Auditing What Was Said: The Epistemic Promise and Limits of Ambient AI in Clinical Practice
Misrai, V.; Bruchon, A.; Campan, A.; Loubes, J. M.; Piau, A.
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Traditional audit methods that rely on written records often miss the nuances of clinical reasoning that influence patient care. Ambient artificial intelligence captures spoken clinical encounters, allowing the analysis of real clinician-patient dialogue at scale. In a study of 124 urology consultations, a transcript-centered audit identified inter-physician variation and expert disagreement that conventional review missed. We explore the epistemic gains of this approach, its nonverbal blind spots, behavioral effects, technical vulnerabilities, and the EU AI Acts regulatory landscape.
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