DATDAT-003 — Data Bias and Fairness Oversights
General Purpose AI Reproduces Discriminatory Stereotypes at Scale
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Opaque training mechanisms embed biases into general purpose AI, producing discriminatory outputs that propagate across multiple downstream applications simultaneously. Boards face amplified legal and reputational exposure as mitigation techniques remain unreliable and impact exceeds that of any single human decision-maker.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Governing General Purpose AI: A Comprehensive Map of Unreliability, Misuse and Systemic Risks (Maham2023) ↗https://airisk.mit.edu/
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