Watch the live webcast on April 27, 10:15 a.m. EDT.

Six new members present their research and answer questions from the audience.

Much of the conversation we hear today about Artificial Intelligence (AI) focuses on fears concerning loss of privacy, lack of transparency and accountability, increase in inequality, and other social and economic issues. The widespread availability of generative AI is fueling much of this debate. However, AI is more than just large language models, and in fact versions of AI have been fueling scientific discovery and exploration for several decades now. This session will be an opportunity to hear from speakers at the forefront of developing AI to advance research by automating workflows, finding patterns in large and complex data sets, mitigating human bias, improving models, speeding up tedious tasks, and exploring domains inhospitable to humans. The session will explore both the promise of and various possible futures for AI-assisted research.


Organizers: Marcia McNutt, President, National Academy of Sciences; William H. Press, Treasurer, National Academy of Sciences; Warren J. and Viola M. Raymer Professor, The University of Texas at Austin; Michael S. Witherell, Laboratory Director, Lawrence Berkeley National Laboratory


AI and Science

Jeannette M. Wing, (session chair), Executive Vice President for Research, Professor of Computer Science, Columbia University

A New Era of Digital Biology

Pushmeet Kohli, Vice President for Research, Google DeepMind

Using AI to Accelerate Drug Discovery

Daphne Koller, CEO and Founder, insitro

The Perpetual Motion Machine of AI-Generated Data and the Distraction of ChatGPT as a ‘Scientist’

Jennifer Listgarten, Professor, Electrical Engineering & Computer Science; Center for Computational Biology, University of California, Berkeley

The Impact of AI on Weather Prediction and Climate Simulation

Michael Pritchard, Associate Professor, University of California, Irvine and Director of Climate Simulation Research, NVIDIA