Thanks to these summits, states established AI Safety Institutes or similar institutions to advance testing, research and standards setting.

Models whose capabilities fall below early warning thresholds require only limited testing and evaluation, while more rigorous assurance mechanisms are needed for advanced AI systems exceeding these early warning thresholds.

Although testing can alert us to risks, it only gives us a coarse grained understanding of a model.

Pre deployment testing, evaluation and assurance are not sufficient.

States should mandate that developers conduct regular testing for concerning capabilities, with transparency provided through independent pre deployment audits by third parties granted sufficient access to developers’ staff, systems and records necessary to verify the developer’s claims.

To ensure global trust, it will be important to have international collaborations developing and stress testing verification methods.