Enabling Frontier Lab Collaboration to Mitigate AI Safety Risks
DOI:
https://doi.org/10.70777/si.v2i6.16439Keywords:
AI Safety, Frontier AI Labs, AI lab Collaboration, AI lab Antitrust Policy, AI Developmental Pause, AI lab information Sharing, National Cooperative Research and Production Act (NCRPA), AI Regulatory GuidanceAbstract
Frontier AI labs face intense commercial competitive pressure to develop increasingly powerful systems, raising the risk of a race to the bottom on safety. Voluntary coordination among labs — including by way of joint safety testing, information sharing, and resource pooling — could reduce catastrophic and existential risks. But the risk of antitrust scrutiny may deter such collaboration, even when it is demonstrably beneficial. This paper explores how U.S. antitrust policy can evolve to accommodate AI safety cooperation without abandoning core competition principles. After outlining the risks of unconstrained AI development and the benefits of lab–lab coordination, the paper analyses potential antitrust concerns, including output restrictions, market allocation, and information sharing. It then surveys a range of legislative and regulatory reforms that could provide legal clarity and safe harbours that will encourage responsible collaboration.
References
Charlotte Stix and Matthijs M Maas, Bridging the gap: the case for an ‘Incompletely Theorized Agreement’ on AI policy (2021) 1 AI and Ethics 261; DOI: https://doi.org/10.1007/s43681-020-00037-w
Thorin Bristow and Luke Thorburn, Don’t slip into binary thinking about AI (2023);
Emily M Bender and Alex Hanna, The AI Con: How To Fight Big Tech’s Hype and Create the Future We Want (2025).
Amanda Askell et al, The Role of Cooperation in Responsible AI Development (2019) 9: “The race to the bottom on safety
Anthropic, Submission to the National Telecommunications and Information Administration (2024).
Anthropic, Announcing our updated Responsible Scaling Policy (Oct. 15, 2024), https://www.anthropic.com/news/announcing-our-updated-responsible-scaling-policy.
Matt Sutton and Damian Ruck, Indirect Prompt Injection: Generative AI’s Greatest Security Flaw (2024), https://cetas.turing.ac.uk/publications/indirect-prompt-injection-generative-ais-greatest-security-flaw.
Microsoft Threat Intelligence, AI jailbreaks; What they are and how they can be mitigated (2024), https://www.microsoft.com/en-us/security/blog/2024/06/04/ai-jailbreaks-what-they-are-and-how-they-can-be-mitigated/.
Dan Hendrycks et al, An Overview of Catastrophic AI Risks (Center for AI Safety) 14.
See David Luckey et al, Mitigating Risks at the Intersection of Artificial Intelligence and Chemical and Biological Weapons (2025); Elliot McKernon, AI and Chemical, Biological, Radiological, & Nuclear Hazards (2024), https://www.convergenceanalysis.org/ai-regulatory-landscape/ai-and-chemical-biological-radiological-and-nuclear-hazards.
Dan Hendrycks et al, An Overview of Catastrophic AI Risks (Center for AI Safety) 34.
Ryan Greenblatt et al, Alignment faking in large language models (2024), https://arxiv.org/pdf/2412.14093.
Fabien Roger and Ryan Greenblatt, Preventing Language Models from Hiding Their Reasoning (2023), https://arxiv.org/pdf/2310.18512; Tamera Lanham et al, Measuring Faithfulness in Chain-of-Though Reasoning (2023), https://storage.prod.researchhub.com/uploads/papers/2023/08/01/2307.13702.pdf.
Caroline Delbert, A.I. Can Now Replicate Itself without Human Help. Can We Control What Comes Next? (2025), https://www.popularmechanics.com/science/a64288856/ai-replication/.
Sarah Kreps, Democratizing Harm: Artificial Intelligence in the Hands of Nonstate Actors (2021), https://www.brookings.edu/wp-content/uploads/2021/11/FP_20211122_ai_nonstate_actors_kreps.pdf; Valerie Wirtschafter, The implication of the AI boom for nonstate armed actors (2024), https://www.brookings.edu/articles/the-implications-of-the-ai-boom-for-nonstate-armed-actors/;
Tom Davidson et al, AI-Enabled Coups: How a Small Group Could Use AI to Seize Power (2025), https://www.forethought.org/research/ai-enabled-coups-how-a-small-group-could-use-ai-to-seize-power.pdf.
OpenAI, Charter, https://openai.com/charter/.
Anthropic, Our Purpose, https://www.anthropic.com/company.
Microsoft, Principles and approach, https://www.microsoft.com/en-us/ai/principles-and-approach.
Google DeepMind, Build AI responsibly to benefit humanity, https://deepmind.google/about/.
