Enabling Frontier Lab Collaboration to Mitigate AI Safety Risks
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 9 Nov 2025.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2026: 1.
1 paper.
- 2026The Normalization of Deviance in AI Developmentcited by 0
- 2026The Normalization of Deviance in AI Development4 Sep 2026