DATDAT-003 — Data Bias and Fairness Oversights
Biased Training Corpora Cause LLMs to Reproduce Demographic Stereotypes
4/5Sector: OtherGeography: GlobalStage: DevelopIngested: —
Executive Summary
Large language models trained on imbalanced corpora systematically under-represent certain demographic groups and encode stereotypical beliefs as default outputs. Organisations deploying such models face regulatory exposure and reputational harm if biased outputs affect hiring, lending, or public-facing services.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024) ↗https://airisk.mit.edu/
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