A Measurement Study of Contextual Leakage in AI Chat Platforms
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Ranked by a public rubric, not by votes: what a comment adds counts, not who wrote it. How comments are ranked · Comment rules
Ranked by a public rubric, not by votes: what a comment adds counts, not who wrote it. How comments are ranked · Comment rules
Summary
Researchers at Stony Brook audited the web interfaces of 42 AI chatbots, 25 general-purpose and 17 in health, legal and education, and found that 21 send conversation titles to third-party trackers and nine send verbatim prompts. In the general-purpose group, 11 of 13 leaking platforms also send the user's email, linking content to identity. Trackers read auto-generated page titles as ordinary metadata. Testing used fresh accounts, two prompts, one US vantage point and web interfaces only. Builders embedding analytics scripts in chat UIs should audit what those scripts can read.