DATDAT-002 — Data Privacy and Protection Failures
LLMs Inferring Private Characteristics from User Inputs
4/5Sector: OtherGeography: GlobalStage: OperateIngested: —
Executive Summary
Large language models can deduce sensitive personal attributes such as race and gender directly from prompt data, without those details being explicitly provided. Organisations deploying AI assistants face material privacy liability and regulatory exposure under data protection law.
Domain
Data Management
Blindspots in data quality, privacy, bias, lineage, lifecycle, and third-party data dependencies.
Source
MIT AI Risk Repository — The Ethics of Advanced AI Assistants (Gabriel2024) ↗https://airisk.mit.edu/
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