DATDAT-003 — Data Bias and Fairness Oversights
Biased Training Data Produces Discriminatory AI Decisions
4/5Sector: OtherGeography: GlobalStage: DevelopIngested: —
Executive Summary
AI models trained on historically biased data systematically reproduce discriminatory outcomes against protected groups. Organisations face legal liability and reputational harm unless fairness is addressed at the data collection and preprocessing stage.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — A Survey of Artificial Intelligence Challenges: Analyzing the Definitions, Relationships, and Evolutions (Saghiri2022) ↗https://airisk.mit.edu/
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