Enhancing AI Privacy with Contextual Integrity: Two Innovative Approaches
Understanding Privacy Challenges in AI Systems Artificial intelligence systems are increasingly present in daily life, handling vast amounts of personal data. This raises concerns about privacy, especially when AI unintentionally reveals sensitive information. Maintaining privacy is essential to protect individuals’ rights and foster trust in AI technologies. The Concept of Contextual Integrity in Privacy Contextual integrity is a privacy framework that focuses on appropriate information flow based on social norms within specific contexts. It suggests that privacy is preserved when data sharing aligns with expected purposes and relationships. Applying this concept to AI means ensuring that AI agents respect context-specific privacy rules when processing and sharing data. First Approach: Lightweight Inference-Time Privacy Checks The first method to enhance privacy in AI involves adding lightweight checks during the AI’s inference phase. These checks monitor the AI’s outputs i...