Frontier Risk Report (February to March 2026)
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Informe de riesgos de la IA de frontera (febrero–marzo de 2026)
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前沿 AI 风险报告（2026 年 2–3 月）
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Measuring the Self-Reported Impact of Early-2026 AI on Technical Worker Productivity
Summary In February–April 2026, we ran a survey of 349 technical workers (including 87 software engineers, 71 researchers, 129 academics and PhD students, and 48 founders…
Review of the "Risks from automated R&D" section in the Anthropic Risk Report (February 2026)
We reviewed the “Risks from automated R&D” section of Anthropic’s February 2026 Risk Report, producing two corresponding review documents: our original review and our updated review.…
Task Substitution and Uplift
Summary: We describe three different definitions of the productivity impact of AI (AKA uplift), and show there’s reason to expect: [text{uplift on old tasks} leq text{uplift…
Evidence on AI R&D Progress from NanoGPT
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MirrorCode: Evidence that AI can already do some weeks-long coding tasks
This is a linkpost for MirrorCode, a project that METR funded and co-developed with Epoch AI. See Epoch AI’s blog post for more detail: https://epoch.ai/publications/mirrorcode-preliminary-results/
Fine-tuning experiments on CoT controllability
p:has(> img) { margin-bottom: 0; } .content img { margin: 0.75em 0; } Kei Nishimura-Gasparian is an Astra fellow and was the primary contributor to this…
Red-Teaming Anthropic's Internal Agent Monitoring Systems
Update: Further details on this exercise are included in our Frontier Risk Report (February-March 2026), within the Anthropic section of Appendix B. In collaboration with Anthropic,…