As medical AI tools are deployed in the hospital, their accuracy may falter as patients do better. Adam Yala comments on the limitations of predictive models and the needed work to improve them.

In this Q&A, Irene Chen describes how machine learning could help clinicians identify and support victims of intimate partner violence, her work on machine learning for equitable healthcare, and a related upcoming event at UCSF, Toward Algorithmic Justice in Precision Medicine.

JAMA Editor in Chief Dr. Kirsten Bibbins-Domingo, in conversation with Ida Sim, Professor of Medicine, UCSF and CPH co-Director, about the promise and perils of AI in the clinical encounter, and how to keep humanity at the center.

Host Dr. Christine Sinsky, AMA Vice President of Professional Satisfaction, and guest A Jay Holmgren, Assistant Professor of Medicine at UCSF, and the Center for Clinical Informatics and Improvement Research, discuss how assessing Epic Signal data and other EHR metadata can be a useful tool for evaluating team-based interventions to reduce inbox volume.

Time highlights Ziad Obermeyer’s work on detecting racial bias in algorithms and use of machine learning to improve physician decision making, and Stuart Russell’s pioneering work to make sure that AI is beneficial to humans.