DATDAT-001 — Data Quality and Completeness Issues
AI Safety Benchmark Exposes Self-Harm Enablement Risk in Generative Models
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
MLCommons benchmarking identified that AI systems can produce responses that enable or endorse intentional self-harm. Organisations deploying generative AI face regulatory and reputational liability if safety evaluations are absent from procurement and governance processes.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Introducing v0.5 of the AI Safety Benchmark from MLCommons (Vidgen2024) ↗https://airisk.mit.edu/
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