International scientists convene to advance ethical generative AI in healthcare

Nine conference attendees wearing name badges stand in a row in a university lecture hall with wood-paneled walls and a raised stage. Flags and a banner for the University of Calabria are visible behind the group, indicating an academic conference or research meeting.
University of Florida presenters and organizing committee members at the Data and Artificial Intelligence Symposium, or DAISY, workshop, held this year in Italy. Photos by April O’Neal.

By Jill Pease

Six years after its launch, the University of Florida’s Data and Artificial Intelligence Symposium, or DAISY, has reached a new level of global prominence. Hosted last month in Italy, DAISY welcomed an expanded global audience and international slate of collaborators to discuss causal and generative AI for decision making in healthcare, public health and policy.

“Healthcare decisions are now being made using imperfect models and imperfect real-world data. Generative AI can produce recommendations that sound convincing, but that does not mean they are causally valid or will actually improve outcomes,” said Noah Hammarlund, Ph.D., a member of the DAISY organizing committee and an assistant professor of health services research, management and policy in the UF College of Public Health and Health Professions. “DAISY focused on how causal methods, careful evaluation and human oversight can help address that gap.”

DAISY 2026 was offered in conjunction with the flagship conference of the Association for Computing Machinery’s Special Interest Group in Bioinformatics, Computational Biology and Health Informatics, also held for the first time outside the U.S. The event drew participants from 24 countries to the University of Calabria in Rende, Italy.

“Our hosts were incredibly generous and created a conference experience that combined scientific learning and networking with opportunities to experience the region and its culture,” Hammarlund said.

DAISY’s half-day workshop featured a keynote by Takis Benos, Ph.D., the William Bushnell Presidential Chaired Professor at the UF Department of Epidemiology, who discussed how causal discovery approaches can be applied to real-world health data. A moderated panel on causal reliability of decision‑policy design highlighted perspectives from U.S. health policy, technical research and European healthcare and regulation. Panelists included PHHP Dean Beth A. Virnig, Ph.D., Fabrizio Pecoraro, Ph.D., of the Italian National Research Council, and Gregor Stiglic, Ph.D., of the University of Maribor in Slovenia.

Four researchers, selected from peer‑reviewed submissions, gave lightning talks on AI applications in different healthcare contexts. Aprinda Indahlastari Queen, Ph.D., a PHHP assistant professor of clinical and health psychology, delivered a lightning talk on her AI-powered research to help prevent dementia. The workshop also included student research poster presentations.

“My hope is that attendees left thinking beyond simply building more powerful models,” Hammarlund said. “The real goal is to develop AI-supported decisions that can be trusted in real healthcare settings.”

DAISY’s organizing committee also included UF’s Mattia Prosperi, Ph.D., a professor of epidemiology and associate dean for AI and innovation at the College of Public Health and Health Professions, and Yi Guo, Ph.D., a professor of health outcomes and biomedical informatics and division chief at the College of Medicine.