Ushering in the Algorithmic Century: Duke’s Pathfinding Leadership in Ensuring that Health AI Is Safe, Effective & Equitable for All

In this seminar, Dr. Michael Pencina, Vice Dean for Data Science, Chief Data Scientist for Duke Health, and Director of Duke AI Health, will examine the ongoing revolution in health data science and the application of artificial intelligence tools to the field of medicine. He will trace the evolution of increasingly sophisticated AI-powered technologies now being leveraged for patient care and clinical research, surveying the challenges and opportunities presented by these algorithmic technologies. In particular, the seminar will focus on the increasingly urgent need for robust oversight of health AI tools that encompass the entire lifecycle of such technologies, from development through validation and deployment. He will explain how robust frameworks of review and continuous oversight - including ones being articulated by Duke and its partners - are critical to ensuring that current and future applications of AI in healthcare and clinical research are safe, accurate, trustworthy, and equitable. This seminar will emphasize Duke University's contributions to a field that is rapidly reshaping the practice of healthcare and biomedical science for the coming century. The presentation will touch on the history of applied health data science at Duke, understood as part of a tradition of innovation that dates back to the pioneering efforts of Duke Cardiology professor Eugene Stead in creating computer-based predictive tools for improving patient care. In addition, the seminar will also acknowledge the larger legacy of innovation and collaboration between the disciplines of medicine and computer science at the university. It will also explore how Duke continues to play a major role in the AI revolution as it transforms medicine and clinical research in the coming century, with particular emphasis on developing frameworks of governance, review, and oversight that ensure that health AI technologies are safe, trustworthy, and equitable.