The Privacy Guardian Agent: Towards Trustworthy AI Privacy Agents
For users overwhelmed by privacy consent dialogues, this work offers a balanced automation approach that preserves human oversight when needed.
The paper proposes a Privacy Guardian Agent that automates routine consent decisions while escalating uncertain or high-risk cases to the user, aiming to reduce consent fatigue and maintain trust.
The current "notice and consent" paradigm is broken: consent dialogues are often manipulative, and users cannot realistically read or understand every privacy policy. While recent LLM-based tools empower users seeking active control, many with limited time or motivation prefer full automation. However, fully autonomous solutions risk hallucinations and opaque decisions, undermining trust. I propose a middle ground - a Privacy Guardian Agent that automates routine consent choices using user profiles and contextual awareness while recognizing uncertainty. It escalates unclear or high-risk cases to the user, maintaining a human-in-the-loop only when necessary. To ensure agency and transparency, the agent's reasoning on its autonomous decisions is reviewable, allowing for user recourse. For problematic cases, even with minimal consent, it alerts the user and suggests switching to an alternative site. This approach aims to reduce consent fatigue while preserving trust and meaningful user autonomy.