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This article outlines METR's methodology for independently evaluating large-scale loss-of-control risks in AI agents and publishing transparent evidence to inform public and policy decisions. It emphasizes an open scientific approach to risk assessment rather than dictating specific development or deployment strategies for companies.
Sources coveringMETR, LessWrong, Fortune, Analytics Vidhya
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

Our approach to working with AI companies

METR12 min read

This blog post explains how we approach working with AI companies on projects that the public might rely on to understand risks. It was published on Oct 14, 2026, and we expect to update it over time. At METR, we gather and publish evidence about whether humans could lose control of AI agents on a large scale. We work with AI companies to conduct evaluations, assessments, and investigations,1 and to share this evidence publicly. As we have seen increasing expectations for these kinds of voluntary engagements to provide external ‘safety assurance’, we want to explain our perspective. In this post, we clarify our overall goals for this work, our approach, and what our approach looks like in practice. Our goal is to give the public accurate, timely, and independent evidence about AI loss-of-control risk, so that they (along with policymakers and developers) can make their own informed decisions. Our primary approach is collecting high-quality, concrete evidence and publishing what we find. Beyond this, we may also work with companies or regulators to share our comments on unpublished sensitive information,2 to review risk reports, or to provide an independent judgment on claims about risk. However, many of the relevant claims involve…

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