MIT Seed Grants Fuel Ethical Computing Research

Researchers Tackle AI Bias, Transplant Fairness, and Online Discourse

A new wave of research at MIT is confronting the complex ethical and societal implications of rapidly advancing technology. Fifteen projects, supported by seed grants from the Social and Ethical Responsibilities of Computing (SERC) initiative, were recently showcased at a symposium, highlighting innovative approaches to responsible innovation.

Fairer Kidney Allocation with AI

Current policies governing kidney transplants in the United States can be agonizingly slow, often taking years to implement changes—a timeframe many patients simply don’t have. Dimitris Bertsimas, vice provost for open learning at MIT, presented a groundbreaking algorithm that dramatically accelerates the evaluation of potential policy scenarios.

Bertsimas’s system analyzes factors like location, mortality risk, and age in a mere 14 seconds, a stark contrast to the typical six hours required by existing methods. He collaborates closely with the United Network for Organ Sharing (UNOS) to refine and implement the technology.

“This optimization radically changes the turnaround time for evaluating these different simulations of policy scenarios. It used to take us a couple months to look at a handful of different policy scenarios, and now it takes a matter of minutes to look at thousands and thousands of scenarios. We are able to make these changes much more rapidly, which ultimately means that we can improve the system for transplant candidates much more rapidly.”

—James Alcorn, Senior Policy Strategist at UNOS

According to the National Kidney Foundation, over 100,000 Americans are currently on the waiting list for a kidney transplant. (National Kidney Foundation, 2024)

Navigating the Ethics of AI-Generated Content

As artificial intelligence increasingly generates content online, questions arise about transparency and its impact on user perception. Adam Berinsky, Mitsui Professor of Political Science, and PhD student Gabrielle Péloquin-Skulski investigated how different labels on AI-generated posts affect trust and engagement.

Their research revealed that a “process-oriented” label—describing *how* the content was created—can paradoxically decrease belief in both true and false posts. This suggests that labels combining process and veracity information may be more effective in combating misinformation.

Watch Dimitris Bertsimas’s presentation on kidney transplant allocation.

AI for More Civil Online Dialogue

Lily Tsai, Ford Professor of Political Science, is leading research into using generative AI to foster more constructive online discussions. Her team has developed DELiberation.io, an AI-integrated platform designed to enhance online deliberation and address issues of information overload and incivility.

“If you take nothing else from this presentation, I hope that you’ll take away this — that we should all be demanding that technologies that are being developed are assessed to see if they have positive downstream outcomes, rather than just focusing on maximizing the number of users,” Tsai urged the audience.

Liberatory AI: A New Public Think Tank

Catherine D’Ignazio, associate professor of urban science and planning, and Nikko Stevens, a postdoctoral researcher, co-founded Liberatory AI, a “rolling public think tank” dedicated to exploring all facets of artificial intelligence. The initiative brings together researchers from diverse backgrounds to challenge the status quo and advocate for a more equitable and transformative approach to AI development.

The group published over 20 position papers, categorized into themes of the corporate AI landscape, dead ends, and potential pathways forward.

These projects represent a growing commitment at MIT to ensuring that technological advancements are guided by ethical considerations and contribute to a more just and equitable future.