Smart Privacy Policy Assistant: An LLM-Powered System for Transparent and Actionable Privacy Notices
This addresses the issue of opaque privacy policies for general internet users, though it is incremental as it applies existing LLM methods to a new domain.
The paper tackles the problem of users not reading or understanding complex online privacy policies by developing the Smart Privacy Policy Assistant, an LLM-powered system that automatically extracts and categorizes key clauses, assigns risk levels, and generates clear explanations, with evaluation based on clause-level accuracy, risk agreement, and user comprehension.
Most users agree to online privacy policies without reading or understanding them, even though these documents govern how personal data is collected, shared, and monetized. Privacy policies are typically long, legally complex, and difficult for non-experts to interpret. This paper presents the Smart Privacy Policy Assistant, an LLM-powered system that automatically ingests privacy policies, extracts and categorizes key clauses, assigns human-interpretable risk levels, and generates clear, concise explanations. The system is designed for real-time use through browser extensions or mobile interfaces, surfacing contextual warnings before users disclose sensitive information or grant risky permissions. We describe the end-to-end pipeline, including policy ingestion, clause categorization, risk scoring, and explanation generation, and propose an evaluation framework based on clause-level accuracy, policy-level risk agreement, and user comprehension.