Online lunch event: Slow Science in Times of AI
Artificial intelligence promises faster research: automated analysis, generated text, shorter publication cycles. The Slow Science Movement argues that good research needs time, reflection and careful collaboration. This event examines what slow science can mean in an AI driven research environment.
David Ginsbourger, Professor of Statistical Data Science and Director of the Institute of Mathematical Statistics and Actuarial Science, University of Bern, presents STRADA (www.strada.unibe.ch), the university's initiative connecting disciplinary knowledge with AI methods. He discusses opportunities and limits of AI for scientific practice.
Dr. Matteo Negri of the Slow Science Movement (www.slow-science.com) present their demands addressed to funders, institutions, publishers and researchers: more time for reflection, broader evaluation criteria, incentives for careful review, and stronger collaboration among researchers.
The event raises questions for discussion: Where can AI create room for reflection instead of adding pressure? Which research tasks gain from automation, and which lose quality when accelerated? Can AI even provide tools for slow science?
25. November 2026, 12:15
Online