Mark Gurman and Riley Griffin, Meta Poached Apple’s Ruoming Pang with Pay Package over $200 Million, Bloomberg (July 9, 2025), https://www.bloomberg.com/news/articles/2025-07-09/meta-poached-apple-s-pang-with-pay-package-over-200-million?embedded-checkout=true.
Amanda Askell et al, The Role of Cooperation in Responsible AI Development (2019) 8.
Wim Naudé and Nicola Dimitri, The race for an artificial general intelligence: implications for public policy, 35 AI & Society 367 (2020). DOI: https://doi.org/10.1007/s00146-019-00887-x
OpenAI, Charter, https://openai.com/charter/.
Commission Regulation 2023/1066 (2023), [7]–[8].
Federal Trade Commission and Department of Justice, Antitrust Guidelines for Collaborations Among Competitors (2000) (“Guidelines”). These Guidelines are discussed in detail below at page XX.
Stuart Armstrong, Nick Bostrom and Carl Shulman, Racing to the Precipice: A Model of Artificial Intelligence Development, Future of Humanity Institute (2013).
Frontier Model Forum, Membership, https://www.frontiermodelforum.org/membership/.
Frontier Model Forum, FMF Announces First-Of-Its-Kind Information-Sharing Agreement (Mar. 28, 2025), https://www.frontiermodelforum.org/updates/fmf-announces-first-of-its-kind-information-sharing-agreement/.
Frontier Model Forum, FMF Information-Sharing, https://www.frontiermodelforum.org/information-sharing/.
OpenAI, Findings from a pilot Anthropic–OpenAI alignment evaluation exercise: OpenAI Safety Tests (2025), https://openai.com/index/openai-anthropic-safety-evaluation/
Jide Alaga and Jonas Schuett, Coordinated pausing: An evaluation-based coordination scheme for frontier developers (2023) (“Coordinated pausing”).
OpenAI, Findings from a pilot Anthropic–OpenAI alignment evaluation exercise: OpenAI Safety Tests (2025), https://openai.com/index/openai-anthropic-safety-evaluation/; Anthropic, Findings from a Pilot Anthropic–OpenAI Alignment Evaluation Exercise (2025), https://alignment.anthropic.com/2025/openai-findings/.
OpenAI, Findings from a pilot Anthropic–OpenAI alignment evaluation exercise: OpenAI Safety Tests (2025), https://openai.com/index/openai-anthropic-safety-evaluation/.
Michael Gvozdenovic & Stephen Puttick, Perspectives on Part IV, in CURRENT ISSUES IN COMPETITION LAW: PRACTICE AND PERSPECTIVES 3 (Michael Gvozdenovic & Stephen Puttick, eds., 2021); ARIE FREIBERG, REGULATION IN AUSTRALIA 42 (2017).
Brown Shoe Co. v. United States, 370 U.S. 294, 320 (1962); Australian Competition and Consumer Commission v Pacific National Pty Ltd (No 2) [2019] FCA 669, [1261].
OECD, Interim Report on Convergence of Competition Policies (1994) 8–9.
Jack Corrigan, Promoting AI Innovation Through Competition: A Guide to Managing Market Power (2025). See generally Anu Bradford, The False Choice between Regulation and Innovation (2024).
Debby Wu, TSMC’s Dominance Is Starting to Worry More Than Just Rivals (2024), https://www.bloomberg.com/news/newsletters/2024-10-21/tsmc-s-dominance-is-starting-to-worry-more-than-just-rivals.
Julian West, ASML Holding: The Indispensable Monopoly Powering the AI Revolution (2025), https://www.ainvest.com/news/asml-holding-indispensable-monopoly-powering-ai-revolution-2507/#;
Renato Neves, ASML: The EUV Lithography Giant Navigating Challenges (2024), https://finance.yahoo.com/news/asml-euv-lithography-giant-navigating-130136031.html.
Associated Press, Nvidia is facing an antitrust probe from US regulators amid competitor complaints, report says (Aug. 2, 2024)
Anissa Gardizy, Stephanie Palazzolo, and Amir Efrati, Nvidia Faces DOJ Antitrust Probe Over Complaints from Rivals (Aug. 1, 2024), https://www.theinformation.com/articles/nvidia-faces-doj-antitrust-probe-over-complaints-from-rivals
RAND, Evaluating Natural Monopoly Conditions in the AI Foundation Model Market (2024).
Department of Justice and Federal Trade Commission, Guidelines at 1.
Anthropic, Submission to the National Telecommunications and Information Administration (2024).
Daniel Francis and Christopher Jon Sprigman, Antitrust: Principles, Cases, and Materials (2024) 2.Federal Trade Commission, Dealings with Competitors, https://www.ftc.gov/advice-guidance/competition-guidance/guide-antitrust-laws/dealings-competitors.
