Last summer, MIT President Sally Kornbluth and Provost Cynthia Barnhart issued a call for papers to “formulate effective roadmaps, policy recommendations, and calls to motion across the sphere of generative AI.” The response to the decision for proposals far exceeded expectations, with 75 proposals submitted. Of these, 27 proposals were chosen for start-up financing.

Given this enthusiastic response, Kornbluth and Barnhart announced a second call for proposals this fall.

“The high level of interest and overall quality of ideas made it clear that a second round was warranted,” they said of their email to MIT’s research community this fall. This second call received 53 submissions.

After the second call, the primary round faculty committee reviewed the proposals and chosen 16 proposals for exploratory funding. Co-authored by interdisciplinary teams of school and researchers from all five schools within the Institute and the MIT Schwarzman College of Computing, the proposals provide insights and perspectives on the potential impact and applications of generative AI across a broad range of topics and disciplines.

Each chosen research group will receive between $50,000 and $70,000 to supply 10-page impact papers. These articles might be widely distributed through a publishing venue managed and hosted by MIT Press under the auspices of the MIT Open Publishing Services program.

As with the primary round of contributions, Thomas Tull, a member of the MIT School of Engineering Dean’s Advisory Board and a former innovation scientist on the School of Engineering, donated funds to support the hassle.

The chosen contributions are:

  • “A Roadmap for End-to-End Privacy and Auditability in Generative AI,” led by Alex Pentland, Srini Devadas, Lalana Kagal, and Vinod Vaikuntanathan;
  • “A Virtuous Cycle: Generative AI and Discovery within the Natural Sciences,” led by Philip Harris and Phiala Shanahan;
  • “Artificial Cambrian Intelligence: Generating New Forms of Visual Intelligence,” led by Ramesh Raskar and Tomaso A. Poggio;
  • “Artificial Fictions and the Value of AI-Generated Art,” led by Justin Khoo;
  • “GenAI for Improving Human-to-Human Interactions with a Focus on Negotiations,” led by Lawrence Susskind;
  • “Generative AI as a brand new application platform and ecosystem”, led by Michael Cusumano;
  • “Generative AI for Cities: A Playbook for Civic Engagement,” led by Sarah Williams, Sara Beery, and Eden Medina;
  • “Generative AI for Textile Engineering: Advanced Materials from Heritage Lace Craft,” led by Svetlana V. Boriskina;
  • “Generative AI Impact for Biomedical Innovation and Drug Discovery,” led by Manolis Kellis, Brad Pentelute and Marinka Zitnik;
  • “Impact of Generative AI on the Creative Industries,” led by Ashia Wilson and Dylan Hadfield-Menell;
  • “Redefining Virtuosity: The Role of Generative AI in Live Music Performance,” led by Joseph A. Paradiso and Eran Egozy;
  • “Reflection-based learning with generative AI”, led by Stefanie Mueller;
  • “Robust and Reliable Systems for Generative AI,” led by Shafi Goldwasser, Yael Kalai and Vinod Vaikuntanathan;
  • “Supporting the Aging Population with Generative AI,” led by Pattie Maes;
  • “The Science of Language within the Age of Generative AI,” led by Danny Fox, Yoon Kim and Roger Levy; And
  • “Visual Artists, Technological Shock and Generative AI,” led by Caroline Jones and Huma Gupta.

This article was originally published at news.mit.edu