Priorities and principles for effective third party assessments

Frontier AI labs are proposing priorities and principles for how independent third parties should assess whether AI safety claims and safeguards are effective. Third party assessments matter because they provide external scrutiny of safety practices, help identify missed risks, and keep labs accountable to their safety claims. Labs propose four priority areas for assessment: evaluating overall safety cases across training and deployment, testing critical safeguards for vulnerabilities, assessing capability evaluations for high-risk domains, and examining alignment evaluations. The work requires balancing meaningful independent oversight with protection of sensitive information, and labs argue that both parties should operate under shared international safety and security standards.