In the landscape of modern academia, the silos between "hard" science and the humanities have long been considered impassable. However, Bailey Flanigan, a rising star in computational social science and a newly appointed faculty member at the Massachusetts Institute of Technology (MIT), is proving that the most pressing problems of the 21st century exist exactly in the space where those silos crumble.

As a joint faculty member between the MIT Schwarzman College of Computing and the departments of Political Science and Electrical Engineering and Computer Science (EECS), Flanigan is spearheading a movement to use rigorous mathematics to fortify democratic institutions. Her journey—from a spirited child on a Wisconsin farm to a principal investigator at MIT’s Laboratory for Information and Decision Systems—is a testament to the power of interdisciplinary curiosity.

A Childhood of Unruly Curiosity

Long before she was developing algorithms to ensure representative democracy, Bailey Flanigan was a child defined by an insatiable, albeit unconventional, intellectual appetite. Growing up on a family farm in Wisconsin, she was known for being "spirited and a bit unruly." Her energy was not directed toward traditional extracurriculars, but rather toward a sprawling array of interests: constructing elaborate booby traps, engaging in experimental building projects, diving into the intricacies of medicine, and weaving together fiction and music.

Even then, she was already thinking about the world’s structural flaws. She spent time planning nonprofit organizations designed to address social inequality, hinting at the civic-minded researcher she would eventually become. By the time she reached high school, her detachment from standard academic requirements became clear. She found the "check-the-box" nature of Advanced Placement (AP) classes uninspiring, preferring to obsessively dedicate her time to creative pursuits—using mathematics to model real-world problems or exploring the humanities. She spent her formative years learning a vital lesson: that deep, independent creative work often yields more insight than the prescribed path.

The Chronology of a Non-Linear Career

Flanigan’s path to MIT was anything but a straight line. It was a series of intellectual pivots, each driven by a desire to address the most urgent problems of the time.

The Scientific Foundation (University of Wisconsin-Madison)

During her undergraduate years at UW-Madison, Flanigan began in the laboratory, focusing on the therapeutic targets of cancer and the computational analysis of tumor genetics. While intellectually rigorous, she soon faced a moral crossroads. She began to question the real-world impact of her work, fearing that the specialized medicine she was developing might only benefit a wealthy, narrow sliver of the global population, while millions suffered from preventable diseases.

This realization prompted a pivot toward public health. She began researching microfluidic devices for HIV detection tailored for low-resource environments. However, even here, she felt that the underlying socioeconomic drivers of these resource constraints remained unaddressed, leading her to study economics.

Mentorship and the Power of Persistence

Flanigan’s ascent was catalyzed by a series of mentors who saw potential in her that she hadn’t yet recognized in herself. Steven Wright, a professor of law and creative writing at UW-Madison, became an informal but vital guide. Working with him at the Wisconsin Innocence Project, Flanigan found the confidence to aim for elite institutions like Harvard and MIT.

Similarly, the persistence of UW-Madison scholarship administrators Debbie Berger and Julie Stubbs was transformative. Flanigan recalls repeatedly deleting their emails regarding the Goldwater Scholarship, dismissing them as "spam." Their refusal to let her stay in the shadows forced her to apply, fundamentally expanding the scope of what she believed she could achieve.

The Mathematical Awakening at Princeton

Following graduation, Flanigan served as a predoctoral research assistant in economics at Princeton University. It was here that Professor Evita Nestoridi invited her to audit a real analysis course. This was her first true exposure to the beauty of formal proofs. The experience was transformative; it provided the technical language she needed to articulate her ideas. With Nestoridi’s encouragement, Flanigan abandoned her doubts about her mathematical abilities and applied to computer science PhD programs.

Supporting Data: Algorithmic Fairness in Governance

Flanigan’s doctoral work at Carnegie Mellon University focused on the intersection of social choice theory and democratic decision-making. Her research seeks to solve a fundamental problem: how do we ensure that collective decisions are truly representative?

The core of her work involves "citizens’ assemblies"—groups of people selected to deliberate on complex policy issues. In traditional settings, these assemblies suffer from self-selection bias. If a government organizes an assembly on Artificial Intelligence, the participants are likely to be younger, tech-savvy, and more highly educated, leaving the voices of the broader, potentially more affected, public out of the conversation.

The Mechanics of Representation

Flanigan has developed advanced algorithms to select assembly participants that balance representational accuracy with procedural fairness. Her tools manage a complex set of trade-offs, including:

• Equality of Participation: Ensuring every citizen has a statistically fair chance to be included.
• Manipulation Resistance: Protecting the selection process from special interest groups or bad actors who might try to "game" the results.
• Transparency: Making the selection process legible and defensible to the public.

Her research is currently deployed on panelot.org, an open-access platform that allows practitioners to input their priorities and constraints. The site serves as a bridge, translating the high-level needs of democratic organizers into the precise language of algorithmic optimization.

Implications for the Future of Governance

Flanigan’s appointment at MIT marks a significant moment for the intersection of computer science and political science. Her work suggests that the "crisis of democracy" is partly a crisis of infrastructure. If we want citizens to trust their governments, the processes by which decisions are made must be perceived as legitimate.

"If any political solution is going to be viable," Flanigan notes, "the public needs to feel that it was arrived at via a legitimate political process."

Her current research is moving beyond citizens’ assemblies to explore how we solicit public input on complex, multifaceted policy decisions. She is investigating how the phrasing of questions and the structure of preference elicitation can influence the final conclusions of a public body. By applying computational rigor to these questions, she is helping to build a new toolkit for governance that is more direct, transparent, and representative.

An Environment of Belonging

For Flanigan, MIT is more than just a prestigious employer; it is an environment that validates her multidisciplinary identity. Throughout her career, she often felt like an outsider—the "non-traditional" researcher who didn’t fit into a single box.

"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.

As she continues her research in the fall of 2025 and beyond, Flanigan serves as a model for a new generation of scholars. She demonstrates that the most complex challenges of our time—inequality, the erosion of trust in institutions, and the digital divide—cannot be solved by programmers or politicians alone. They require the fusion of both. By chasing the problems that feel "most pressing and inspiring," Bailey Flanigan is not just studying democracy; she is actively upgrading its operating system for a more complex world.