Daniel Francis and Christopher Jon Sprigman, Antitrust: Principles, Cases, and Materials (2024) 8.
Federal Trade Commission, The Enforcers, https://www.ftc.gov/advice-guidance/competition-guidance/guide-antitrust-laws/enforcers.
Federal Trade Commission and Department of Justice, Antitrust Guidelines for Collaborations Among Competitors (2000).
California Dental Association v. Federal Trade Commission, 526 U.S. 756, 770 (1999).
Jonathan Berman, The Failure of “Quick Look” Analyses of Antitrust Claims, 14 American University Business Law Review 79.
In re Cardizem CD Antitrust Litigation, 332 F.3d 896, 909 (6th Cir. 2003)
NCAA v. Board of Regents, 468 U.S. 85, 107–8.
Phillip Areeda, Louis Kaplow, and Aaron Edlin, Antitrust Analysis: Problems, Text, and Cases (2013) at 395 DOI: https://doi.org/10.2139/ssrn.2482772
Daniel Francis and Christopher Jon Sprigman, Antitrust: Principles, Cases, and Materials (2024) at 169.
NCAA v. Board of Regents, 468 U.S. 85, 100.
NCAA v. Board of Regents, 468 U.S. 85, 100–101. As Justice Stevens observed:
Polk Bros., Inc., v. Forest City Enterprises, Inc., 776 F.2d 185 (7th Cir. 1985).
OpenAI, Charter, https://openai.com/charter/.
Arizona v. Maricopa County Medical Society, 457 U.S. 332, 347 (1982)
United States v. Trenton Potteries Co., 273 U.S. 392 (1927).
United States v. Aiyer, 33 F.4th 97 (2d Cir. 2022)
Daniel Francis and Christopher Jon Sprigman, Antitrust: Principles, Cases, and Materials (2024) 208).
United States v. Topco Associates, 405 U.S. 596, 608 (1972)
Cynthia Hanwalt and Denise Hearn, Recommendations to Update the FTC & DOJ’s Guidelines for Collaborations Among Competitors (2024).
Helen Toner, Testimony before the U.S. House Committee on the Judiciary, Subcommittee on Courts, Intellectual Property, Artificial Intelligence, and the Internet, “Protecting Our Edge: Trade Secrets and the Global AI Arms Race” (2025) 7–8.
Ball, D. (2025). A Framework for the Private Governance of Frontier Artificial Intelligence. SuperIntelligence - Robotics - Safety & Alignment, 2(2). https://doi.org/10.70777/si.v2i2.14519 DOI: https://doi.org/10.70777/si.v2i2.14519
UTS Human Technology Institute and e61 Institute, AI, Productivity, and Australia’s Choice of Regulatory Framework (2025) 11.
U.S.C. §4301.
John T. Scott, The National Cooperative Research and Production Act, 2 Issues in Competition Law and Policy 1297 (2008).
Tom Wheeler and Blair Levin, With AI, we need both competition and safety (2024), https://www.brookings.edu/articles/with-ai-we-need-both-competition-and-safety/, citing United States v. United States Gypsum Co, 438 U.S. 422 (1978).
Department of Justice, Filing a Notification under the NCRPA, https://www.justice.gov/atr/filing-notification-under-ncrpa.
John T. Scott, The National Cooperative Research and Production Act, 2 Issues in Competition Law and Policy 1297, 1300 (2008).
Department of Justice and Federal Trade Commission, Antitrust Policy Statement on Sharing of Cybersecurity Information (2014) 6.
U.S.C. § 1503(e).
Law Reform Institute, Antitrust Exemption for AI Frontier Model Risks (Draft at 30 May 2025).
Cynthia Hanwalt and Denise Hearn, Recommendations to Update the FTC & DOJ’s Guidelines for Collaborations Among Competitors (2024) 25–26. DOI: https://doi.org/10.2139/ssrn.4850509
Department of Justice and Federal Trade Commission, Antitrust Policy Statement on Sharing of Cybersecurity Information (2014).
Cass R. Sunstein, On the Expressive Function of Law, U. Penn. L.R. (1996). DOI: https://doi.org/10.2307/3312647
C.F.R. § 50.6. See also Department of Justice, Introduction to Antitrust Division Business Reviews (2011).
Department of Justice, What Is a Business Review?, https://www.justice.gov/atr/what-business-review.
Department of Justice, Introduction to Antitrust Division Business Reviews, https://www.justice.gov/sites/default/files/atr/legacy/2011/11/03/276833.pdf.
United States v. Grinnell Corporation, 30 F.R.D. 358, 363
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