DATDAT-001 — Data Quality and Completeness Issues
Benign User Exposure to NSFW Content via Unsafe Prompt Handling
3/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models fail to reliably filter or refuse prompts containing not-suitable-for-work content, exposing ordinary users to harmful material. Organisations deploying LLMs face reputational, legal, and safeguarding liability where content moderation controls are insufficient.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024) ↗https://airisk.mit.edu/
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