DATDAT-003 — Data Bias and Fairness Oversights
Algorithmic Pricing and Demonetisation Systems Cause Disproportionate Economic Harm
4/5Sector: EducationGeography: GlobalStage: OperateIngested: —
Executive Summary
Demonetisation, differential pricing, and generative AI systems systematically disadvantage lower-income, minority, and creative-sector users by encoding existing socioeconomic inequalities into automated decisions. Boards face reputational and regulatory exposure where deployed tools amplify economic harm across protected characteristics.
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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