Generative AI in Medicine

Excitement about the promise of generative AI in medicine has inspired an explosion of new applications. Generative models have the potential to change how care is delivered (1-5), the roles and responsibilities of care providers (6, 7), and the communication pathways between patients and providers (8, 9). Further upstream, generative models have shown promise in improving scientific discovery in medicine (through both clinical trials (10, 11) and observational research (12, 13)) and facilitating medical education (8, 14). These developments are a direct result of technical advances in generative AI, which have drastically increased the ability to generate realistic language and images, and raise important questions about how to integrate generative models into medicine. Generative AI is the latest in a series of technical advances that have driven major shifts in medicine. Past significant advances include the adoption of electronic health records (EHRs); the integration of robotics into telesurgeries (15); and the incorporation of predictive models and continuous monitoring as foundational infrastructure for new diagnostic tools (16, 17).