DATDAT-003 — Data Bias and Fairness Oversights
Language Model Performance Gaps Across Languages and Dialects
4/5Sector: TechnologyGeography: GlobalStage: OperateIngested: —
Executive Summary
Language models systematically underperform for speakers of under-resourced languages and marginalised dialects due to structural gaps in training data. Organisations deploying these systems risk discriminatory outcomes and regulatory exposure when serving linguistically diverse populations.
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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