Conferences and Workshops

Most recent

AI and the Nature of Science: Concepts and Controversies 

Symposium, Friday 14 November 2025

Artificial Intelligence (AI) is reshaping the landscape of academics, business, politics, and the scientific enterprise. For the latter, there have been diverse and groundbreaking applications of large language models and machine learning methods in physics, chemistry, biology, medicine, cognitive science/psychology, and social science. However, these applications also raise a number of conceptual questions, including but not limited to: how does scientific understanding connect with successful predictions from AI? What role do explanatory theories have when AI methods are applied to big data? Can AI lead to paradigm shifts? How should credit for discovery be attributed when AI plays a key role in scientific inquiry?

In an attempt to explore these and related questions more intentionally, we organized a symposium at the University of Minnesota under the auspices of the Data Science Initiatives recently launched here (in the College of Liberal Arts and College of Science and Engineering). The goal was to bring together cutting-edge perspectives on these questions and help set an agenda for future research and application. 

Speakers:

• Carl T. Bergstrom, University of Washington

• Cameron Buckner, University of Florida

• Thomas Byrd, University of Minnesota

• Lisa Messeri, Yale University

• Claudia Scarlata, University of Minnesota