Updated

Updated · MIT News · Jul 17

Bailey Flanigan Deploys Citizen-Assembly Algorithms on panelot.org, Extending MIT Research Into Public Use

Updated

Updated · MIT News · Jul 17

Bailey Flanigan Deploys Citizen-Assembly Algorithms on panelot.org, Extending MIT Research Into Public Use

Q: From HIV tests to democratic tools, what core principle connects Bailey Flanigan's seemingly disparate research interests?

The through line in Bailey Flanigan’s work is using rigorous technical tools to solve high-impact public problems in ways that are fair, accessible, and legitimate for the people affected. That principle links her early work on low-cost HIV diagnostics and her current work on democratic decision-making. In public health, she moved from cancer therapeutics to portable HIV detection for low-resource settings because she wanted broader social impact and better access where resources were scarce. In democracy research, she applies algorithms to citizens’ assemblies with the same concern: designing systems that work under real-world constraints while giving people an equal and meaningful chance to be represented. Across both areas, Flanigan is focused less on technology for its own sake than on the rules and structures that determine who benefits, who gets included, and whether outcomes are trusted. Her sortition tools aim to balance representation, resist manipulation, and increase transparency; her comments on AI governance similarly stress the importance of deciding who is entitled to govern systems in the first place, not just how efficiently they operate. In that sense, the common principle is social equity through careful system design: building mathematically grounded, practical tools that expand access, protect fairness, and strengthen the legitimacy of collective decisions.

1 articles · Updated · MIT News · Jul 17

Flanigan’s participant-selection algorithms are now live on panelot.org, an open-access site that helps organizers build citizen assemblies from volunteer pools.
The tools address a core problem in assemblies: self-selected volunteers can skew younger, more educated, or more tech-focused than the broader public, weakening representation.
panelot.org guides practitioners through technical trade-offs—such as equal participation chances, resistance to manipulation, and transparency—then optimizes selections based on their priorities.
Flanigan, who joined MIT in fall 2025 with a joint appointment in political science and EECS, focuses her research on computational methods that make democratic participation more legitimate and scalable.
Her broader work also examines how to gather public input on complex decisions and how question design can shape the preferences policymakers infer.

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MIT News3h ago

MIT's Bailey Flanigan Deploys Citizen Assembly Algorithms on panelot.org

Could randomly selected citizen panels, empowered by AI, ultimately threaten the role of experienced, elected officials in government?

Can algorithms designed for fairness overcome public distrust in both politics and the very technology meant to fix it?

From HIV tests to democratic tools, what core principle connects Bailey Flanigan's seemingly disparate research interests?

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1 total

MIT News3h ago

MIT's Bailey Flanigan Deploys Citizen Assembly Algorithms on panelot.org

Bailey Flanigan Deploys Citizen-Assembly Algorithms on panelot.org, Extending MIT Research Into Public Use

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