Preface

We are pleased to share this volume of papers on generative AI and its broader impacts, written by MIT faculty and researchers and their collaborators. These papers resulted from a call issued by President Sally Kornbluth and Provost Cynthia Barnhart to provide roadmaps, policy recommendations, and calls for action across the broad domain of generative AI.

These 25 papers, resulting from 75 proposals in response to the call, reveal the striking breadth of interest in and work on generative AI across MIT. They offer insights of broad relevance beyond academia, ranging from experimental results in the social sciences, to scholarly investigations in the arts and humanities, to analyses and proposed directions for work in science and engineering. They offer recommendations in many areas, including healthcare, government, education, climate, environment, innovation, and human flourishing. To develop their ideas, the authors of the papers in this collection received seed funding from MIT.

We knew early on that we wanted the results of these varied research projects to be made discoverable and broadly accessible as quickly as possible. These papers are works in progress; the research evolving as rapidly as this new era of AI. We expect many of these projects will lead to further academic, industry, and policy impact. The papers should be considered “preprints,” that is, research that has been made available before being formally peer reviewed. The collection is openly accessible under a CC license.

We invite readers to explore and engage with the topical issues and insights at the intersections of generative AI and engineering, science, education, social sciences, humanities and the arts. Generative AI has implications for all of us.

We are grateful to Thomas Tull, a member of the Engineering Dean’s Advisory Council and a former innovation scholar at the School of Engineering, for his foresight in supporting this effort. This collection of papers also would not have been possible without the leadership of Anantha Chandrakasan, the chief innovation and strategy officer and dean of engineering at MIT. We also would like to recognize Professors Caspar Hare and Ron Rivest along with almost 20 faculty and researchers at MIT for their participation in evaluating the submissions that led to these papers, as well as the staff members without whose effort this volume would not exist.

Daniel Huttenlocher
Dean, MIT Schwarzman College of Computing
Henry Ellis Warren (1894) Professor, Electrical Engineering and Computer Science

Asu Ozdaglar
Deputy Dean, MIT Schwarzman College of Computing
Department Head and Mathworks Professor, Electrical Engineering and Computer Science