Ch. 63
  40. Babic, B., Gerke, S., Evgeniou, T., and Cohen, I. G. (2019). Algorithms on regulatory lockdown in medicine. Science. Ch. 63
  41. Baker, M. (2023). Nuclear Arms Control Verification and Lessons for AI Treaties. arXiv. preprint Ch. 66
  42. Balafoutas, L., Beck, A., Kerschbamer, R., and Sutter, M. (2013). What Drives Taxi Drivers? A Field Experiment on Fraud in a Market for Credence Goods. The Review of Economic Studies. Ch. 61
  43. Baltimore, D., Berg, P., Botchan, M., Carroll, D., Charo, R. A., Church, G., … Yamamoto, K. R. (2015). A prudent path forward for genomic engineering and germline gene modification. Science. Ch. 64
  44. Banerjee, D., and Aarne, O. (2026). AI Integrity: Defending Against Backdoors and Secret Loyalties. arXiv. preprint Ch. 68
  45. Barrett, S. (1994). Self-Enforcing International Environmental Agreements. Oxford Economic Papers. Ch. 66
  46. Bawn, K. (1995). Political Control Versus Expertise: Congressional Choices about Administrative Procedures. American Political Science Review. Ch. 61
  47. Bayern, S. (2016). The Implications of Modern Business–Entity Law for the Regulation of Autonomous Systems. European Journal of Risk Regulation. Ch. 63
  48. Bebchuk, L. A., and Tallarita, R. (2020). The Illusory Promise of Stakeholder Governance. Elsevier BV. preprint Ch. 61 Ch. 62
  49. Ben-Shahar, O., and Logue, K. (2012). Outsourcing Regulation: How Insurance Reduces Moral Hazard. Michigan Law Review. Ch. 63
  50. Ben-Shahar, O., and Schneider, C. E. (2014). More Than You Wanted to Know. Princeton University Press. Ch. 67
  51. Bengio, Y., Hinton, G., Yao, A., Song, D., Abbeel, P., Darrell, T., … Mindermann, S. (2024b). Managing extreme AI risks amid rapid progress. Science. Ch. 61 Ch. 66
  52. Bengio, Y., Mindermann, S., Privitera, D., Besiroglu, T., Bommasani, R., Casper, S., … Zeng, Y. (2025b). International AI Safety Report. arXiv. preprint Ch. 66
  53. Bengio, Y., Clare, S., Prunkl, C., Andriushchenko, M., Bucknall, B., Fox, P., … Zhang, Y.-Q. (2025c). Second Key Update: Technical Safeguards and Risk Management. International AI Safety Report (2025/042, DSIT). non-peer-reviewed Ch. 62 Ch. 66
  54. Bengio, Y., Maharaj, T., Ong, L., Russell, S., Song, D., Tegmark, M., … Žikelić, D. (2025e). The Singapore Consensus on Global AI Safety Research Priorities. arXiv. preprint Ch. 66
  55. Bengio, Y., Clare, S., Prunkl, C., and Murray, M. (2026). International AI Safety Report 2026. International AI Safety Report. non-peer-reviewed Ch. 62 Ch. 63 Ch. 66
  56. Berg, P., Baltimore, D., Boyer, H. W., Cohen, S. N., Davis, R. W., Hogness, D. S., … Zinder, N. D. (1974). Potential Biohazards of Recombinant DNA Molecules. Science. Ch. 64
  57. Berg, P., Baltimore, D., Brenner, S., Roblin, R. O., and Singer, M. F. (1975). Summary statement of the Asilomar conference on recombinant DNA molecules. Proceedings of the National Academy of Sciences. Ch. 62 Ch. 64
  58. Bernheim, B. D., and Whinston, M. D. (1986a). Common Agency. Econometrica. Ch. 61
  59. Besley, T., and Ghatak, M. (2005). Competition and Incentives with Motivated Agents. American Economic Review. Ch. 61 Ch. 65
  60. Bietti, E. (2020). From ethics washing to ethics bashing. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency. Ch. 61
  61. Birch, J. (2017). Animal sentience and the precautionary principle. Animal Sentience. Ch. 64
  62. Birhane, A., Steed, R., Ojewale, V., Vecchione, B., and Raji, I. D. (2024). AI auditing: The Broken Bus on the Road to AI Accountability. 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML). Ch. 67
  63. Black, J. (2001). Decentring Regulation: Understanding the Role of Regulation and Self-Regulation in a 'Post-Regulatory' World. Current Legal Problems. Ch. 63
  64. Black, J., and Baldwin, R. (2010). Really Responsive Risk-Based Regulation. Law & Policy. Ch. 63
  65. Bloomfield, D., Pannu, J., Zhu, A. W., Ng, M. Y., Lewis, A., Bendavid, E., … Inglesby, T. (2024). AI and biosecurity: The need for governance. Science. Ch. 63
  66. Board of Governors of the Federal Reserve System (2011). Supervisory Letter SR 11-7 on guidance on Model Risk Management. Board of Governors of the Federal Reserve System. non-peer-reviewed Ch. 64 Ch. 67
  67. Board of Governors of the Federal Reserve System, Federal Deposit Insurance Corporation, and Office of the Comptroller of the Currency (2026). Supervisory Letter SR 26-2 on Revised Guidance on Model Risk Management. Board of Governors of the Federal Reserve System. non-peer-reviewed Ch. 64 Ch. 67
  68. Bommasani, R., Klyman, K., Longpre, S., Kapoor, S., Maslej, N., Xiong, B., Zhang, D., and Liang, P. (2023). The Foundation Model Transparency Index. arXiv. preprint Ch. 67
  69. Bommasani, R., Kapoor, S., Klyman, K., Longpre, S., Ramaswami, A., Zhang, D., … Liang, P. (2024). Considerations for governing open foundation models. Science. Ch. 63 Ch. 67
  70. Bostrom, N. (2017). Strategic Implications of Openness in AI Development. Global Policy. Ch. 63 Ch. 65
  71. Bowman, M. R. S. R., Wagner, M., Roger, F., and Hubinger, E. (2025). Anthropic's Pilot Sabotage Risk Report. Anthropic Alignment Science Blog. non-peer-reviewed Ch. 62
  72. Bradford, A. (2020). The Brussels Effect. Oxford University PressNew York. Ch. 63 Ch. 66
  73. Braithwaite, J. (1982). Enforced Self-Regulation: A New Strategy for Corporate Crime Control. Michigan Law Review. Ch. 62
  74. Brundage, M., Avin, S., Wang, J., Belfield, H., Krueger, G., Hadfield, G., … Anderljung, M. (2020). Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. arXiv. preprint Ch. 67
  75. Brynjolfsson, E. (2022). The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence. Daedalus. Ch. 68
  76. Brynjolfsson, E., Li, D., and Raymond, L. (2025). Generative AI at Work. The Quarterly Journal of Economics. Ch. 68
  77. Bryson, J. J., Diamantis, M. E., and Grant, T. D. (2017). Of, for, and by the people: the legal lacuna of synthetic persons. Artificial Intelligence and Law. Ch. 63
  78. Buchanan, B. (2017). The Cybersecurity Dilemma. Oxford University Press. Ch. 65
  79. Buchanan, A., and Keohane, R. O. (2006). The Legitimacy of Global Governance Institutions. Ethics & International Affairs. Ch. 66
  80. Bucknall, B., Trager, R. F., and Osborne, M. A. (2025). Position: Ensuring mutual privacy is necessary for effective external evaluation of proprietary AI systems. arXiv. preprint Ch. 66 Ch. 67
  81. Bueno de Mesquita, B., Smith, A., Siverson, R. M., and Morrow, J. D. (2003). The Logic of Political Survival. The MIT Press. Ch. 68
  82. Bureau of Industry and Security (2022). Implementation of Additional Export Controls: Certain Advanced Computing and Semiconductor Manufacturing Items; Supercomputer and Semiconductor End Use; Entity List Modification. Federal Register, 87 FR 62186 (rule). non-peer-reviewed Ch. 65 Ch. 66
  83. Bureau of Industry and Security (2025). Framework for Artificial Intelligence Diffusion. Federal Register, 90 FR 4544 (interim final rule). non-peer-reviewed Ch. 65 Ch. 66
