The privacy policies of the 20 most popular large language models average 4,603 words and would take the typical reader 19 minutes 44 seconds to get through, with readability scores placing most of them at university-graduate difficulty, according to analysis by cybersecurity firm Bridewell.
Meta's Muse Spark has the longest policy: 14,000 words, taking the average reader close to an hour. Kimi K from Moonshot AI is the hardest to parse, scoring 28.1 on the Flesch Reading Ease scale. A score above 60 is considered suitable for the general public; the average across the 20 policies in the study is 40.2. ChatGPT, the UK's most popular LLM, takes 17 minutes to read and sits broadly in the middle of the pack.
Command by Cohere takes 27 minutes on average, with a Flesch score of 37.6. Thirteen of the 20 platforms in the study train their models on user inputs, a detail that many users are unlikely to have registered.
The timing matters. A government survey published earlier this year found that nearly three-quarters of the UK population use AI tools at least once a month, often for tasks involving sensitive personal, financial or medical information. Separately, 77 percent of employees admitted to pasting company information into AI tools, and 82 percent of those used a personal account to do it.
“The reliance on AI tools is increasing rapidly, yet many users fail to understand how their data is being used and processed — often due to the complexity and length of privacy policies,” said Chris Linnell, Associate Director of Data Privacy at Bridewell. “While these policies are a legal requirement, they need to be more accessible if we want people to make informed choices about which AI tools they use and how.”
Bridewell's analysis scored policies on length, average reading time, Flesch Reading Ease and prevalence of technical and legal jargon. The full breakdown is available at bridewell.com.
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