DATDAT-001 — Data Quality and Completeness Issues
Generative AI Systems Producing Harmful and Prohibited Content
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Generative AI models have produced content violating community standards, including child sexual abuse material, incitement to violence, and identity-based attacks. Boards face acute legal liability and reputational exposure where deployed systems lack robust content controls and human oversight.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents (Li2025) ↗https://airisk.mit.edu/
Could this happen in your organisation?
A Velinor AI Audit maps your active AI portfolio against the 50+ blindspots and benchmarks against documented sector failures like this one. A board-ready foresight document in 5 weeks.