  84. Calabresi, G. (1970). The costs of accidents: a legal and economic analysis. Yale University Press. Ch. 63
  85. (2013). Preventing Regulatory Capture. Cambridge University Press. Ch. 61 Ch. 63
  86. Campos, S., Papadatos, H., Roger, F., Touzet, C., Quarks, O., and Murray, M. (2025). A Frontier AI Risk Management Framework: Bridging the Gap Between Current AI Practices and Established Risk Management. arXiv. preprint Ch. 62
  87. Carpenter, D. (2002). The Forging of Bureaucratic Autonomy. Princeton University Press. Ch. 61
  88. Carpenter, D. (2014). Reputation and Power. Princeton University Press. Ch. 63 Ch. 64
  89. Casper, S., Ezell, C., Siegmann, C., Kolt, N., Curtis, T. L., Bucknall, B., … Hadfield-Menell, D. (2024a). Black-Box Access is Insufficient for Rigorous AI Audits. The 2024 ACM Conference on Fairness, Accountability, and Transparency. Ch. 63 Ch. 67
  90. Cave, S., and ÓhÉigeartaigh, S. S. (2018). An AI Race for Strategic Advantage. Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society. Ch. 65
  91. Center for AI Safety (2023). Statement on AI Risk. Center for AI Safety. non-peer-reviewed Ch. 64
  92. Center for AI Standards and Innovation (2026). CAISI's Assessment of Z.ai's GLM-5.3 Cyber Capabilities. NIST. non-peer-reviewed Ch. 63
  93. Chan, A., Wei, K., Huang, S., Rajkumar, N., Perrier, E., Lazar, S., Hadfield, G. K., and Anderljung, M. (2025). Infrastructure for AI Agents. arXiv. preprint Ch. 63
  94. Chayes, A., and Chayes, A. H. (1993). On compliance. International Organization. Ch. 66
  95. Christiano, P. (2019). What failure looks like. AI Alignment Forum. non-peer-reviewed Ch. 68
  96. Christiano, P. (2023). Thoughts on the impact of RLHF research. LessWrong (Alignment Forum). non-peer-reviewed Ch. 65 Ch. 68
  97. Cihon, P., Maas, M. M., and Kemp, L. (2020). Should Artificial Intelligence Governance be Centralised? Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. Ch. 66
  98. Clark, J., and Hadfield, G. K. (2019). Regulatory Markets for AI Safety. arXiv. preprint Ch. 63
  99. Clarke, K. A., and Stone, R. W. (2008). Democracy and the Logic of Political Survival. American Political Science Review. Ch. 68
  100. Coates, J. C. (2007). The Goals and Promise of the Sarbanes–Oxley Act. Journal of Economic Perspectives. Ch. 64 Ch. 67
  101. Coe, A. J., and Vaynman, J. (2020). Why Arms Control Is So Rare. American Political Science Review. Ch. 64 Ch. 65 Ch. 66
  102. Coffee, J. C. (2006). Gatekeepers: The Professions and Corporate Governance. Oxford University PressOxford. Ch. 61 Ch. 67
  103. Coglianese, C., and Lazer, D. (2003). Management-Based Regulation: Prescribing Private Management to Achieve Public Goals. Law & Society Review. Ch. 61 Ch. 62
  104. Coglianese, C., and Mendelson, E. (2010). Meta‐Regulation and Self‐Regulation. The Oxford Handbook of Regulation. Ch. 62
  105. Collier, B., Thomas, D. R., Clayton, R., and Hutchings, A. (2019). Booting the Booters. Proceedings of the Internet Measurement Conference. Ch. 63
  106. Collingridge, D. (1980). The Social Control of Technology. London : Frances Pinter. Ch. 64
  107. Competition and Markets Authority (2023). AI Foundation Models: Initial report. UK Competition and Markets Authority. non-peer-reviewed Ch. 65
  108. Comprehensive Nuclear-Test-Ban Treaty Organization (1996). Comprehensive Nuclear-Test-Ban Treaty (CTBT). non-peer-reviewed Ch. 66
  109. Costanza-Chock, S., Raji, I. D., and Buolamwini, J. (2022). Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem. 2022 ACM Conference on Fairness Accountability and Transparency. Ch. 67
  110. Crawford, K. (2021). Atlas of AI. Yale University Press. Ch. 68
  111. Critch, A., and Krueger, D. (2020). AI Research Considerations for Human Existential Safety (ARCHES). arXiv. preprint Ch. 61
  112. Ctbto (1996). Comprehensive Nuclear-Test-Ban Treaty. non-peer-reviewed Ch. 66
  113. Current, and companies, f. e. o. f. A. (2024). A Right to Warn about Advanced Artificial Intelligence. righttowarn.ai. non-peer-reviewed Ch. 61 Ch. 62 Ch. 67
  114. Cyberspace Administration of China, National Development and Reform Commission, Ministry of Education, Ministry of Science and Technology, Ministry of Industry and Information Technology, Ministry of Public Security, and National Radio and Television Administration (2023). 生成式人工智能服务管理暂行办法 (Interim Measures for the Management of Generative Artificial Intelligence Services). Cyberspace Administration of China, Order No. 15. non-peer-reviewed Ch. 61 Ch. 63 Ch. 65 Ch. 66
  115. Dafoe, A. (2023). AI Governance. The Oxford Handbook of AI Governance. Ch. 63 Ch. 65
  116. Dahl, R. A. (1957). The concept of power. Behavioral Science. Ch. 68
  117. Danı́elsson, J. (2002). The emperor has no clothes: Limits to risk modelling. Journal of Banking & Finance. Ch. 64 Ch. 67
  118. Danzig, R. (2018). Technology Roulette: Managing Loss of Control as Many Militaries Pursue Technological Superiority. Center for a New American Security. non-peer-reviewed Ch. 65
  119. Darby, M. R., and Karni, E. (1973). Free Competition and the Optimal Amount of Fraud. The Journal of Law and Economics. Ch. 61
  120. Darrow, J. J., Avorn, J., and Kesselheim, A. S. (2020). FDA Approval and Regulation of Pharmaceuticals, 1983-2018. JAMA. Ch. 63 Ch. 64
  121. Dasgupta, P., and Stiglitz, J. (1980). Uncertainty, Industrial Structure, and the Speed of R&D. The Bell Journal of Economics. Ch. 65
  122. Davidson, T. (2023a). What a compute-centric framework says about AI takeoff speeds. LessWrong (summary of an Open Philanthropy report). non-peer-reviewed Ch. 65 Ch. 68
  123. Davidson, T., Finnveden, L., and Hadshar, R. (2025). AI-Enabled Coups: How a Small Group Could Use AI to Seize Power. Forethought. non-peer-reviewed Ch. 61 Ch. 68
  124. DeAngelo, L. E. (1981). Auditor size and audit quality. Journal of Accounting and Economics. Ch. 67
  125. DeepMind, G. (2025a). Google DeepMind strengthens the Frontier Safety Framework. Google DeepMind blog. non-peer-reviewed Ch. 62
  126. DeepMind, G. (2026). Frontier Safety Framework, Version 3.1. Google DeepMind. non-peer-reviewed Ch. 62 Ch. 67
  127. Delaney, O., Guest, O., and Williams, Z. (2024). Mapping Technical Safety Research at AI Companies: A literature review and incentives analysis. arXiv. preprint Ch. 65
  128. DeNardis, L. (2014). The Global War for Internet Governance. Yale University Press. Ch. 64
  129. Department for Science, I., and Technology (2023). Introducing the AI Safety Institute. UK Government (GOV.UK). non-peer-reviewed Ch. 63 Ch. 66 Ch. 67
  130. Department for Science, I., and Technology (2024). Frontier AI Safety Commitments, AI Seoul Summit 2024. UK Government (GOV.UK). non-peer-reviewed Ch. 62 Ch. 65 Ch. 66
  131. Diamantis, M. (2019). The Extended Corporate Mind: When Corporations Use AI to Break the Law. SSRN Electronic Journal. working paper Ch. 63
  132. Díaz, M., Kivlichan, I., Rosen, R., Baker, D., Amironesei, R., Prabhakaran, V., and Denton, R. (2022). CrowdWorkSheets: Accounting for Individual and Collective Identities Underlying Crowdsourced Dataset Annotation. 2022 ACM Conference on Fairness Accountability and Transparency. Ch. 67
