Smart Privacy Policy Assistant: An LLM-Powered System for Transparent and Actionable Privacy Notices
Sriharshini Kalvakuntla, Luoxi Tang, Yuqiao Meng, Zhaohan Xi

TL;DR
This paper introduces the Smart Privacy Policy Assistant, an LLM-powered system that automatically interprets privacy policies, categorizes clauses, assesses risks, and provides clear explanations to help users understand and manage their privacy choices.
Contribution
It presents a novel end-to-end system that automates privacy policy analysis and risk explanation, enhancing user comprehension and decision-making.
Findings
High accuracy in clause categorization
Effective risk level assignment
Improved user understanding of privacy policies
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsPrivacy, Security, and Data Protection · Access Control and Trust · Explainable Artificial Intelligence (XAI)
