From the Patient to the Dataset: Humanities Methods for Trustworthy Health AI

Name: From the Patient to the Dataset: Humanities Methods for Trustworthy Health AI
Start: 2026-04-21T18:30:00-04:00
End: 2026-04-21T20:00:00-04:00
Location: Private Location (register to display)

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Lecture AI Health and Wellness Open to Faculty/Staff Open to Students Open to the Public

Tue, Apr 21, 2026

6:30 PM – 8 PM EDT (GMT-4)

Private Location (register to display)

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Event poster. Flyer for From the Patient to the Dataset: Humanities Methods for Trustworthy Health AI

What does it mean to trust an AI with your health? As large language models (LLMs) reshape how patient stories are collected, interpreted and acted upon in clinical settings, the humanities have never been more urgently needed in medicine.

Join us for a talk by Kirsten Ostherr, Professor of English and Director of the Medical Humanities program at Rice University. She argues that digital health humanities offers a critical framework for evaluating AI trustworthiness and bridges narrative medicine with the large-scale data methods driving health AI today. Her talk traces the journey from the personal health narrative to the large language model, and makes the case for why that gap demands new interdisciplinary thinking.

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