DATDAT-003 — Data Bias and Fairness Oversights
Generative AI Systems Deliver Lower Quality Outputs for Non-English Language Users
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Generative AI systems consistently underperform for non-English speakers, producing inferior outputs that disadvantage already marginalised user groups. Organisations deploying such systems face equity obligations, reputational risk, and potential regulatory scrutiny under fairness and non-discrimination frameworks.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Sociotechnical Safety Evaluation of Generative AI Systems (Weidinger2023) ↗https://airisk.mit.edu/
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