DATDAT-003 — Data Bias and Fairness Oversights
Language Models Encode and Reproduce Harmful Social Stereotypes at Scale
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models trained on internet and book data systematically absorb and reproduce demeaning stereotypes, compounding historical injustice across intersecting marginalised groups. Opaque models obstruct victim recourse, exposing deploying organisations to discrimination liability and reputational harm.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Taxonomy of Risks posed by Language Models (Weidinger2022) ↗https://airisk.mit.edu/
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