In response to a call for research proposals on generative AI issued last summer, MIT President Sally Kornbluth and Provost Cynthia Barnhart received an overwhelming response from the MIT research community. The initiative resulted in the submission of 75 proposals, with 27 receiving seed funding.
Gaining significant insight from the quality of ideas received, they issued a second call for proposals in the fall. The second call generated 53 submissions.
After thorough consideration, an interdisciplinary faculty committee selected 16 proposals to receive exploratory funding that ranged between $50,000 and $70,000. These teams, coming from all five of the Institute’s schools and the MIT Schwarzman College of Computing, were asked to create impact papers on a wide variety of topics, to illuminate the potential impact and applications of generative AI.
The impact papers will be publicly circulated via a publication platform managed by the MIT Press within the MIT Open Publishing Services program. The effort is financially supported by Thomas Tull, a member of the MIT School of Engineering Dean’s Advisory Council, and a former innovation scholar at the School.
The chosen proposals encompass a range of topics:
1. An exploration into the realm of privacy and verifiability in generative AI.
2. A study on the intersection of generative AI and discovery in the physical sciences.
3. An investigation into the development of visual intelligence through AI.
4. A comprehensive look at the value of AI-generated art.
5. The application of generative AI to enhance human interaction with a focus on negotiation.
6. Evaluating the potential of generative AI as a platform for new applications and ecosystems.
7. Applying generative AI into civic engagement in cities.
8. Incorporating generative AI into textile engineering with an emphasis on heritage lace craft.
9. Assessing the impact of generative AI on biomedical innovation and drug discovery.
10. Analyzing the influence of generative AI on the creative economy.
11. Exploring the role of generative AI in live music performances.
12. Investigating the application of generative AI in reflection-based learning.
13. Developing robust and reliable systems for generative AI.
14. Exploring the potential of generative AI in supporting an aging population.
15. Looking into the science of language in the era of generative AI.
16. Investigating the interface of visual artists, technological shock, and generative AI.
This initiative reflects the MIT’s commitment to the development and comprehensive understanding of generative AI and shows its potential impacts across multiple fields.
