Hosted by the College of Engineering and Edwardson School of Industrial Engineering

Abstract

Generative AI is transforming how we collect, synthesize and interpret data, but it also blurs the line between evidence, simulation and modeling. This panel will examine how model-building and decision-making are changing in the age of generative models, probing when we should trust generative AI-assisted analysis, how to keep humans meaningfully “in the loop,” and what new methodological developments are needed to ensure that powerful generative tools improve, rather than erode, responsible model-building and decision-making.

Moderator

• Harsha Honnappa, Associate Professor Edwardson School of Industrial Engineering

Panelists

• Martin Wainwright, Cecil H. Green Professor in Electrical Engineering and Computer Science and Mathematics, MIT
• David Inouye, Assistant Professor, Elmore Family School of Electrical and Computer Engineering
• Ana Maria Estrada Gomez, Assistant Professor, Edwardson School of Industrial Engineering
• Guang Lin, Associate Dean of Research and Innovation, Moses Cobb Stevens Professor, Mathematical Sciences and Professor of Mechanical Engineering
• Mohit Tawarmalani, Executive Associate Dean of Strategy, Research, and Innovation, Allison & Nancy Schleicher Chair, Daniels School of Business