The MIT administration issued an open call for papers on generative AI, attracting 75 proposals above expectations. Following this, MIT’s President, Sally Kornbluth, and Provost, Cynthia Barnhart, issued a second call for proposals which saw 53 submissions. Now, 16 of these submissions have been chosen by the faculty committee to receive exploratory funding for detailed research.
The chosen projects will receive grants ranging from $50,000 to $70,000 to produce 10-page impact papers. The topics of these selected proposals vary widely across different faculties and disciplines, reflecting a broad spectrum of generative AI applications and impacts. Notably, many of the proposals come from interdisciplinary faculty and researcher teams representing all five of the Institute’s schools and the MIT Schwarzman College of Computing, underlining the wide-reaching interest and potential of generative AI.
The selected papers cover a vast range of topics from the use of generative AI in privacy, physical sciences, visual intelligence, art, human interactions, negotiations, new applications, civic engagement, textile engineering, biomedical innovation, the creative economy, live music performances, learning systems, supporting the aging population, understanding language, to visual arts. The authors of the papers come from a diverse range of disciplines, demonstrating the pervasiveness of AI technology.
These papers are to be disseminated widely via a publication medium managed and hosted by MIT Press under the MIT Open Publishing Services program, ensuring widespread accessibility and impact. The funding for the projects was supported in part by a former innovation scholar and current advisory council member of MIT School of Engineering, Thomas Tull.
The dual call for projects and its overwhelming response signifies the rapid growth and interest in AI across a multitude of fields. Furthermore, the seed funding of selected proposals highlights MIT’s active encouragement and promotion of AI research within its academic community. Not only does this help expand our knowledge and understanding of AI’s capacity, but it also pushes the boundaries of its applicability across various disciplines.
