DATDAT-003 — Data Bias and Fairness Oversights
LLM Performance Gaps Across Racial, Language and Social Groups
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models exhibit measurable performance disparities across racial, linguistic, and socioeconomic groups due to training data imbalance and cultural blind spots. Organisations deploying these systems face regulatory exposure and reputational risk if equitable outcomes are not validated before and during deployment.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment (Liu2024) ↗https://airisk.mit.edu/
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