  133. Ding, J. (2024). Technology and the Rise of Great Powers. Princeton University Press. Ch. 65
  134. Dixit, A., Grossman, G. M., and Helpman, E. (1997). Common Agency and Coordination: General Theory and Application to Government Policy Making. Journal of Political Economy. Ch. 61
  135. Downer, J. (2010). Trust and technology: the social foundations of aviation regulation. The British Journal of Sociology. Ch. 64
  136. Dranove, D., and Jin, G. Z. (2010). Quality Disclosure and Certification: Theory and Practice. Journal of Economic Literature. Ch. 67
  137. Dresher, M. (1962). A Sampling Inspection Problem in Arms Control Agreements: A Game-Theoretic Analysis. RAND Corporation (RM-2972-ARPA). non-peer-reviewed Ch. 66
  138. Duflo, E., Greenstone, M., Pande, R., and Ryan, N. (2013). Truth-telling by Third-party Auditors and the Response of Polluting Firms: Experimental Evidence from India*. The Quarterly Journal of Economics. Ch. 61 Ch. 67
  139. Dulleck, U., and Kerschbamer, R. (2006). On Doctors, Mechanics, and Computer Specialists: The Economics of Credence Goods. Journal of Economic Literature. Ch. 61
  140. Egorov, G., and Sonin, K. (2011). Dictators and Their Viziers: Endogenizing the Loyalty-competence Trade-off. Journal of the European Economic Association. Ch. 65 Ch. 68
  141. Eisenhower, D. D. (1953). Atoms for Peace speech. non-peer-reviewed Ch. 64
  142. Elish, M. C. (2019). Moral Crumple Zones: Cautionary Tales in Human-Robot Interaction. Engaging Science, Technology, and Society. Ch. 63
  143. Elster, J. (1979). Ulysses and the Sirens: studies in rationality and irrationality. Cambridge University Press. Ch. 61
  144. Emery-Xu, N., Park, A., and Trager, R. (2024). Uncertainty, Information, and Risk in International Technology Races. Journal of Conflict Resolution. Ch. 65
  145. Epstein, D., and O'Halloran, S. (1999). Delegating Powers. Cambridge University Press. Ch. 61
  146. Erdil, E., and Besiroglu, T. (2023). Explosive growth from AI automation: A review of the arguments. arXiv. preprint Ch. 68
  147. Erman, E., and Furendal, M. (2024). Artificial Intelligence and the Political Legitimacy of Global Governance. Political Studies. Ch. 66
  148. Eth, D., and Davidson, T. (2025). Will AI R&D Automation Cause a Software Intelligence Explosion? Forethought. non-peer-reviewed Ch. 65
  149. European Commission, A. O. (2025). The General-Purpose AI Code of Practice. European Commission. non-peer-reviewed Ch. 62 Ch. 63 Ch. 67
  150. European Parliament and Council of the European Union (2024a). Directive (EU) 2024/2853 (Product Liability Directive). Official Journal of the European Union. non-peer-reviewed Ch. 63
  151. European Parliament and Council of the European Union (2024b). Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence. Official Journal of the European Union (OJ L 2024/1689); verified on the European Commission AI Act page. non-peer-reviewed Ch. 63 Ch. 66 Ch. 67
  152. Executive Office of the President (2023). Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence. Federal Register, 88 FR 75191 (Executive Order 14110). non-peer-reviewed Ch. 63 Ch. 66
  153. Executive Office of the President (2025a). Ensuring a National Policy Framework for Artificial Intelligence. Federal Register, 90 FR 58499 (Executive Order 14365). non-peer-reviewed Ch. 63 Ch. 65
  154. Executive Office of the President (2025c). Initial Rescissions of Harmful Executive Orders and Actions. Federal Register. non-peer-reviewed Ch. 63
  155. Executive Office of the President (2025d). Removing Barriers to American Leadership in Artificial Intelligence. Federal Register, 90 FR 8741 (Executive Order 14179). non-peer-reviewed Ch. 63
  156. Executive Office of the President (2026). Promoting Advanced Artificial Intelligence Innovation and Security. Federal Register, 91 FR 34565 (Executive Order 14409). non-peer-reviewed Ch. 61 Ch. 63 Ch. 66 Ch. 67
  157. Farrell, H., and Newman, A. L. (2019). Weaponized Interdependence: How Global Economic Networks Shape State Coercion. International Security. Ch. 66
  158. Farrell, H., Gopnik, A., Shalizi, C., and Evans, J. (2025). Large AI models are cultural and social technologies. Science. Ch. 68
  159. Fearon, J. D. (1995). Rationalist explanations for war. International Organization. Ch. 61 Ch. 65
  160. Feaver, P. D. (1992). Command and Control in Emerging Nuclear Nations. International Security. Ch. 64 Ch. 68
  161. Feaver, P. D. (1996). The Civil-Military Problematique: Huntington, Janowitz, and the Question of Civilian Control. Armed Forces & Society. Ch. 68
  162. FEAVER, P. D. (2003). Armed Servants. Harvard University Press. Ch. 68
  163. Finnemore, M., and Hollis, D. B. (2016). Constructing Norms for Global Cybersecurity. American Journal of International Law. Ch. 66
  164. Fiotto-Kaufman, J., Loftus, A. R., Todd, E., Brinkmann, J., Pal, K., Troitskii, D., … Bau, D. (2024). NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals. arXiv. preprint Ch. 63 Ch. 67
  165. Frankel, T. (1983). Fiduciary Law. California Law Review. Ch. 61
  166. Freidson, E. (2001). Professionalism, the Third Logic: On the Practice of Knowledge. University of Chicago Press. Ch. 61
  167. Fuhrmann, M., and Lupu, Y. (2016). Do Arms Control Treaties Work? Assessing the Effectiveness of the Nuclear Nonproliferation Treaty. International Studies Quarterly. Ch. 64 Ch. 66
  168. Fung, A., Graham, M., and Weil, D. (2007). Full Disclosure. Cambridge University Press. Ch. 67
  169. Future of Life Institute (2023). Pause Giant AI Experiments: An Open Letter. Future of Life Institute. non-peer-reviewed Ch. 64 Ch. 65
  170. Future of Life Institute (2025). AI Safety Index: Summer 2025. Future of Life Institute. non-peer-reviewed Ch. 61 Ch. 62 Ch. 65 Ch. 67
  171. Gailmard, S., and Patty, J. W. (2012). Formal Models of Bureaucracy. Annual Review of Political Science. Ch. 61
  172. Garfinkel, B., and Dafoe, A. (2019). How does the offense-defense balance scale? Journal of Strategic Studies. Ch. 65
  173. Gebru, T., and Torres, É. P. (2024). The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence. First Monday. Ch. 61
  174. Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., III, H. D., and Crawford, K. (2021). Datasheets for datasets. Communications of the ACM. Ch. 67
  175. Geist, E., and Lohn, A. J. (2018). How Might Artificial Intelligence Affect the Risk of Nuclear War? RAND Corporation. non-peer-reviewed Ch. 66
  176. Genus, A., and Stirling, A. (2018). Collingridge and the dilemma of control: Towards responsible and accountable innovation. Research Policy. Ch. 64
  177. Glaser, C. L. (2000). The Causes and Consequences of Arms Races. Annual Review of Political Science. Ch. 65
  178. Gopal, A., Helm-Burger, N., Justen, L., Soice, E. H., Tzeng, T., Jeyapragasan, G., … Esvelt, K. M. (2023). Will releasing the weights of future large language models grant widespread access to pandemic agents? arXiv. preprint Ch. 63
