DATDAT-002 — Data Privacy and Protection Failures
General-Purpose AI Models Leak Personal Data and Enable Privacy Abuse
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
AI models trained on sensitive data can expose personal health and financial information through leakage or inference attacks. Boards face material regulatory and reputational liability as these capabilities scale across enterprise deployments.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — International Scientific Report on the Safety of Advanced AI (Bengio2024) ↗https://airisk.mit.edu/
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