Enabling Frontier Lab Collaboration to Mitigate AI Safety Risks

TL;DR

This paper discusses how U.S. antitrust policy can adapt to promote safe collaboration among AI labs, balancing safety risks with competition laws to prevent a dangerous AI development race.

Contribution

It analyzes antitrust concerns related to AI safety cooperation and proposes legislative reforms to facilitate responsible lab collaboration.

Findings

Coordination among AI labs can reduce safety risks.

Legal reforms can enable safe AI safety collaborations.

Antitrust concerns can be addressed through policy adjustments.

Abstract

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.