AI tools are now embedded throughout healthcare: they transcribe doctor notes, flag at-risk patients, and interpret X-rays and lab results. The adoption curve has been steep. The evidence curve, much less so. A deep investigation by MIT Technology Review reveals a troubling gap โ most AI health products deployed in clinical settings have never been rigorously tested for patient outcomes. We know these tools change clinician behavior. We don't know if that change is good. In a field where 'first, do no harm' is foundational, rolling out unvalidated AI at scale is a bold โ some would say reckless โ experiment. Who's responsible when AI gets a diagnosis wrong?
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