Ever since she was a toddler 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 all the pieces from constructing booby traps to doing experimental construction projects to exploring an intense interest in medicine to writing fiction and music to planning nonprofit organizations to assist lessen social inequality.
By highschool, Flanigan was intensely drawn to particular subjects.
“I discovered myself unmotivated to take all of the AP [advanced placement] classes for the sake of it. My interest was captured by classes where I may very well be creative — where I could use math to unravel real-world problems, creatively write, make music, connect distant ideas, or deeply explore the humanities — and I worked on such classes obsessively, as a chance to explore my intuitions and interests,” she says. “As a substitute of joining clubs, I ended up spending loads of time considering and creating alone, and trying to know 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 within the MIT Laboratory for Information and Decision Systems. She has been involved in research on 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 recent avenues for meaningful democratic participation.
Perhaps not surprisingly, her path has crossed huge expanses of subject material 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 only a results of me chasing down the issues I felt were most pressing or inspiring on the time. Along the way in which, I wound up in loads of situations where I used to be less well-trained or qualified in the usual ways. While this was sometimes precarious, it was also incredibly fun, and it cultivated my ability to learn the languages of latest disciplines more easily — a skill just about essential to my current research and job.”
In college on 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 could have the sort of impact she wanted.
“On the time, I began to worry that the science I used to be developing might only, in the perfect case, be utilized by a small, relatively wealthy fraction of the world, when there have been people affected by 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 may very well be utilized in low-resource settings. Still bothered by the circumstances driving these settings’ limited resources to start with, she then began to dabble in economics.
Around the identical time, Flanigan’s academic advisors were chipping away at preconceptions she held about her own abilities.
Steven Wright, a professor of law and artistic writing at UW-Madison, served as Flanigan’s informal mentor throughout college, they usually worked together on a case on the Wisconsin Innocence Project.
“He guided me through my evolving interests in science, social inequality, and economics,” she says. “He was considered one of the people most liable for convincing me that I could aim higher in my profession, and that I could actually go to places like MIT or Harvard.”
Also while she was in college, the 2 heads of the UW-Madison scholarship office, Debbie Berger and Julie Stubbs, sent Flanigan repeated emails, encouraging her to use for a Goldwater Scholarship.
“I kept deleting their emails, considering they were spam — I didn’t think I used to be the sort of person that might apply for something like that. Their persistence convinced me to use, and in the method, the horizons I perceived for myself began to alter,” 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 evaluation class.
“Evita’s class was my first real exposure to formal mathematics and proofs, and I loved it a lot that it completely modified my profession trajectory,” Flanigan says. “Despite my initial doubts, she convinced me that I could do math on the graduate level; due to her encouragement, I applied to computer science PhD programs the next fall.”
Selecting Carnegie Mellon for her PhD, Flanigan began research on social alternative and democratic decision-making, serving her dual passions for technical research and the difficulty of “who gets what and why,” she says, quoting Nobel Prize-winning economist Al Roth.
Flanigan has developed algorithms that randomly select participants of residents’ assemblies, designed for the common case where willing participants self-select in ways in which don’t reflect the larger population. In a policy transient, Flanigan gave a hypothetical example of an assembly on artificial intelligence, whose willing participants might skew toward younger, more educated residents with an interest in technology, leaving other groups underrepresented despite their stake in the difficulty. The tools Flanigan has developed help balance representation with such features of the choice process as equality amongst individuals’ probabilities to participate, resistance to manipulation of the method, and transparency — all of which may affect the final 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 choosing citizen assembly participants.
“The location principally walks practitioners through a series of otherwise very technical trade-offs, making those trade-offs legible after which optimizing in line with the priorities practitioners dictate,” she says.
Flanigan says she is motivated to enhance how the general public makes political decisions, “because if any political solution goes to be viable, the general public must feel that it was arrived at via a legitimate political process — at the least under the forms of presidency I find most appealing.”
Beyond her work on residents’ assemblies, Flanigan’s research is exploring recent avenues related to how one can more systematically get public input on complex decisions, and the way 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 inside each political science and EECS, because I even have the liberty to explore each the political and technical substance of tools for more direct governance as deeply as I need,” she says.
Flanigan’s curiosity-driven journey through widely various terrain feels right within the MIT environment, she says.
“From the start, I got this sense of belonging at MIT — like my ways of considering and problem-solving, which had seemed peculiar in lots of situations, actually made me belong more,” she says. “This was an excellent refreshing feeling, and it has been 100% borne out since I arrived.”