Health AI and sensitive data
Studies of how people understand advice from consumer health AI, how their sensitive health data is handled, and the limits of available protections.
- Research area
- Health technologies, privacy, and wellbeing
- Status
- Ongoing
- Leadership
- PI: Xinning Gui.
People turn to symptom checkers, conversational AI, and health tracking apps for health information and support. This line of work examines how people understand and use these tools’ advice, how they navigate the data practices behind them, and what protections are available for sensitive health information such as reproductive health data.
Related work was supported by Penn State College of IST seed grants on users’ explanations of AI-powered symptom checkers (2020–2021) and on period and fertility tracking after Roe v. Wade (2023–2024).
Example papers
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Usable Anonymity in Reproductive Health Privacy
Qiurong Song, Yanlai Wu, Rie Helene (Lindy) Hernandez, Yao Li, Yubo Kou, and Xinning Gui
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Understanding Users’ Perception of Personally Identifiable Information
Qiurong Song, Yanlai Wu, Rie Helene (Lindy) Hernandez, Yao Li, Yubo Kou, and Xinning Gui
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Beyond Self-diagnosis: How a Chatbot-based Symptom Checker Should Respond
Yue You, Chun-Hua Tsai, Yao Li, Fenglong Ma, Christopher Heron, and Xinning Gui