Staying Grounded in the Age of AI: Why Statistical Thinking Matters More Than Ever

Artificial intelligence is transforming science and medicine at a remarkable pace, creating unprecedented opportunities for discovery while raising fundamental questions about how we generate, evaluate, and interpret evidence. In this talk, I will reflect on why rigorous statistical thinking remains essential in this rapidly changing landscape. Drawing on examples from my editorial experience at NEJM AI, I will highlight some statistical challenges that relate directly to the use of AI in medicine, including issues related to quantifying real-world impact and balancing the need for both speed and rigor when evaluating AI. I will also discuss lessons from my own research in HIV and global health related to implementing and evaluating decision support tools in a clinical workflow. Finally, I will offer some broader reflections on why investment in both domain-area research and long-term collaborative relationships remains critically important to statistical research and training. My hope is to encourage statisticians, particularly those early in their careers, to embrace the opportunities presented by AI while continuing to deliver the rigor, curiosity, and collaborative spirit that define our discipline.

Presidential Invited Speaker:

Joseph Hogan, ScD is Professor and Chair of Biostatistics, and Carole and Lawrence Sirovich Professor of Public Health, at Brown University. His research concerns development and application of statistical methods for causal inference, missing data, and Bayesian inference for large-scale observational data and randomized trials, with focus in HIV/AIDS and global health. More recently he is interested in methods for design and analysis of studies to understand the impact of AI interventions on individual health outcomes. Joe serves as Co-Director of Biostatistics for AMPATH, an international consortium of universities in the US, Canada and Kenya focused on treatment and prevention of HIV in Kenya; Program co-Director for NAMBARI, an NIH-funded biostatistics training partnership between Brown and Moi University in Kenya; and co-Director of the Biostatistics Core for the Providence-Boston Center for AIDS Research. He has collaborated with the Rhode Island Department of Health on infectious disease surveillance (COVID and HIV) and has served as advisor and consultant for the FDA, NIH, NSF and National Academies of Science. Within ENAR, Joe has served as RECOM member, Associate Editor for Biometrics, and Vice Program Chair for the spring meetings. He is an elected Fellow of the American Statistical Association and currently serves as Statistical Editor for the New England Journal of Medicine and for NEJM-AI.