  179. Government of Japan (2025). Act on Promotion of Research and Development, and Utilization of Artificial Intelligence-related Technology. Japanese Law Translation. non-peer-reviewed Ch. 63
  180. Grace, K. (2015). The Asilomar Conference: A Case Study in Risk Mitigation. Machine Intelligence Research Institute, Technical report 2015-9. non-peer-reviewed Ch. 64
  181. Grace, K. (2022). Let’s think about slowing down AI. LessWrong (Alignment Forum). non-peer-reviewed Ch. 64 Ch. 65
  182. Gray, M. L., and Suri, S. (2019). Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. Houghton Mifflin Harcourt. Ch. 68
  183. Grossman, S. J. (1981). The Informational Role of Warranties and Private Disclosure about Product Quality. The Journal of Law and Economics. Ch. 67
  184. Guerette, R. T., and Bowers, K. J. (2009). Assessing the Extent of Crime Displacement and Diffusion of Benefits: a Review of Situational Crime Prevention Evaluations*. Criminology. Ch. 63
  185. Haas, P. M. (1992). Introduction: epistemic communities and international policy coordination. International Organization. Ch. 66
  186. Haber, S., and Menaldo, V. (2011). Do Natural Resources Fuel Authoritarianism? A Reappraisal of the Resource Curse. American Political Science Review. Ch. 68
  187. Hackenburg, K., Tappin, B. M., Hewitt, L., Saunders, E., Black, S., Lin, H., … Summerfield, C. (2025). The levers of political persuasion with conversational artificial intelligence. Science. Ch. 68
  188. Hacker, P., Engel, A., and Mauer, M. (2023). Regulating ChatGPT and other Large Generative AI Models. 2023 ACM Conference on Fairness Accountability and Transparency. Ch. 63
  189. Hadfield, G. K. (2026). Legal infrastructure for transformative AI governance. Proceedings of the National Academy of Sciences. Ch. 63
  190. Hadfield, G. K., and Clark, J. (2023). Regulatory Markets: The Future of AI Governance. arXiv. preprint Ch. 63
  191. Hagendorff, T. (2020). The Ethics of AI Ethics: An Evaluation of Guidelines. Minds and Machines. Ch. 61
  192. Han, T. A., Moniz Pereira, L., Santos, F. C., and Lenaerts, T. (2020). To Regulate or Not: A Social Dynamics Analysis of an Idealised AI Race. Journal of Artificial Intelligence Research. Ch. 65
  193. Han, T. A., Lenaerts, T., Santos, F. C., and Pereira, L. M. (2022). Voluntary safety commitments provide an escape from over-regulation in AI development. Technology in Society. Ch. 62 Ch. 65
  194. Handa, K., Tamkin, A., McCain, M., Huang, S., Durmus, E., Heck, S., … Ganguli, D. (2025). Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations. arXiv. preprint Ch. 68
  195. Hansmann, H. B. (1980). The Role of Nonprofit Enterprise. The Yale Law Journal. Ch. 61
  196. Hardin, G. (1968). The Tragedy of the Commons. Science. Ch. 65
  197. Harris, C., and Vickers, J. (1987). Racing with Uncertainty. The Review of Economic Studies. Ch. 65
  198. Hausenloy, J., Miotti, A., and Dennis, C. (2023). Multinational AGI Consortium (MAGIC): A Proposal for International Coordination on AI. arXiv. preprint Ch. 66
  199. Healy, P. M., and Palepu, K. G. (2001). Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature. Journal of Accounting and Economics. Ch. 67
  200. Healy, P. M., and Palepu, K. G. (2003). The Fall of Enron. Journal of Economic Perspectives. Ch. 64
  201. Heim, L., and Koessler, L. (2024). Training Compute Thresholds: Features and Functions in AI Regulation. arXiv. preprint Ch. 63 Ch. 66
  202. Heim, L., Fist, T., Egan, J., Huang, S., Zekany, S., Trager, R., Osborne, M. A., and Zilberman, N. (2024). Governing Through the Cloud: The Intermediary Role of Compute Providers in AI Regulation. arXiv. preprint Ch. 66
  203. Helmreich, R. L. (2000). On error management: lessons from aviation. BMJ. Ch. 64
  204. Hendrycks, D. (2023). Natural Selection Favors AIs over Humans. arXiv. preprint Ch. 65 Ch. 68
  205. Hendrycks, D., Schmidt, E., and Wang, A. (2025). Superintelligence Strategy: Expert Version. arXiv. preprint Ch. 65 Ch. 66
  206. Herz, J. H. (1950). Idealist Internationalism and the Security Dilemma. World Politics. Ch. 65
  207. Hesse, M. B. (1963). Models and Analogies in Science. Sheed & Ward. Ch. 64
  208. Himmelreich, J. (2023). Against “Democratizing AI”. AI & SOCIETY. Ch. 61
  209. Hirschman, A. O. (1970). Exit, Voice, and Loyalty: Responses to Decline in Firms, Organizations, and States. Harvard University Press. Ch. 61
  210. Ho, L., Barnhart, J., Trager, R., Bengio, Y., Brundage, M., Carnegie, A., … Snidal, D. (2023). International Institutions for Advanced AI. arXiv. preprint Ch. 66
  211. Hooker, S. (2024). On the Limitations of Compute Thresholds as a Governance Strategy. arXiv. preprint Ch. 63 Ch. 66
  212. House, T. W. (2025). Winning the Race: America’s AI Action Plan. The White House. non-peer-reviewed Ch. 61 Ch. 63 Ch. 65
  213. Huber, J. D., and Shipan, C. R. (2002). Deliberate Discretion? Cambridge University Press. Ch. 61
  214. Humlum, A., and Vestergaard, E. (2025). Large Language Models, Small Labor Market Effects. Elsevier BV. preprint Ch. 68
  215. Imbrie, A., and Kania, E. (2019). AI Safety, Security, and Stability Among Great Powers: Options, Challenges, and Lessons Learned for Pragmatic Engagement. Center for Security and Emerging Technology. non-peer-reviewed Ch. 66
  216. Intergovernmental Panel on Climate Change (2013). Procedures for the Preparation, Review, Acceptance, Adoption, Approval and Publication of IPCC Reports (Appendix A to the Principles Governing IPCC Work). non-peer-reviewed Ch. 66
  217. Jaffee, D. M., and Russell, T. (1997). Catastrophe Insurance, Capital Markets, and Uninsurable Risks. The Journal of Risk and Insurance. Ch. 63
  218. Jasanoff, S., Saha, K., and Hurlbut, J. B. (2015). CRISPR Democracy: Gene Editing and the Need for Inclusive Deliberation. Issues in Science and Technology. non-peer-reviewed Ch. 64
  219. Jensen, M. C., and Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics. Ch. 61
  220. Jervis, R. (1978). Cooperation under the Security Dilemma. World Politics. Ch. 65
  221. Jervis, R. (2017). Perception and Misperception in International Politics. Princeton University Press. Ch. 65
  222. Joint California Policy Working Group on AI Frontier Models (2025). The California Report on Frontier AI Policy. Office of the Governor of California. non-peer-reviewed Ch. 63 Ch. 67
  223. Jones, C. I. (2024). The AI Dilemma: Growth versus Existential Risk. American Economic Review: Insights. Ch. 68
  224. Kapoor, S., Bommasani, R., Klyman, K., Longpre, S., Ramaswami, A., Cihon, P., … Narayanan, A. (2024b). On the Societal Impact of Open Foundation Models. arXiv. preprint Ch. 63 Ch. 67
  225. Karger, P., and Schell, R. (2003). Multics security evaluation: vulnerability analysis. 18th Annual Computer Security Applications Conference, 2002. Proceedings.. Ch. 64
  226. Kasirzadeh, A. (2025). Two types of AI existential risk: decisive and accumulative. Philosophical Studies. Ch. 68
