Could generative AI assist in extending access to vulnerable populations and begin to bridge the gap in disparities? In this Q&A, Davey Smith, MD, MAS, an infectious disease specialist and virologist at the University of California, San Diego, joins JAMA's Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to explore the implications of large language models for improving patient outcomes. Related Content: Will Generative AI Tools Improve Access to Reliable Health Information?

AI can understand brain signals linked to the sensory and motor processes involved in speech. In this Q&A, Edward Chang, MD, the chair and professor of neurosurgery at UCSF joins JAMA's Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to discuss how AI has the potential to facilitate communication and how close AI development is to being able to translate human emotion. Related Content: Digital Avatars and Personalized Voices—How AI Is Helping to Restore Speech to Patients

Can AI enhance the speed and efficiency of interpreting ultrasounds and echocardiograms, thereby minimizing diagnostic errors? In this Q&A, Rima Arnaout, MD, a cardiologist and associate professor of medicine at the University of California-San Francisco, joins JAMA's Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to discuss the transformative impact of AI on cardiac imaging. Related Content: How Machine Learning Might Help Improve Cardiac Imaging

Automation bias and shortcuts in clinical AI models have posed significant challenges. In this Q&A, Jenna Wiens, PhD, an associate professor of Computer Science and Engineering at the University of Michigan in Ann Arbor, joins JAMA Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to discuss how we can start leveraging human collaboration with AI to provide more effective health care. Related Content: Blind Spots, Shortcuts, and Automation Bias—Researchers Are Aiming to Improve AI Clinical Models

AI in clinical practice needs ethical frameworks to avert future biases. In this Q&A, Marzyeh Ghassemi, PhD, the Herman L. F. von Helmholtz Career Development Professor at MIT in Electrical Engineering and Computer Science (EECS), joins JAMA's Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to discuss ethical machine learning and responsible clinical implementation. Related Content: AI Developers Should Understand the Risks of Deploying Their Clinical Tools, MIT Expert Says

How can we leverage AI to transform health care into a more efficient model for delivering care? In this Q&A, JAMA Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, interviews Atul Butte, MD, PhD, the director of the Bakar Computational Health Sciences Institute at UCSF, to discuss scalable privilege and the need for the broad distribution of AI-driven expertise. Related Content: “Scalable Privilege”—How AI Could Turn Data From the Best Medical Systems Into Better Care for All

Amid the surging buzz around artificial intelligence (AI), can we trust the Al hype, and more importantly, are we ready for its implications? In this Q&A, Arvind Narayanan, PhD, a professor of computer science at Princeton, joins JAMA's Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to discuss the exploration of Al's fairness, transparency, and accountability. Related Content: How to Navigate the Pitfalls of AI Hype in Health Care

Artificial intelligence holds the promise of revolutionizing disease diagnosis and prediction, but it also presents a pivotal challenge: ensuring equity. In this Q&A, Alondra Nelson, PhD, the Harold F. Linder Professor at the Institute for Advanced Study, joins JAMA's Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, to discuss the equitable regulation of AI to benefit all populations. Related Content: How Do Policymakers Regulate AI and Accommodate Innovation in Research and Medicine?

In this Q&A, JAMA Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, interviews John Ayers, PhD, MA, vice chief of innovation in the Division of Infectious Diseases & Global Public Health, deputy director of informatics in the Altman Clinical and Translational Research Institute, and affiliate scientist in the Qualcomm Institute, all at UC San Diego, to discuss how genAI programs like ChatGPT can increase communication pathways and improve patient outcomes. Related Content: How AI Assistants Could Help Answer Patients’ Messages—and Potentially Improve Their Outcomes

In this Q&A, JAMA Editor in Chief Kirsten Bibbins-Domingo, PhD, MD, MAS, interviews Nigam Shah, MBBS, PhD, professor of medicine at Stanford University and chief data scientist at Stanford Health Care, to discuss how large language models are reshaping medicine and the potential pitfalls of automation. Related Content: Clinical AI Tools Must Be Fed the Right Data, Stanford Health Care's Chief Data Scientist Says Creation and Adoption of Large Language Models in Medicine