Assessing Privacy Policies with AI: Ethical, Legal, and Technical Challenges

Privacy policies are too complex for most people to understand: The paper identifies that privacy policies are often lengthy and difficult to comprehend, leading to "consent fatigue" where users accept data practices they don't actually understand or agree with—a significant problem in today's data-driven economy.

AI tools could help users understand their privacy rights, but face major obstacles: While Large Language Models like GPT could potentially summarize and assess privacy policies to help users make informed decisions, the paper identifies substantial technical, ethical, and legal challenges that must be resolved before this approach can be reliably deployed.

Using AI to assess privacy policies raises ethical concerns: The paper highlights that employing LLMs for this purpose creates new ethical dilemmas, including questions about who controls these assessment tools and whether they might introduce their own biases or limitations into privacy evaluations.

Legal compatibility remains unclear: The research explores whether using AI systems to interpret privacy policies aligns with existing privacy laws and regulations, suggesting that current legal frameworks may not adequately address this emerging use case.

This is an interdisciplinary challenge requiring collaboration: The paper emphasizes that solving privacy assessment problems requires expertise across technical, legal, and ethical domains—no single perspective alone can address the full complexity of the issue.