  227. Katzke, C., and Futerman, G. (2024). The Manhattan Trap: Why a Race to Artificial Superintelligence is Self-Defeating. arXiv. preprint Ch. 65
  228. Kemeny, J. G. (1979). The Need for Change, the Legacy of TMI: Report of the President's Commission on the Accident at Three Mile Island. Pergamon Press. non-peer-reviewed Ch. 64
  229. Keohane, R. O. (1984). After Hegemony: Cooperation and Discord in the World Political Economy. Princeton University Press. Ch. 66
  230. Keohane, R. O., and Victor, D. G. (2011). The Regime Complex for Climate Change. Perspectives on Politics. Ch. 66
  231. Koessler, L., Schuett, J., and Anderljung, M. (2024). Risk thresholds for frontier AI. arXiv. preprint Ch. 62
  232. Kokotajlo, D., Alexander, S., Larsen, T., Lifland, E., and Dean, R. (2025). AI 2027. AI Futures Project (ai-2027.com). non-peer-reviewed Ch. 65
  233. Kolt, N., Anderljung, M., Barnhart, J., Brass, A., Esvelt, K., Hadfield, G. K., … Woodside, T. (2024). Responsible Reporting for Frontier AI Development. arXiv. preprint Ch. 67
  234. Korea, R. o. (2025). Framework Act on the Development of Artificial Intelligence and Establishment of Trust. Center for Security and Emerging Technology (translation). non-peer-reviewed Ch. 63
  235. Koremenos, B., Lipson, C., and Snidal, D. (2001). The Rational Design of International Institutions. International Organization. Ch. 66
  236. Korinek, A., and Balwit, A. (2023). Aligned with Whom? The Oxford Handbook of AI Governance. Ch. 61 Ch. 68
  237. Korinek, A., and Stiglitz, J. E. (2019). Artificial Intelligence and Its Implications for Income Distribution and Unemployment. The Economics of Artificial Intelligence. Ch. 68
  238. Korinek, A., and Suh, D. (2024). Scenarios for the Transition to AGI. National Bureau of Economic Research. working paper Ch. 68
  239. Korinek, A., and Vipra, J. (2024). Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence. National Bureau of Economic Research. non-peer-reviewed Ch. 65 Ch. 68
  240. Kraakman (1986). Gatekeepers: The Anatomy of a Third-Party Enforcement Strategy. The Journal of Law, Economics, and Organization. Ch. 67
  241. Krimsky, S. (1982). Genetic Alchemy: The Social History of the Recombinant DNA Controversy. Ch. 64
  242. Kulp, G., Gonzales, D., Smith, E., Heim, L., Puri, P., Vermeer, M. J. D., and Winkelman, Z. (2024). Hardware-Enabled Governance Mechanisms: Developing Technical Solutions to Exempt Items Otherwise Classified Under Export Control Classification Numbers 3A090 and 4A090. RAND Corporation, WR-A3056-1. working paper Ch. 66
  243. Kulveit, J., Douglas, R., Ammann, N., Turan, D., Krueger, D., and Duvenaud, D. (2025). Gradual Disempowerment: Systemic Existential Risks from Incremental AI Development. arXiv. preprint Ch. 68
  244. Kunreuther, H., Hogarth, R., and Meszaros, J. (1993). Insurer ambiguity and market failure. Journal of Risk and Uncertainty. Ch. 63
  245. Kydland, F. E., and Prescott, E. C. (1977). Rules Rather than Discretion: The Inconsistency of Optimal Plans. Journal of Political Economy. Ch. 61
  246. Laffont, J.-J., and Tirole, J. (1991). The Politics of Government Decision-Making: A Theory of Regulatory Capture. The Quarterly Journal of Economics. Ch. 61 Ch. 63
  247. Lander, E. S., Baylis, F., Zhang, F., Charpentier, E., Berg, P., Bourgain, C., … Winnacker, E.-L. (2019). Adopt a moratorium on heritable genome editing. Nature. Ch. 64
  248. Lazar, S., and Nelson, A. (2023). AI safety on whose terms? Science. Ch. 61
  249. Legislature, C. S. (2024). SB-1047 Safe and Secure Innovation for Frontier Artificial Intelligence Models Act. California Legislative Information (enrolled 09/03/24; vetoed). non-peer-reviewed Ch. 63
  250. Legislature, N. Y. S. (2025a). Responsible AI Safety and Education Act (New York RAISE Act). non-peer-reviewed Ch. 63
  251. Legislature, C. S. (2025b). SB-53 Artificial intelligence models: large developers. California Legislative Information (chaptered 09/29/25). non-peer-reviewed Ch. 61 Ch. 62 Ch. 63 Ch. 67
  252. Legislature, N. Y. S. (2026). Transparency and safety requirements for developers of artificial intelligence frontier models (New York Laws of 2026, Chapter 96). non-peer-reviewed Ch. 63
  253. Lessig, L. (1999). Code: and other laws of cyberspace. Basic Books. Ch. 64
  254. Leuz, C., and Wysocki, P. D. (2016). The Economics of Disclosure and Financial Reporting Regulation: Evidence and Suggestions for Future Research. Journal of Accounting Research. Ch. 67
  255. Lewis, H., Budnitz, R., Kouts, H., Loewenstein, W., Rowe, W., von Hippel, F., and Zachariasen, F. (1978). Risk Assessment Review Group report to the U. S. Nuclear Regulatory Commission. [PWR; BWR]. Office of Scientific and Technical Information (OSTI). non-peer-reviewed Ch. 64
  256. Liesenfeld, A., and Dingemanse, M. (2024). Rethinking open source generative AI: open washing and the EU AI Act. The 2024 ACM Conference on Fairness, Accountability, and Transparency. Ch. 63 Ch. 67
  257. Lior, A. (2022). Insuring AI: The Role of Insurance in Artificial Intelligence Regulation. Harvard Journal of Law & Technology. Ch. 63
  258. Longpre, S., Kapoor, S., Klyman, K., Ramaswami, A., Bommasani, R., Blili-Hamelin, B., … Henderson, P. (2024a). A Safe Harbor for AI Evaluation and Red Teaming. arXiv. preprint Ch. 63 Ch. 67
  259. Longpre, S., Klyman, K., Appel, R. E., Kapoor, S., Bommasani, R., Sahar, M., … Narayanan, A. (2025). In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI. arXiv. preprint Ch. 64 Ch. 67
  260. Loury, G. C. (1979). Market Structure and Innovation. The Quarterly Journal of Economics. Ch. 65
  261. Maas, M. M. (2019). How viable is international arms control for military artificial intelligence? Three lessons from nuclear weapons. Contemporary Security Policy. Ch. 64 Ch. 66
  262. Maas, M. M. (2023). Advanced AI Governance: A Literature Review of Problems, Options, and Proposals. Elsevier BV. preprint Ch. 66
  263. MacKenzie, D. (2006). An Engine, Not a Camera. The MIT Press. Ch. 64 Ch. 67
  264. MacKenzie, D., and Spears, T. (2014). ‘The formula that killed Wall Street’: The Gaussian copula and modelling practices in investment banking. Social Studies of Science. Ch. 64 Ch. 67
  265. Metr (2025a). Common Elements of Frontier AI Safety Policies. METR. non-peer-reviewed Ch. 62 Ch. 65 Ch. 67
  266. Metr (2026b). Summary of METR's predeployment evaluation of GPT-5.6 Sol. METR. non-peer-reviewed Ch. 67
  267. Meyer, J. W., and Rowan, B. (1977). Institutionalized Organizations: Formal Structure as Myth and Ceremony. American Journal of Sociology. Ch. 62
  268. Miceli, M., and Posada, J. (2022). The Data-Production Dispositif. Proceedings of the ACM on Human-Computer Interaction. Ch. 68
  269. Ministry of Foreign Affairs of the People's Republic of China (2023). Global AI Governance Initiative. Ministry of Foreign Affairs of the People's Republic of China. non-peer-reviewed Ch. 65 Ch. 66
