METR

Do public capability evaluations track deployment-relevant risk under adversarial pressure and Goodhart Selection?

Introduction

METR measures dangerous autonomous and AI R&D capabilities at the frontier, producing eval-driven forecasting and risk reporting to inform policy and lab decisions.

Who carries it: Model Evaluation & Threat Research

What they aim to do. Measure dangerous capabilities to inform policy and lab decisions before systems reach deployment-relevant autonomy.

The hard question. Do public capability evaluations track deployment-relevant risk under adversarial pressure and Goodhart Selection?

What they produce. Autonomy evaluations, AI R&D evaluations, and frontier risk reporting including red-teaming of lab monitoring systems.

Key terms. Key terms include autonomous capabilities, AI R&D evals, eval-driven forecasting, and entity-based assessment.

Related field cruxes. Goodhart Selection; Inner Alignment

What they contribute. Empirical capability measurement at the frontier, including autonomy and AI R&D evaluations that shape lab and policy timelines.

How this project treats it. Capability evaluations do not establish correction-channel integrity  or value-bundle transport  across deployment; this project treats evals as an indirect signal for Inner Alignment rather than a direct guarantee.

Map clustering

AISafety.com map listings that roll up to this agenda:

See the coverage matrix for evidence tagged to this agenda, and the glossary for shared terms.