DATDAT-003 — Data Bias and Fairness Oversights
Training Process Amplifies Dataset Bias Beyond Source Data Levels
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
AI models can produce outputs more biased than their training data, meaning bias controls applied only at the data ingestion stage are insufficient. Organisations relying solely on dataset audits will have undetected liability exposure in deployed systems.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024) ↗https://airisk.mit.edu/
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