DATDAT-002 — Data Privacy and Protection Failures
AI Training Data Misuse Exposes Sensitive Personal Information
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
AI systems require large datasets to function, creating systemic risk of sensitive data mishandled during training or deployment. Boards face regulatory exposure and reputational liability where data governance frameworks fail to govern AI data pipelines adequately.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Artificial Intelligence Trust, Risk and Security Management (AI TRiSM): Frameworks, Applications, Challenges and Future Research Directions (Habbal2024) ↗https://airisk.mit.edu/
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