Redefining Intro Statistics in the Age of AI: Perspectives from Academe, Industry, and Government

As artificial intelligence (AI) technologies continue to become more prevalent, the role of foundational statistical education is increasingly critical. This panel brings together experts from academia, industry, and government, including representatives of the College GAISE revision steering committee, to explore the evolving significance of undergraduate introductory statistics courses in preparing the next generation of professionals. With AI technologies impacting data analysis, decision-making, and problem-solving, the panelists will discuss how statistical curricula must adapt to meet these new demands. The panelists will consider how the need to account for the impact of AI technologies should be reflected in the recommendations in the revised College GAISE report. Key topics include the integration of AI tools into coursework, the balance between theoretical understanding and practical application, and the development of skills essential for a workforce that increasingly relies on data-driven insights. Attendees will gain diverse perspectives on how to ensure that introductory statistics courses not only remain relevant but also serve as a robust foundation for students navigating an AI-driven world. Patti Frazer Lock who is co-chairing the College GAISE Steering Committee and professor in the department of mathematics, computer science, and statistics at St. Lawrence University will chair this session and will be joined by confirmed panelists - Ji-Hyun Lee, 2025 ASA President, professor of Biostatistics, and Associate Director for the Cancer Quantitative Sciences at the University of Florida Health Cancer Center (UFHCC), Amarjot Kaur, Executive Director, Merck, Wendy Martinez, Senior Mathematical Statistician for Data Science, Research and Methodology, U.S. Census Bureau, Jun Yan, Professor, Department of Statistics, University of Connecticut and editor, Journal of Data Science, Lisa Kay, Professor, Department of Mathematics and Statistics, Eastern Kentucky University and College GAISE Revision Steering Committee, and ChatGPT. The panel plans to explicitly ask ChatGPT to respond to the questions posed by the chair and the audience since ChatGPT contributed to the development of this abstract.