Last summer, MIT President Sally Kornbluth and Provost Cynthia Barnhart invited researchers to submit papers that lay out effective strategies, policy recommendations, and urgent actions within the field of generative artificial intelligence (AI). Among the 75 received proposals, 27 were selected for seed funding.
Impressed by the level of interest and the quality of ideas, Kornbluth and Barnhart decided to issue a second call for proposals. This resulted in a submission of 53 more proposals, out of which a faculty committee selected 16 for exploratory funding.
Each chosen research group will receive $50,000 – $70,000 to develop 10-page impact papers. These papers will then be broadly disseminated via the MIT Press that operates under MIT’s Open Publishing Services program. Thomas Tull, a member of the MIT School of Engineering Dean’s Advisory Council and a former innovation scholar at the School of Engineering, provided funding to support this initiative.
The proposals chosen for funding span a wide variety of topics and disciplines, reflecting the broad potential impact and various applications of generative AI. Contributors to these proposals comprised interdisciplinary teams of faculty and researchers affiliated with all five of MIT’s schools and the MIT Schwarzman College of Computing.
The titles of the selected papers cover a wide array of topics in generative AI, from privacy and verifiability to the value of AI-generated art, from its impact on the creative economy to its potential for supporting the aging population. Other topics include generative AI’s possible roles in drug discovery, live music performances, textile engineering, and city development, among others.
In summary, this initiative aims to encourage and fund innovative research in generative AI, with the goal of charting a roadmap for the application and implications of this groundbreaking technology across multiple disciplines. The selected research groups are now tasked with drafting impact papers, whose findings and insights will be shared widely to engage the broader scientific community and the public in discussions around the prospective benefits and risks of generative AI applications.
