DATDAT-003 — Data Bias and Fairness Oversights
Algorithmic Systems Deliver Degraded Service to Minority User Groups
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
AI systems consistently underperform for users defined by disability, ethnicity, gender identity, and race, producing unequal service outcomes at scale. Boards face regulatory exposure and reputational liability where disparate quality of service remains undetected or unaddressed.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Shelby2023) ↗https://airisk.mit.edu/
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