What practical steps must the global community take to move away from competitive AI development toward shared safety standards?

Moving away from a zero-sum mindset requires changing the underlying incentives that currently reward speed over caution. Right now, companies and nations feel pressured to cut corners to avoid falling behind. We break this cycle by building institutional guardrails that make safety a prerequisite for market entry rather than a competitive disadvantage.

First, we need international technical standards that function like aviation safety protocols. When every airline follows the same rigorous maintenance rules, flying becomes safer for everyone. Similarly, creating open-source benchmarks for evaluating model risks allows labs to prove their systems are stable without surrendering proprietary code. This turns safety into a shared technical baseline rather than a trade secret.

Second, governments must decouple safety research from military competition. This involves funding independent, international bodies to conduct audits and stress tests on frontier models. Such agencies should operate under a multilateral framework, much like how the IAEA monitors nuclear energy. By treating high-level AI safety as a global utility, we ensure that a failure in one country doesn't trigger a catastrophe in another. Cooperation becomes the logical choice when the cost of a mistake outweighs the profit of a fast launch.