Biostatistics Dept. Seminar: Principled AI

Biostatistics Department Seminar 

Title: Principled AI

Abstract: We are entering an era where artificial intelligence is transforming science, medicine, and society, yet the enduring principles of statistics remain central to ensuring validity, interpretability, and trust. This talk reflects on core statistical foundations, including error control and calibration, optimality and decision-theoretic framing, reproducibility and robustness, sampling, prior/empirical Bayes, modern statistical/mathematical computation, and the likelihood principle. And we will examine their continued impact in the age of AI. Through examples drawn from several clinical studies, the discussion will show how principled statistical thinking safeguards against bias while enabling innovation. These case studies illustrate that statisticians are not bystanders but essential architects of reliable evidence generation and decision-making in an AI-driven world.

Speaker

Yong Chen is a professor of biostatistics in the Department of Biostatistics, Epidemiology, and Informatics (DBEI), and a senior scholar at the Center for Clinical Epidemiology & Biostatistics (CCEB) at the University of Pennsylvania Perelman School of Medicine.

Zoom Registration

If you would like to join via Zoom, please register here.

2025-2026 Monday Seminar Series

All seminars are held at 12:05 PM via Zoom and onsite. View all seminar information here.