DATDAT-003 — Data Bias and Fairness Oversights
AI Systems Trained on Biased Historical Data Perpetuate Discrimination in High-Stakes Decisions
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
AI systems trained on historical data inherit and reproduce existing prejudices, producing discriminatory outcomes in employment, lending, and law enforcement. Boards face mounting legal and reputational exposure where algorithmic decisions exacerbate socioeconomic inequality across protected groups.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Ethical Issues in the Development of Artificial Intelligence: Recognizing the Risks (Kumar2023) ↗https://airisk.mit.edu/
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