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DATDAT-001 — Data Quality and Completeness Issues

LLMs Express Extremist Views and Political Bias in Government Contexts

4/5Sector: GovernmentGeography: GlobalStage: OperateIngested: —

Executive Summary

Large language models deployed in government settings have demonstrated extremist outputs and measurable left-leaning political bias across policy domains despite neutrality claims. Departments relying on these tools risk undermining public trust and regulatory compliance where impartiality is a statutory requirement.

Domain

Data Management

Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.

Source

MIT AI Risk Repository — Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements (Deng2023) ↗

https://airisk.mit.edu/

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