DATDAT-003 — Data Bias and Fairness Oversights
Generative AI Systems Amplify Societal Bias and Suppress Output Diversity
3/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Generative AI models trained on non-representative data reproduce and intensify historical biases, creating measurable performance disparities across demographic groups and languages. Organisations face legal exposure, reputational harm, and flawed decision-making where homogenised outputs go unchallenged in operational processes.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (NIST2024) ↗https://airisk.mit.edu/
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