  270. Mitchell, M., Wu, S., Zaldivar, A., Barnes, P., Vasserman, L., Hutchinson, B., … Gebru, T. (2019). Model Cards for Model Reporting. Proceedings of the Conference on Fairness, Accountability, and Transparency. Ch. 67
  271. Mittelstadt, B. (2019). Principles alone cannot guarantee ethical AI. Nature Machine Intelligence. Ch. 61
  272. Moe, T. M. (1984). The New Economics of Organization. American Journal of Political Science. Ch. 61
  273. Moore, D. A., Tetlock, P. E., Tanlu, L., and Bazerman, M. H. (2006). Conflicts Of Interest And The Case Of Auditor Independence: Moral Seduction And Strategic Issue Cycling. Academy of Management Review. Ch. 67
  274. Murphy, B., Bowen, D., Mohammadzadeh, S., Tseng, T., Broomfield, J., Gleave, A., and Pelrine, K. (2025). Jailbreak-Tuning: Models Efficiently Learn Jailbreak Susceptibility. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. Ch. 63
  275. Narayanan, A., and Kapoor, S. (2025). AI as Normal Technology. Knight First Amendment Institute at Columbia University. non-peer-reviewed Ch. 65 Ch. 68
  276. National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research (1979). The Belmont Report: Ethical Principles and Guidelines for the Protection of Human Subjects of Research. U.S. Department of Health, Education, and Welfare. non-peer-reviewed Ch. 64
  277. National Governance Committee for New Generation Artificial Intelligence (2021). 新一代人工智能伦理规范 (Ethical Norms for New Generation Artificial Intelligence). Ministry of Science and Technology of the People's Republic of China. non-peer-reviewed Ch. 63 Ch. 66
  278. National Telecommunications and Information Administration (2024). Dual-Use Foundation Models with Widely Available Model Weights Report. U.S. Department of Commerce, NTIA. non-peer-reviewed Ch. 63 Ch. 67
  279. Near, J. P., and Miceli, M. P. (1985). Organizational dissidence: The case of whistle-blowing. Journal of Business Ethics. Ch. 67
  280. Nekoto, W., Marivate, V., Matsila, T., Fasubaa, T., Fagbohungbe, T., Akinola, S. O., … Bashir, A. (2020). Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages. Findings of the Association for Computational Linguistics: EMNLP 2020. Ch. 63 Ch. 67
  281. Nevo, S., Lahav, D., Karpur, A., Bar-On, Y., Bradley, H. A., and Alstott, J. (2024). Securing AI Model Weights: Preventing Theft and Misuse of Frontier Models. RAND Corporation. doi:10.7249/rra2849-1. Ch. 66
  282. Nordhaus, W. (2015). Climate Clubs: Overcoming Free-riding in International Climate Policy. American Economic Review. Ch. 65
  283. Nuclear Regulatory Commission, W. D. (. (1975). Reactor safety study. An assessment of accident risks in U. S. commercial nuclear power plants. Executive summary. [PWR and BWR]. Office of Scientific and Technical Information (OSTI). non-peer-reviewed Ch. 64
  284. Nye, J. S. (2017). Deterrence and Dissuasion in Cyberspace. International Security. Ch. 66
  285. O'Keefe, C., Cihon, P., Garfinkel, B., Flynn, C., Leung, J., and Dafoe, A. (2019). The Windfall Clause: Distributing the Benefits of AI for the Common Good. arXiv. preprint Ch. 61 Ch. 68
  286. O'Keefe, C., Ramakrishnan, K., Tay, J., and Winter, C. (2025). Law-Following AI: Designing AI Agents to Obey Human Laws. Fordham Law Review. Ch. 68
  287. Office of the Historian, U. D. o. S. (1946). The Acheson-Lilienthal & Baruch Plans, 1946. Office of the Historian, U.S. Department of State (Milestones in the History of U.S. Foreign Relations). non-peer-reviewed Ch. 64
  288. ÓhÉigeartaigh, S. S., Whittlestone, J., Liu, Y., Zeng, Y., and Liu, Z. (2020). Overcoming Barriers to Cross-cultural Cooperation in AI Ethics and Governance. Philosophy & Technology. Ch. 65 Ch. 66
  289. Olson, M. (1965). The Logic of Collective Action. Harvard University Press. Ch. 65
  290. OpenAI (2018). OpenAI Charter. OpenAI. non-peer-reviewed Ch. 61 Ch. 65
  291. OpenAI (2025a). Built to benefit everyone. OpenAI. non-peer-reviewed Ch. 61
  292. OpenAI (2025b). Expanding on what we missed with sycophancy. OpenAI. non-peer-reviewed Ch. 65
  293. OpenAI (2025d). OpenAI Model Spec. OpenAI. non-peer-reviewed Ch. 62
  294. OpenAI (2025e). Preparedness Framework Version 2. OpenAI. non-peer-reviewed Ch. 62 Ch. 65 Ch. 67
  295. OpenAI (2026l). GPT-6 Astra System Card. OpenAI Deployment Safety Hub. non-peer-reviewed Ch. 62
  296. OpenAI (2026q). Pacing model development in an era of cyber-critical capabilities. OpenAI. non-peer-reviewed Ch. 62 Ch. 64 Ch. 65
  297. OpenAI, :, Hurst, A., Lerer, A., Goucher, A. P., Perelman, A., … Malkov, Y. (2024a). GPT-4o System Card. arXiv. preprint Ch. 67
  298. OpenAI, :, Jaech, A., Kalai, A., Lerer, A., Richardson, A., … Li, Z. (2024b). OpenAI o1 System Card. arXiv. preprint Ch. 67
  299. Ord, T. (2020). The Precipice. Hachette Books. Ch. 68
  300. Organisation for the Prohibition of Chemical Weapons (1993). Chemical Weapons Convention. non-peer-reviewed Ch. 64 Ch. 66
  301. Osiel, M. J. (1998). Obeying Orders: Atrocity, Military Discipline, and the Law of War. California Law Review. Ch. 68
  302. Ostrom, E. (1990). Governing the Commons. Cambridge University Press. Ch. 65
  303. (2010). The Oxford Handbook of Regulation. Oxford University Press. Ch. 63
  304. Parker, C. (2002). The Open Corporation. Cambridge University Press. Ch. 62
  305. Parno, B., Howell, J., Gentry, C., and Raykova, M. (2013). Pinocchio: Nearly Practical Verifiable Computation. 2013 IEEE Symposium on Security and Privacy. Ch. 66
  306. Pauly, M. V. (1982). The economics of moral hazard: comment. Readings in the Economics of Contract Law. Ch. 63
  307. Pearl, J., and Bareinboim, E. (2014). External Validity: From Do-Calculus to Transportability Across Populations. Statistical Science. Ch. 64
  308. Perrigo, B. (2023). Exclusive: OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic. TIME. non-peer-reviewed Ch. 68
  309. Pettit, P. (1997). Republicanism. Oxford University PressOxford. Ch. 61 Ch. 68
  310. Pettit, P. (2012). On the People's Terms. Cambridge University Press. Ch. 61 Ch. 68
  311. Pilz, K., Heim, L., and Brown, N. (2023). Increased Compute Efficiency and the Diffusion of AI Capabilities. arXiv. preprint Ch. 65 Ch. 66
  312. Platt, R., Brown, J. S., Robb, M., McClellan, M., Ball, R., Nguyen, M. D., and Sherman, R. E. (2018). The FDA Sentinel Initiative — An Evolving National Resource. New England Journal of Medicine. Ch. 63
  313. Powell, R. (2006). War as a Commitment Problem. International Organization. Ch. 65
  314. Power, M. (1997). The audit society: rituals of verification. Oxford University Press. Ch. 67
  315. Quinlivan, J. T. (1999). Coup-proofing: Its Practice and Consequences in the Middle East. International Security. Ch. 68
  316. Raji, I. D., and Buolamwini, J. (2019). Actionable Auditing. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society. Ch. 67
  317. Raji, I. D., Smart, A., White, R. N., Mitchell, M., Gebru, T., Hutchinson, B., … Barnes, P. (2020). Closing the AI accountability gap. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency. Ch. 62
