Ever since she was a child playing on her family’s farmland in Wisconsin, Bailey Flanigan was guided by her own selective, yet wide-ranging, curiosity. Describing her young self as spirited and a bit unruly, she directed her energies to everything from building booby traps to doing experimental construction projects to exploring an intense interest in medicine to writing fiction and music to planning nonprofit organizations to help lessen social inequality.
By high school, Flanigan was intensely drawn to particular subjects.
“I found myself unmotivated to take all the AP [advanced placement] classes for the sake of it. My interest was captured by classes where I could be creative — where I could use math to solve real-world problems, creatively write, make music, connect distant ideas, or deeply explore the humanities — and I worked on such classes obsessively, as an opportunity to explore my intuitions and interests,” she says. “Instead of joining clubs, I ended up spending a lot of time thinking and creating on my own, and trying to understand what I enjoyed.”
Today Flanigan is a shared faculty member between the MIT Schwarzman College of Computing and the MIT departments of Political Science and Electrical Engineering and Computer Science (EECS), and a principal investigator in the MIT Laboratory for Information and Decision Systems. She has been involved in research at the University of Wisconsin, the National Institutes of Health, Google, and Carnegie Mellon, Drexel, Harvard, Princeton, and Stanford universities. Her current work focuses on using computational and mathematical tools to create new avenues for meaningful democratic participation.
Perhaps not surprisingly, her path has crossed huge expanses of subject matter and specialties — from medicine and bioengineering to public health, and from economics to her joint appointment at MIT in computer science and political science, which began in fall 2025.
“My trajectory across disciplines was just a result of me chasing down the problems I felt were most pressing or inspiring at the time. Along the way, I wound up in a lot of situations where I was less well-trained or qualified in the standard ways. While this was sometimes precarious, it was also incredibly fun, and it cultivated my ability to learn the languages of new disciplines more easily — a skill pretty much essential to my current research and job.”
In college at the University of Wisconsin at Madison, Flanigan worked in a wet lab on therapeutic targets in cancer and computationally on tumor genetics. She says she found the research intellectually interesting, but eventually began to wonder about whether it would have the kind of impact she wanted.
“At the time, I started to worry that the science I was developing might only, in the best case, be used by a small, relatively wealthy fraction of the world, when there were people suffering from much more-preventable diseases in much larger numbers,” she says.
So Flanigan moved toward public health, where she researched microfluidic devices for HIV detection that could be used in low-resource settings. Still bothered by the circumstances driving these settings’ limited resources to begin with, she then started to dabble in economics.
Around the same time, Flanigan’s academic advisors were chipping away at preconceptions she held about her own abilities.
Steven Wright, a professor of law and creative writing at UW-Madison, served as Flanigan’s informal mentor throughout college, and they worked together on a case at the Wisconsin Innocence Project.
“He guided me through my evolving interests in science, social inequality, and economics,” she says. “He was one of the people most responsible for convincing me that I could aim higher in my career, and that I could actually go to places like MIT or Harvard.”
Also while she was in college, the two heads of the UW-Madison scholarship office, Debbie Berger and Julie Stubbs, sent Flanigan repeated emails, encouraging her to apply for a Goldwater Scholarship.
“I kept deleting their emails, thinking they were spam — I didn’t think I was the kind of person that would apply for something like that. Their persistence convinced me to apply, and in the process, the horizons I perceived for myself started to change,” she says.
After graduating from UW-Madison, Flanigan worked as a predoctoral research assistant in economics at Princeton. There, Professor Evita Nestoridi, now an associate professor at Stony Brook University, also provided a pivotal moment of support, letting Flanigan audit her real analysis class.
“Evita’s class was my first real exposure to formal mathematics and proofs, and I loved it so much that it completely changed my career trajectory,” Flanigan says. “Despite my initial doubts, she convinced me that I could do math at the graduate level; because of her encouragement, I applied to computer science PhD programs the subsequent fall.”
Choosing Carnegie Mellon for her PhD, Flanigan began research on social choice and democratic decision-making, serving her dual passions for technical research and the issue of “who gets what and why,” she says, quoting Nobel Prize-winning economist Al Roth.
Flanigan has developed algorithms that randomly choose participants of citizens’ assemblies, designed for the common case where willing participants self-select in ways that do not reflect the larger population. In a policy brief, Flanigan gave a hypothetical example of an assembly on artificial intelligence, whose willing participants might skew toward younger, more educated citizens with an interest in technology, leaving other groups underrepresented despite their stake in the issue. The tools Flanigan has developed help balance representation with such features of the selection process as equality among individuals’ chances to participate, resistance to manipulation of the process, and transparency — all of which can affect the general perception of a decision-making group’s legitimacy.
Flanigan’s work is now deployed on panelot.org, a widely used open-access website hosting algorithms for randomly selecting citizen assembly participants.
“The site basically walks practitioners through a series of otherwise very technical trade-offs, making those trade-offs legible and then optimizing according to the priorities practitioners dictate,” she says.
Flanigan says she is motivated to improve how the public makes political decisions, “because if any political solution is going to be viable, the public needs to feel that it was arrived at via a legitimate political process — at least under the forms of government I find most appealing.”
Beyond her work on citizens’ assemblies, Flanigan’s research is exploring new avenues related to how to more systematically get public input on complex decisions, and how the format of questions we ask people in preference elicitation contexts can affect the substance of what we conclude.
“I feel so lucky to be studying these questions from within both political science and EECS, because I have the freedom to explore both the political and technical substance of tools for more direct governance as deeply as I want,” she says.
Flanigan’s curiosity-driven journey through widely varying terrain feels right in the MIT environment, she says.
“From the beginning, I got this sense of belonging at MIT — like my ways of thinking and problem-solving, which had seemed peculiar in many situations, actually made me belong more,” she says. “This was a super refreshing feeling, and it has been 100 percent borne out since I arrived.”
