DATDAT-001 — Data Quality and Completeness Issues
Healthcare AI Generates Inappropriate Sexual Content Instead of Clinical Responses
4/5Sector: HealthcareGeography: GlobalStage: OperateIngested: —
Executive Summary
AI systems in healthcare settings risk producing pornographic or erotically engaging outputs rather than maintaining the clinical neutrality required for medical contexts. Failure to enforce content boundaries exposes organisations to regulatory censure, patient harm, and reputational damage.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — AILUMINATE: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons (Ghosh2024) ↗https://airisk.mit.edu/
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