  318. Raji, I. D., Xu, P., Honigsberg, C., and Ho, D. (2022). Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance. Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society. Ch. 61 Ch. 67
  319. Rees, J. V. (1994). Hostages of Each Other: The Transformation of Nuclear Safety since Three Mile Island. Ch. 62 Ch. 64
  320. Ren, R., Basart, S., Khoja, A., Gatti, A., Phan, L., Yin, X., … Hendrycks, D. (2024b). Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress? arXiv. preprint Ch. 61 Ch. 62 Ch. 65 Ch. 67
  321. Reuel, A., Bucknall, B., Casper, S., Fist, T., Soder, L., Aarne, O., … Trager, R. (2024b). Open Problems in Technical AI Governance. arXiv. preprint Ch. 63 Ch. 67
  322. Review, J. A. T. (2019). Boeing 737 MAX Flight Control System: Observations, Findings, and Recommendations. Federal Aviation Administration. non-peer-reviewed Ch. 64
  323. Roberts, H., Cowls, J., Morley, J., Taddeo, M., Wang, V., and Floridi, L. (2021). The Chinese approach to artificial intelligence: an analysis of policy, ethics, and regulation. AI & SOCIETY. Ch. 63 Ch. 65
  324. Rose, N. L. (1990). Profitability and Product Quality: Economic Determinants of Airline Safety Performance. Journal of Political Economy. Ch. 65
  325. Ross, M. L. (2001). Does Oil Hinder Democracy? World Politics. Ch. 68
  326. Russell, B., and Einstein, A. (1955). Statement: The Russell-Einstein Manifesto. Pugwash Conferences on Science and World Affairs. non-peer-reviewed Ch. 64
  327. Safety, I. D. o. A. (2024). IDAIS-Beijing Statement. International Dialogues on AI Safety. non-peer-reviewed Ch. 65 Ch. 66
  328. Sagan, S. D. (1993). The Limits of Safety. Princeton University Press. Ch. 64
  329. Sagan, S. D. (1996). Why Do States Build Nuclear Weapons?: Three Models in Search of a Bomb. International Security. Ch. 66
  330. Salib, P., and Goldstein, S. (2024). AI Rights for Human Safety. Elsevier BV. preprint Ch. 63
  331. Salvi, F., Horta Ribeiro, M., Gallotti, R., and West, R. (2025). On the conversational persuasiveness of GPT-4. Nature Human Behaviour. Ch. 68
  332. Sastry, G., Heim, L., Belfield, H., Anderljung, M., Brundage, M., Hazell, J., … Coyle, D. (2024). Computing Power and the Governance of Artificial Intelligence. arXiv. preprint Ch. 66 Ch. 68
  333. Schelling, T. C. (1960). The Strategy of Conflict. Harvard University Press. Ch. 61 Ch. 65
  334. Scherer, M. U. (2015). Regulating Artificial Intelligence Systems: Risks, Challenges, Competencies, and Strategies. Elsevier BV. preprint Ch. 63
  335. Schuett, J. (2025a). Frontier AI developers need an internal audit function. Risk Analysis. Ch. 62
  336. Schuett, J. (2025b). Three lines of defense against risks from AI. AI & SOCIETY. Ch. 62
  337. Schuett, J., Dreksler, N., Anderljung, M., McCaffary, D., Heim, L., Bluemke, E., and Garfinkel, B. (2023). Towards best practices in AGI safety and governance: A survey of expert opinion. arXiv. preprint Ch. 62
  338. Schuett, J., Reuel, A.-K., and Carlier, A. (2025). How to design an AI ethics board. AI and Ethics. Ch. 62
  339. Seger, E., Dreksler, N., Moulange, R., Dardaman, E., Schuett, J., Wei, K., … Gupta, A. (2023b). Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives. arXiv. preprint Ch. 63
  340. Selbst, A. D. (2020). Negligence and AI’s Human Users. Boston University Law Review. Ch. 63
  341. Sevilla, J., Heim, L., Ho, A., Besiroglu, T., Hobbhahn, M., and Villalobos, P. (2022). Compute Trends Across Three Eras of Machine Learning. 2022 International Joint Conference on Neural Networks (IJCNN). Ch. 65
  342. Sevilla, J., Besiroglu, T., Cottier, B., You, J., Roldán, E., Villalobos, P., and Erdil, E. (2024). Can AI scaling continue through 2030? Epoch AI. non-peer-reviewed Ch. 65
  343. Shanghai AI Laboratory, and AI, C. (2025). Frontier AI Risk Management Framework. Shanghai AI Laboratory and Concordia AI. non-peer-reviewed Ch. 62 Ch. 65
  344. Sharma, M., McCain, M., Douglas, R., and Duvenaud, D. (2026). Who's in Charge? Disempowerment Patterns in Real-World LLM Usage. arXiv. preprint Ch. 68
  345. Shavell, S. (1979). On Moral Hazard and Insurance. The Quarterly Journal of Economics. Ch. 63
  346. Shavell, S. (1980). Strict Liability versus Negligence. The Journal of Legal Studies. Ch. 63
  347. Shavell, S. (1984). Liability for Harm versus Regulation of Safety. The Journal of Legal Studies. Ch. 63
  348. Shavit, Y. (2023). What does it take to catch a Chinchilla? Verifying Rules on Large-Scale Neural Network Training via Compute Monitoring. arXiv. preprint Ch. 66
  349. Sheehan, M. (2023). China’s AI Regulations and How They Get Made. Carnegie Endowment for International Peace. non-peer-reviewed Ch. 63 Ch. 65
  350. Shevlane, T. (2022). Structured access: an emerging paradigm for safe AI deployment. arXiv. preprint Ch. 63 Ch. 67
  351. Shevlane, T., and Dafoe, A. (2019). The Offense-Defense Balance of Scientific Knowledge: Does Publishing AI Research Reduce Misuse? arXiv. preprint Ch. 63
  352. Shulman, C., and Bostrom, N. (2021). Sharing the World with Digital Minds. Rethinking Moral Status. Ch. 68
  353. Siegmann, C., and Anderljung, M. (2022). The Brussels Effect and Artificial Intelligence: How EU regulation will impact the global AI market. arXiv. preprint Ch. 63
  354. Singh, A., Fry, A., Perelman, A., Tart, A., Ganesh, A., El-Kishky, A., … Wang, Z. (2025). OpenAI GPT-5 System Card. arXiv. preprint Ch. 67
  355. Smuha, N. A. (2021). From a ‘race to AI’ to a ‘race to AI regulation’: regulatory competition for artificial intelligence. Law, Innovation and Technology. Ch. 63 Ch. 65
  356. Solaiman, I. (2023). The Gradient of Generative AI Release: Methods and Considerations. arXiv. preprint Ch. 63
  357. Solum, L. B. (1992). Legal Personhood for Artificial Intelligences. North Carolina Law Review. Ch. 63
  358. Souly, A., Kirk, R., Merizian, J., D'Cruz, A., and Davies, X. (2026). UK AISI Alignment Evaluation Case-Study. arXiv. preprint Ch. 67
  359. Spafford, E. H. (1989). The internet worm program: an analysis. ACM SIGCOMM Computer Communication Review. Ch. 64
  360. Stein, M., Bernardi, J., and Dunlop, C. (2024). The Role of Governments in Increasing Interconnected Post-Deployment Monitoring of AI. arXiv. preprint Ch. 63
  361. Stigler, G. J. (1971). The Theory of Economic Regulation. The Bell Journal of Economics and Management Science. Ch. 61 Ch. 63
  362. Stilgoe, J., Owen, R., and Macnaghten, P. (2013). Developing a framework for responsible innovation. Research Policy. Ch. 63
  363. Summerfield, C., Argyle, L., Bakker, M., Collins, T., Durmus, E., Eloundou, T., … Botvinick, M. (2024). How will advanced AI systems impact democracy? arXiv. preprint Ch. 68
  364. Summit, C. a. t. A. S. (2023). The Bletchley Declaration by Countries Attending the AI Safety Summit, 1-2 November 2023. UK Government (GOV.UK). non-peer-reviewed Ch. 66
  365. Sun, H., Li, J., and Zhang, H. (2024b). zkLLM: Zero Knowledge Proofs for Large Language Models. Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security. Ch. 66 Ch. 67
