The US and USSR, despite being adversaries, collaborated to prevent nuclear proliferation to rogue actors. A similar model can be applied to AI. The US and China share an interest in preventing powerful open-weight models from being used for cyber-attacks or bio-terrorism by third parties, creating a foundation for a safety dialogue.

To prevent a reckless race, a proposed solution is a U.S.-China treaty to govern the resources needed for frontier AI. This would involve tracking and monitoring advanced AI chips in data centers and imposing a verifiable cap on the computational power used for any single training run.

The same governments pushing AI competition for a strategic edge may be forced into cooperation. As AI democratizes access to catastrophic weapons (CBRN), the national security risk will become so great that even rival superpowers will have a mutual incentive to create verifiable safety treaties.

A pragmatic starting point for U.S.-China AI cooperation is to agree on verifiable red lines for proliferating dangerous dual-use capabilities, such as advanced cyberattack tools. This addresses a mutual security interest and builds the institutional trust and processes needed for more ambitious agreements on superintelligence.

International AI treaties, particularly with nations like China, are unlikely to hold based on trust alone. A stable agreement requires a mutually-assured-destruction-style dynamic, meaning the U.S. must develop and signal credible offensive capabilities to deter cheating.

Claims that AI treaties are unverifiable lack imagination. During the Cold War, the US and USSR agreed to saw bombers in half on runways, allowing spy planes to visually confirm disarmament. Similar 'outside-the-box' physical verification methods, like publicly escrowing or destroying GPUs, could work for AI.

To accelerate enterprise AI adoption, vendors should achieve verifiable certifications like ISO 42001 (AI risk management). These standards provide a common language for procurement and security, reducing sales cycles by replacing abstract trust claims with concrete, auditable proof.

Davidad argues the old AI safety plan of containing AI like uranium is no longer viable due to geopolitical realities. The new strategy is to build tools for a coalition of aligned AIs that can prove things to each other and collectively defend against rogue AIs, embracing a world of rapid, competitive AI development.

International AI treaties are feasible. Just as nuclear arms control monitors uranium and plutonium, AI governance can monitor the choke point for advanced AI: high-end compute chips from companies like NVIDIA. Tracking the global distribution of these chips could verify compliance with development limits.