Inaugural SERC seed grants aim to advance ethical and responsible computing practices

New seed grants established by the Social and Ethical Responsibilities of Computing (SERC), a cross-cutting initiative of the MIT Schwarzman College of Computing, aims to inspire MIT researchers to make a meaningful contribution to responsible technology development and deployment.

“As computing increasingly transforms nearly every area of human endeavor, it is essential that ethical and societal considerations are interwoven with technical aspects in the design, development, and application of computing solutions,” says Dan Huttenlocher, dean of the MIT Schwarzman College of Computing and Henry Ellis Warren Professor of Electrical Engineering and Computer Science.

The initial call for proposals attracted nearly 70 submissions covering a range of topics, from fairness and bias in data and algorithms to the carbon footprint of computing. Sixteen projects, led by MIT researchers from nine departments across all five schools and the college, have been selected to receive up to $100,000 in funding.

“SERC is dedicated to advancing social and ethical considerations in computing,” says Nikos Trichakis, interim associate dean of SERC in the MIT Schwarzman College of Computing and J.C. Penny Professor of Management. “The seed grants are intended to spark innovation and creativity in tackling the opportunities and challenges within this field. We hope for these projects to pave the way for larger endeavors that will have a lasting, sustainable impact on ethical and responsible computing practices.”

The 16 projects and research leads are:

• “Labeling AI-Generated Content Online,” led by Adam Berinsky, Mitsui Professor of Political Science, and David G. Rand, Erwin H. Schell Professor at MIT Sloan and professor of brain and cognitive sciences;
• “Analytics for Fair and Efficient Kidney Transplant Allocation,” led by Dimitris Bertsimas, Boeing Leaders for Global Operations Professor of Management, and Nikos Trichakis, J.C. Penney Professor of Management and professor of operations management;
• “Leveraging small cohort studies to expand insights from diverse genetic ancestries,” led by Olivia Corradin, assistant professor of biology;
• “A Framework for Participatory Methods and Community Engagement Across the AI/ML Pipeline,” led by Catherine D’Ignazio, associate professor of urban science and planning, and Nikki Stevens, postdoctoral researcher in the Data + Feminism Lab;
• “The Fairness-Efficiency Frontier in Humanitarian Immigration,” led by Daniel Freund, assistant professor of operations management;
• “Code-Side Manner: Evaluating Generative AI’s Role in Clinician/Patient Conversations” led by Marzyeh Ghassemi, associate professor in the Department of Electrical Engineering and Computer Science (EECS) and Institute for Medical Engineering and Science;
• “Towards Equitable and Efficient Organ Transplantation through Longer Preservation Times,” led by Swati Gupta, associate professor of operations research and statistics;
• “The Mathematics of Law-Making in the U.S.,” led by In Song Kim, associate professor of political science, and Jörn Dunkel, MathWorks Professor of Mathematics;
• “The Dark Side of Using Generative AI,” led by Jackson Lu, associate professor of work and organization studies, and Lesley Song, PhD student at MIT Sloan School of Management;
• “Information Sharing, Competition, and Collusion via Algorithms,” led by Manish Raghavan, assistant professor of information technology, and Ashia Wilson, assistant professor of electrical engineering and computer science;
• “Teacher Perspectives on the Arrival of Generative AI in a Watershed School Year,” led by Justin Reich, associate professor of digital media;
• “Empowering Blind/Low-Vision People to Conduct Interactive Data Analysis with LLM-Generated Textual Descriptions,” led by Arvind Satyanarayan, associate professor of computer science;
• “Designing and Evaluating Regulatory Mechanisms to Empower and Constrain AI Supply Chains,” led by Susan Silbey, Leon and Anne Goldberg Professor of Humanities, Sociology and Anthropology, and Aspen Kennedy Hopkins, PhD student in EECS and the Computer Science and Artificial Intelligence Laboratory;
• “Aligning AI with Human Cooperative Norms,” led by Joshua Tenenbaum, professor of computational cognitive science, and Sydney Levine, research affiliate in the Department of Brain and Cognitive Sciences;
• “Experiments on Generative AI and the Future of Digital Democracy,” led by Lily Tsai, Ford Professor of Political Science, and Alex Pentland, Toshiba Professor of Media Arts and Sciences;
• “Minimum Standard of Care for AI: Ethical Risk Assessment for Latin America,” led by Sarah Williams, associate professor of technology and urban planning, and Claudia Dobles, research assistant in the Department of Urban Studies and Planning.