MIT AI Risk Repository · Risk Sub-Category · 02.07.03
Association in LLMs
Category: Privacy Leakage
Description
"Association in LLMs refers to the capability to associate various pieces of information related to a person. According to [68], [86], given a pair of PII entities (xi , xj ), which is associated by a model F. Using a prompt p could force the model F to produce the entity xj , where p is the prompt related to the entity xi . For instance, an LLM could accurately output the answer when given the prompt “The email address of Alice is”, if the LLM associates Alice with her email “alice@email.com”. L"
From Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Domain
- 2. Privacy & Security
- Subdomain
- 2.1 Compromise of privacy by obtaining, leaking or correctly inferring sensitive information
- Causal entity
- AI
- Intent
- Unintentional
- Timing
- Pre-deployment
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
- Meta AI Smart Glasses Reportedly Routed Intimate Imagery to Reviewers at Kenyan Contractor Sama Before Meta Ended Contract
- Grok Reportedly Disclosed Adult Performer Siri Dahl's Legal Name and Birthdate, Allegedly Contributing to Doxxing and Harassment
- NPR Host David Greene Alleged Google's NotebookLM Replicated His Voice Without Consent, Prompting Lawsuit
- Border Patrol Agent Allegedly Claimed Facial Recognition Identified Minneapolis ICE Observer and Global Entry Was Reportedly Revoked Three Days Later
- Perplexity AI Reportedly Accused in Federal Lawsuit of Purported Copyright Infringement and False Attribution of Chicago Tribune Content
- Secret Desires AI Platform Reportedly Exposed Nearly Two Million Sensitive Images in Cloud Storage Leak