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METR · October 14, 2026

AI risk assessment: match each question to evidence and access

analysis Model EvaluationAgent SecurityAI Compliance
Why it matters

METR proposes assessing alignment, control of internal agents, and acceleration of AI research separately. Each question needs different evidence: training behavior, monitoring systems and logs, or research outcomes and resources. The proposal makes access gaps central to interpretation. Voluntary cooperation and limited visibility mean an assessment cannot certify safety or substitute for a full security audit.

My takeaway: Build an assessment matrix linking each risk question to evidence, an owner, and required access. Record unavailable logs, checkpoints, interviews, and research outcomes alongside the conclusions they limit. Evaluate research acceleration using validated outcomes and resource use, rather than code or pull-request volume alone.
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