DATDAT-003 — Data Bias and Fairness Oversights
Generative AI Systems Deliver Inferior Performance for Marginalised User Groups
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Generative AI models systematically underperform for certain demographic groups, causing measurable harm to those already disadvantaged. Boards face legal exposure under equality legislation and reputational risk if disparate capability is not audited and remediated before deployment.
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/
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