Harvard's Bailey Flanigan Develops Advanced Sortition Algorithms
Rongchai Wang Nov 01, 2024 18:21
Bailey Flanigan from Harvard introduces innovative algorithms for fair and manipulation-resistant sortition, advancing citizen assemblies and blockchain decision-making, as reported by a16z crypto.
Harvard's Bailey Flanigan has unveiled groundbreaking algorithms designed to enhance the fairness and robustness of sortition, according to a16z crypto. Sortition, the process of selecting representatives through lottery, has seen renewed interest for its potential applications in citizens' assemblies and blockchain governance.
Advancing Sortition Ideals
Flanigan's work focuses on optimizing the three core ideals of sortition: proportional representation, equal opportunity for participation, and resistance to manipulation. These ideals are challenging to achieve in modern applications where participation cannot be mandated, leading to biases in voluntary opt-ins.
Her algorithms, developed with input from nonprofit organizations utilizing citizens' assemblies, enforce approximate proportional representation as a primary constraint. They then aim to optimize the remaining ideals of equal participation and manipulation resistance through advanced mathematical formalizations using optimization, algorithms, and game theory.
Real-World Applications and Public Access
Flanigan's algorithms have been successfully deployed in various high-profile citizens’ assemblies, providing a robust framework for decision-making processes that aim to be more inclusive and fair. These tools are made publicly available via Panelot.org, offering resources for practitioners seeking to implement fair sortition methods.
About Bailey Flanigan
Bailey Flanigan is a postdoctoral fellow at the Harvard Ash Center for Democratic Governance and Innovation. She holds a PhD in computer science from Carnegie Mellon University, where she was advised by Ariel Procaccia. Starting in Fall 2025, Flanigan will join MIT as an assistant professor in political science and computer science.
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