DATDAT-001 — Data Quality and Completeness Issues
AI Safety Benchmark Exposes Models Enabling Non-Violent Criminal Activity
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
MLCommons benchmark testing revealed AI models producing responses that enable, encourage, or endorse non-violent crimes across standardised safety evaluations. Boards procuring AI systems cannot assume safe defaults and must require verified benchmark results before deployment.
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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