DATDAT-001 — Data Quality and Completeness Issues
LLM Adult Content Generation Identified in Catalogued Evaluations
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Benchmarking evaluations confirm that large language models can be prompted to produce sexual and explicit material without adequate restriction. Boards must ensure deployment contracts mandate content filtering controls and establish liability frameworks for harmful outputs.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Cataloguing LLM Evaluations (InfoComm2023) ↗https://airisk.mit.edu/
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