The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing

Short summary

Researchers surveyed 136 U.S. prescribing clinicians on autonomous AI medication systems, finding they require calibrated confidence thresholds, differentiated uncertainty types, and decision transparency. Current regulatory guidelines lack these safeguards. The study proposes these as minimum requirements—positioning 'autonomous' AI as heavily supervised decision-support tools with clear liability allocation.

• •Survey of 136 U.S. clinicians shows AI prescribing adoption requires confidence-based escalation, uncertainty differentiation, and inferential transparency
• •Current regulatory frameworks (H.R. 238, Utah pilot) do not mandate these architectural requirements
• •Meeting these requirements limits true autonomy, functioning as supervised decision-support rather than autonomous agents

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