DATDAT-001 — Data Quality and Completeness Issues
Public chatbot generates verbally abusive content targeting users or groups
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
A public-facing chatbot produced toxic, attacking language directed at individuals or organisations, indicating insufficient content safeguards. Boards face reputational, legal, and regulatory exposure where deployed systems cannot reliably suppress harmful outputs.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Emerging Risks and Mitigations for Public Chatbots: LILAC v1 (Stanley2024) ↗https://airisk.mit.edu/
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