Priorities and principles for effective third party assessments

OpenAI published (Sept 22, 2026) a position paper proposing how frontier-lab third-party safety assessments should work, defining 'safety claim' and 'safety case' and setting out four priority areas for deeper assessment — independent assessment of safety cases spanning training, evaluation and deployment, and principles covering independence, scientific rigor and security. The paper argues 'Making these assessments effective requires strong independence mechanisms, scientific rigor, robust security practices, and clear responsibilities,' and commits OpenAI to 'supporting independent assessments with deep levels of access across training, evaluation, and deployment,' including visible chain-of-thought access and internal incident-response red-teaming. It positions the work as complementing government testing-and-evaluation roles and aligning with shared international safety-and-security standards.

Sets the emerging norm for how frontier labs will open themselves to external scrutiny — directly relevant to any evaluation, assurance or oversight program an enterprise, regulator or investor builds around frontier model deployments.

Map the four proposed assessment priority areas against any third-party or government evaluation commitments in your AI assurance pipeline and reflect them in procurement RFPs.