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DATDAT-003 — Data Bias and Fairness Oversights

Language models encoding social stereotypes and discriminatory bias

4/5Sector: OtherGeography: GlobalStage: OperateIngested: —

Executive Summary

Language models trained on historical data systematically learn and reproduce social stereotypes, producing discriminatory outputs across protected characteristics including sex, religion and age. Organisations deploying such models risk regulatory liability, reputational harm and reinforcement of the very inequalities their policies seek to address.

Domain

Data Management

Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.

Source

MIT AI Risk Repository — Ethical and social risks of harm from language models (Weidinger2021) ↗

https://airisk.mit.edu/

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