On March 19, 2026 in a conversation moderated by D&S AI on the Ground program director Ranjit Singh, Kristin M. Branson, Lisa Messeri, and Nicole C. Nelson discussed the impact of machine learning tools on the nature of proof, inference, uncertainty, and error in scientific workflows today.
As AI is integrated into scientific practice, the practice of science itself is changing. AI models that summarize, categorize, simulate, and predict not only stand to accelerate scientific research; they now sit inside these practices, alternately enhancing and eroding craft while shifting how questions are posed, what counts as evidence, how tacit judgment is taught and exercised, and reshaping trust in results.
Dr. Kristin M. Branson (@kristinmbranson.bsky.social) is a senior group leader at the Howard Hughes Medical Institute’s (HHMI) Janelia Research Campus in Ashborn, Virginia.
Dr. Lisa Messeri (@lmesseri.bsky.social) is an associate professor of sociocultural anthropology at Yale University.
Dr. Nicole C. Nelson (@nicolecnelson.bsky.social) is an associate professor in the Department of Medical History and Bioethics at the University of Wisconsin–Madison.