Videos / LLMs, Bias, and the Implications for Equitable Healthcare (56:01)

LLMs, Bias, and the Implications for Equitable Healthcare (56:01)

Data Science for Health Equity

14 July 2026

Last Updated

1 January 2025

In this talk, Irene will discuss two recent projects examining the implications of LLMs on equitable healthcare. First, she will present work designing guiding principles for LLMs in maternal health through participatory design with healthcare workers, women, and birthing people. Next, Irene will demonstrate how LLMs can provide insight into medication switching for contraceptives using clinical notes from UCSF. The talk concludes with a discussion about the implications of LLMs in the existing landscape of bias in medical AI.

Instructor

Irene Chen

Researcher

Professor Irene Chen studies machine learning for equitable healthcare. Her research focuses on two main areas: 1) developing ma...

Organisation

Data Science for Health Equity

Data Science for Health Equity (DSxHE) is a global community that brings together students, researchers, practitioners, and policymakers dedicated to using data science to address and eliminate health disparities. Our mission is to foster an environment where interdisciplinary collaboration can flourish, leading to innovative solutions that promote health equity. Our main goals are to create community, raise awareness, improve individual practices, and influence institutional actions.