Ever since she was a toddler enjoying on her household’s farmland in Wisconsin, Bailey Flanigan was guided by her personal selective, but wide-ranging, curiosity. Describing her younger self as spirited and a bit unruly, she directed her energies to every little thing from constructing booby traps to doing experimental building initiatives to exploring an intense curiosity in medication to writing fiction and music to planning nonprofit organizations to assist reduce social inequality.
By highschool, Flanigan was intensely drawn to explicit topics.
“I discovered myself unmotivated to take all of the AP [advanced placement] lessons for the sake of it. My curiosity was captured by lessons the place I may very well be artistic — the place I might use math to unravel real-world issues, creatively write, make music, join distant concepts, or deeply discover the humanities — and I labored on such lessons obsessively, as a possibility to discover my intuitions and pursuits,” she says. “As a substitute of becoming a member of golf equipment, I ended up spending numerous time considering and creating by myself, and making an attempt to know what I loved.”
In the present day Flanigan is a shared school member between the MIT Schwarzman Faculty of Computing and the MIT departments of Political Science and Electrical Engineering and Pc Science (EECS), and a principal investigator within the MIT Laboratory for Data and Determination Methods. She has been concerned in analysis on the College of Wisconsin, the Nationwide Institutes of Well being, Google, and Carnegie Mellon, Drexel, Harvard, Princeton, and Stanford universities. Her present work focuses on utilizing computational and mathematical instruments to create new avenues for significant democratic participation.
Maybe not surprisingly, her path has crossed big expanses of material and specialties — from medication and bioengineering to public well being, and from economics to her joint appointment at MIT in pc science and political science, which started in fall 2025.
“My trajectory throughout disciplines was only a results of me chasing down the issues I felt had been most urgent or inspiring on the time. Alongside the best way, I wound up in numerous conditions the place I used to be much less well-trained or certified in the usual methods. Whereas this was typically precarious, it was additionally extremely enjoyable, and it cultivated my capacity to study the languages of latest disciplines extra simply — a ability just about important to my present analysis and job.”
In faculty on the College of Wisconsin at Madison, Flanigan labored in a moist lab on therapeutic targets in most cancers and computationally on tumor genetics. She says she discovered the analysis intellectually attention-grabbing, however ultimately started to marvel about whether or not it could have the type of impression she needed.
“On the time, I began to fret that the science I used to be creating would possibly solely, in the very best case, be utilized by a small, comparatively rich fraction of the world, when there have been folks affected by a lot more-preventable illnesses in a lot bigger numbers,” she says.
So Flanigan moved towards public well being, the place she researched microfluidic gadgets for HIV detection that may very well be utilized in low-resource settings. Nonetheless bothered by the circumstances driving these settings’ restricted sources to start with, she then began to dabble in economics.
Across the similar time, Flanigan’s educational advisors had been chipping away at preconceptions she held about her personal skills.
Steven Wright, a professor of regulation and inventive writing at UW-Madison, served as Flanigan’s casual mentor all through faculty, and so they labored collectively on a case on the Wisconsin Innocence Venture.
“He guided me by my evolving pursuits in science, social inequality, and economics,” she says. “He was one of many folks most accountable for convincing me that I might purpose greater in my profession, and that I might truly go to locations like MIT or Harvard.”
Additionally whereas she was in faculty, the 2 heads of the UW-Madison scholarship workplace, Debbie Berger and Julie Stubbs, despatched Flanigan repeated emails, encouraging her to use for a Goldwater Scholarship.
“I saved deleting their emails, considering they had been spam — I didn’t suppose I used to be the type of particular person that might apply for one thing like that. Their persistence satisfied me to use, and within the course of, the horizons I perceived for myself began to alter,” she says.
After graduating from UW-Madison, Flanigan labored as a predoctoral analysis assistant in economics at Princeton. There, Professor Evita Nestoridi, now an affiliate professor at Stony Brook College, additionally supplied a pivotal second of help, letting Flanigan audit her actual evaluation class.
“Evita’s class was my first actual publicity to formal arithmetic and proofs, and I beloved it a lot that it utterly modified my profession trajectory,” Flanigan says. “Regardless of my preliminary doubts, she satisfied me that I might do math on the graduate degree; due to her encouragement, I utilized to pc science PhD applications the next fall.”
Selecting Carnegie Mellon for her PhD, Flanigan started analysis on social alternative and democratic decision-making, serving her twin passions for technical analysis and the difficulty of “who will get what and why,” she says, quoting Nobel Prize-winning economist Al Roth.
Flanigan has developed algorithms that randomly select individuals of residents’ assemblies, designed for the frequent case the place prepared individuals self-select in methods that don’t mirror the bigger inhabitants. In a coverage transient, Flanigan gave a hypothetical instance of an meeting on synthetic intelligence, whose prepared individuals would possibly skew towards youthful, extra educated residents with an curiosity in know-how, leaving different teams underrepresented regardless of their stake within the situation. The instruments Flanigan has developed assist stability illustration with such options of the choice course of as equality amongst people’ possibilities to take part, resistance to manipulation of the method, and transparency — all of which may have an effect on the overall notion of a decision-making group’s legitimacy.
Flanigan’s work is now deployed on panelot.org, a broadly used open-access web site internet hosting algorithms for randomly choosing citizen meeting individuals.
“The positioning mainly walks practitioners by a sequence of in any other case very technical trade-offs, making these 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 selections, “as a result of if any political resolution goes to be viable, the general public must really feel that it was arrived at by way of a authentic political course of — not less than beneath the types of authorities I discover most interesting.”
Past her work on residents’ assemblies, Flanigan’s analysis is exploring new avenues associated to the right way to extra systematically get public enter on advanced selections, and the way the format of questions we ask folks in desire elicitation contexts can have an effect on the substance of what we conclude.
“I really feel so fortunate to be finding out these questions from inside each political science and EECS, as a result of I’ve the liberty to discover each the political and technical substance of instruments for extra direct governance as deeply as I would like,” she says.
Flanigan’s curiosity-driven journey by broadly various terrain feels proper within the MIT atmosphere, she says.
“From the start, I bought this sense of belonging at MIT — like my methods of considering and problem-solving, which had appeared peculiar in lots of conditions, truly made me belong extra,” she says. “This was a brilliant refreshing feeling, and it has been one hundred pc borne out since I arrived.”
