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 (EECS) and Mathematics, MIT
• Ana Maria Estrada Gomez, Assistant Professor Edwardson School of Industrial Engineering
• David Inouye, Assistant Professor of Electrical and Computer Engineering
• Guang Lin, Moses Cobb Stevens Professor in Mathematical Sciences; College of Science Associate Dean of Research and Innovation; Professor of Mechanical Engineering
• Mohit Tawarmalani, Executive Associate Dean of Strategy, Research, and Innovation, Allison & Nancy Schleicher Chair, Professor