A recent study has revealed a concerning trend regarding the privacy policies of popular Large Language Models (LLMs): they are becoming increasingly lengthy, dense, and difficult for the average user to understand. This complexity poses a significant barrier to informed consent, as users struggle to grasp how their personal data is collected, used, and shared by AI providers.

The Challenge of Policy Complexity

The study found that the average LLM privacy policy can be comparable in length to a novel, making it impractical for most users to read and fully comprehend. These policies frequently contain complex legal jargon and technical terms, further obscuring crucial details about data handling practices. This lack of clarity prevents users from making informed decisions about their privacy when interacting with LLMs.

Implications for User Consent and Transparency

The growing inscrutability of LLM privacy policies undermines the principle of transparency and user control over personal data. When policies are nearly impossible to decode, users cannot effectively understand the terms they are agreeing to, potentially leading to unintended data sharing or usage. The study highlights an urgent need for LLM providers to develop more accessible and user-friendly privacy policies to ensure true informed consent and foster greater trust.

Source: https://www.helpnetsecurity.com/2025/12/12/llms-privacy-policies-study/