Table 1 Key risk categories and recommended safeguards for AI scribe implementation
From: Beyond human ears: navigating the uncharted risks of AI scribes in clinical practice
Risk Category | Examples of Potential Harm | Recommended Safeguards |
|---|---|---|
Clinical Accuracy | AI Hallucinations (fabricated exams), Omissions of symptoms | Mandatory accuracy standards, Independent validation studies |
Patient Privacy | Unauthorized recording, Data repurposing for AI training | Explicit consent protocols, Audit trails for data access |
Legal Liability | Unclear responsibility for AI errors, Documentation discrepancies | Updated liability frameworks, Clear error attribution processes |
Transparency | “Black box” algorithms, Proprietary systems | Required explainability standards, Open audit of error rates |
Interprofessional Communication | Inconsistent documentation across care team, Widened information gaps | Team-based implementation protocols, Shared responsibility models |
