This research identifies critical interpretation gaps when large language models translate complex privacy policies into simplified explanations for users.

• Accuracy issues: LLMs may misrepresent data collection practices
• Completeness problems: Important details often get omitted in simplified versions
• Clarity challenges: Simplified explanations can introduce new ambiguities
• Representation concerns: LLMs may present biased interpretations of policies

For legal and compliance teams, this research highlights the need for human oversight when deploying LLMs for privacy document interpretation, while pointing toward future research needed to unlock AI's potential in privacy management.

Interpretation Gaps in LLM-Assisted Comprehension of Privacy Documents