DATDAT-002 — Data Privacy and Protection Failures
Generative AI Systems Infer and Disclose Personal Data Beyond Raw Inputs
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
AI models create disclosure risks by inferring sensitive personal information not present in source data and by exposing individual data through model training pipelines. Boards face compounded regulatory and reputational liability where existing data governance frameworks do not account for AI-driven inference.
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.