A new study published on arXiv demonstrates how agentic AI, specifically large language models, can automate the re-identification of individuals from mobility microdata. The research presents a pipeline where AI agents autonomously search public web sources, cross-reference data, and link location traces to identities with minimal human intervention. This approach successfully re-identified 72% of identifiable individuals in a real-world feasibility study, highlighting a significant shift in privacy risks and challenging existing Statistical Disclosure Control practices. AI
IMPACT Agentic AI significantly lowers the cost and increases the scale of re-identifying individuals from location data, challenging current privacy protections.
RANK_REASON Research paper published on arXiv detailing a new method.
- agentic AI
- arXiv
- GDPR Recital-26
- General Data Protection Regulation
- large language model agents
- mobility microdata
- alphaXiv
- CatalyzeX
- DagsHub
- Gotit.pub
- Hugging Face
- large language model
- ScienceCast
- Statistical Disclosure Control
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