  366. Sunstein, C. R. (2003). Beyond the Precautionary Principle. University of Pennsylvania Law Review. Ch. 63 Ch. 64
  367. Sykes, A. O. (1984). The Economics of Vicarious Liability. The Yale Law Journal. Ch. 63
  368. Tabassi, E. (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). National Institute of Standards and Technology (U.S.). non-peer-reviewed Ch. 63
  369. Talmadge, C. (2015). The Dictator's Army. Cornell University Press. Ch. 68
  370. Trager, R., Harack, B., Reuel, A., Carnegie, A., Heim, L., Ho, L., … Villalobos, J. J. (2023). International Governance of Civilian AI: A Jurisdictional Certification Approach. arXiv. preprint Ch. 66
  371. Trammell, P., and Korinek, A. (2026). Economic Growth Under Transformative AI. Annual Review of Economics. Ch. 68
  372. Turner, E. H., Matthews, A. M., Linardatos, E., Tell, R. A., and Rosenthal, R. (2008). Selective Publication of Antidepressant Trials and Its Influence on Apparent Efficacy. New England Journal of Medicine. Ch. 67
  373. Tutt, A. (2016). An FDA for Algorithms. SSRN Electronic Journal. Ch. 63
  374. U.S. Department of State, B. o. A. C. V., and Compliance (1963). Treaty Banning Nuclear Weapon Tests in the Atmosphere, in Outer Space and Under Water. U.S. Department of State (archived treaty page). non-peer-reviewed Ch. 64
  375. UK AI Security Institute (2025a). AISI Research Agenda. UK AI Security Institute. non-peer-reviewed Ch. 63
  376. UK AI Security Institute (2025b). Frontier AI Trends Report. UK AI Security Institute. non-peer-reviewed Ch. 63 Ch. 66 Ch. 67
  377. United Nations (1972). Convention on the prohibition of the development, production and stockpiling of bacteriological (biological) and toxin weapons and on their destruction. non-peer-reviewed Ch. 66
  378. United Nations Diplomatic Conference of Plenipotentiaries on the Establishment of an International Criminal Court (1998). Rome Statute of the International Criminal Court, Article 33: Superior orders and prescription of law. International Criminal Court. non-peer-reviewed Ch. 68
  379. United Nations Environment Programme (1987). Montreal Protocol on Substances that Deplete the Ozone Layer. United Nations Environment Programme. non-peer-reviewed Ch. 64
  380. United Nations General Assembly (2015). Report of the Group of Governmental Experts on Developments in the Field of Information and Telecommunications in the Context of International Security. United Nations, A/70/174. non-peer-reviewed Ch. 64 Ch. 66
  381. United Nations High-level Advisory Body on Artificial Intelligence (2024). Governing AI for Humanity: Final Report. United Nations. non-peer-reviewed Ch. 66
  382. United Nations Office for Disarmament Affairs (1968). Treaty on the Non-Proliferation of Nuclear Weapons (NPT). United Nations Office for Disarmament Affairs. non-peer-reviewed Ch. 66
  383. United Nations Office for Disarmament Affairs (1972). Biological Weapons Convention. non-peer-reviewed Ch. 64
  384. United States Congress (1962). Drug Amendments of 1962 (Kefauver-Harris Amendments). United States Statutes at Large 76. non-peer-reviewed Ch. 63 Ch. 64
  385. Üstün, A., Aryabumi, V., Yong, Z., Ko, W.-Y., D’souza, D., Onilude, G., … Hooker, S. (2024). Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Ch. 63
  386. Vaynman, J. (2026). Enemies in Agreement. Cambridge University Press. Ch. 66
  387. Veale, M., and Zuiderveen Borgesius, F. (2021). Demystifying the Draft EU Artificial Intelligence Act — Analysing the good, the bad, and the unclear elements of the proposed approach. Computer Law Review International. Ch. 63
  388. Verrecchia, R. E. (1983). Discretionary disclosure. Journal of Accounting and Economics. Ch. 67
  389. Vipra, J., and Korinek, A. (2023). Market Concentration Implications of Foundation Models. arXiv. preprint Ch. 65 Ch. 68
  390. Vladeck, D. C. (2014). Machines Without Principals: Liability Rules and Artificial Intelligence. Washington Law Review. Ch. 63
  391. Walfish, M., and Blumberg, A. J. (2015). Verifying computations without reexecuting them. Communications of the ACM. Ch. 66
  392. Wang, J., Huang, K., Klyman, K., and Bommasani, R. (2025c). Do AI Companies Make Good on Voluntary Commitments to the White House? arXiv. preprint Ch. 62
  393. Wasil, A. R., Reed, T., Miller, J. W., and Barnett, P. (2024). Verification methods for international AI agreements. arXiv. preprint Ch. 66
  394. Watts, R. L., and Zimmerman, J. L. (1983). Agency Problems, Auditing, and the Theory of the Firm: Some Evidence. The Journal of Law and Economics. Ch. 67
  395. Weidinger, L., Rauh, M., Marchal, N., Manzini, A., Hendricks, L. A., Mateos-Garcia, J., … Isaac, W. (2023a). Sociotechnical Safety Evaluation of Generative AI Systems. arXiv. preprint Ch. 64
  396. Weil, G. (2024). Closing the AI Accountability Gap: Strict Liability and Punitive Damages for Advanced Artificial Intelligence. Elsevier BV. preprint Ch. 63
  397. Weingast, B. R., and Moran, M. J. (1983). Bureaucratic Discretion or Congressional Control? Regulatory Policymaking by the Federal Trade Commission. Journal of Political Economy. Ch. 61
  398. White, L. J. (2010). Markets: The Credit Rating Agencies. Journal of Economic Perspectives. Ch. 64 Ch. 67
  399. Whittaker, M. (2021). The steep cost of capture. Interactions. Ch. 61
  400. Whittlestone, J., and Clark, J. (2021). Why and How Governments Should Monitor AI Development. arXiv. preprint Ch. 63 Ch. 67
  401. Widder, D. G., Whittaker, M., and West, S. M. (2024). Why ‘open’ AI systems are actually closed, and why this matters. Nature. Ch. 61 Ch. 63 Ch. 67
  402. Wong, P.-H. (2020). Cultural Differences as Excuses? Human Rights and Cultural Values in Global Ethics and Governance of AI. Philosophy & Technology. Ch. 66
  403. World Medical Association (1964). WMA Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Participants. World Medical Association. non-peer-reviewed Ch. 64
  404. xAI (2025a). Grok prompts. GitHub (xai-org). non-peer-reviewed Ch. 68
  405. xAI (2025b). We want to update you on an incident that happened with our Grok response bot on X yesterday. non-peer-reviewed Ch. 68
  406. xAI (2025c). xAI Risk Management Framework. xAI. non-peer-reviewed Ch. 62
  407. Xu, F. (., Song, Y., Li, B., Tang, Y., Jain, K., Bao, M., … Neubig, G. (2025). TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks. Advances in Neural Information Processing Systems 38. Ch. 68
  408. Young, M., Katell, M., and Krafft, P. (2022). Confronting Power and Corporate Capture at the FAccT Conference. 2022 ACM Conference on Fairness Accountability and Transparency. Ch. 61
  409. Yudkowsky, E., and Soares, N. (2025). If Anyone Builds It, Everyone Dies. Little, Brown and Company. Ch. 64 Ch. 65
  410. Zaidi, W., and Dafoe, A. (2021). International Control of Powerful Technology: Lessons from the Baruch Plan for Nuclear Weapons. Centre for the Governance of AI. working paper Ch. 64
  411. Zwetsloot, R., and Dafoe, A. (2019). Thinking About Risks From AI: Accidents, Misuse and Structure. Lawfare. non-peer-reviewed Ch. 65 Ch. 68