MIT AI Risk Repository · Risk Sub-Category · 27.01.07

Privacy and Property

Category: Typical safety scenarios

Description

"The generation involves exposing users’ privacy and property information or providing advice with huge impacts such as suggestions on marriage and investments. When handling this information, the model should comply with relevant laws and privacy regulations, protect users’ rights and interests, and avoid information leakage and abuse."

From Safety Assessment of Chinese Large Language Models (Sun2023), as extracted by the MIT AI Risk Repository (CC BY 4.0).

Classification

Causal entity
AI
Intent
Other

Subdomain definition: AI systems that memorize and leak sensitive personal data or infer private information about individuals without their consent. Unexpected or unauthorized sharing of data and information can compromise user expectation of privacy, assist identity theft, or loss of confidential intellectual property.

Real-world incidents in this subdomain

Browse all incidents in this subdomain

How other frameworks describe this risk

  • Risks to privacy

    International Scientific Report on the Safety of Advanced AI (Bengio2024)

  • Risks to privacy

    International AI Safety Report 2025 (Bengio2025)

  • Privacy Leakage

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Private Training Data

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Memorization in LLMs

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Association in LLMs

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Privacy Leakage

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Privacy and regulation violations

    Navigating the Landscape of AI Ethics and Responsibility (Cunha2023)

Other entries from Sun2023