Rongchai Wang
Nov 01, 2024 18:21
Bailey Flanigan from Harvard introduces revolutionary algorithms for honest 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 boost the equity and robustness of sortition, in accordance with a16z crypto. Sortition, the method of choosing representatives by lottery, has seen renewed curiosity for its potential purposes in residents’ assemblies and blockchain governance.
Advancing Sortition Beliefs
Flanigan’s work focuses on optimizing the three core beliefs of sortition: proportional illustration, equal alternative for participation, and resistance to manipulation. These beliefs are difficult to attain in fashionable purposes the place participation can’t be mandated, resulting in biases in voluntary opt-ins.
Her algorithms, developed with enter from nonprofit organizations using residents’ assemblies, implement approximate proportional illustration as a major constraint. They then intention to optimize the remaining beliefs of equal participation and manipulation resistance by superior mathematical formalizations utilizing optimization, algorithms, and recreation concept.
Actual-World Purposes and Public Entry
Flanigan’s algorithms have been efficiently deployed in numerous high-profile residents’ assemblies, offering a strong framework for decision-making processes that intention to be extra inclusive and honest. These instruments are made publicly out there by way of Panelot.org, providing sources for practitioners looking for to implement honest sortition strategies.
About Bailey Flanigan
Bailey Flanigan is a postdoctoral fellow on the Harvard Ash Middle for Democratic Governance and Innovation. She holds a PhD in laptop science from Carnegie Mellon College, the place she was suggested by Ariel Procaccia. Beginning in Fall 2025, Flanigan will be part of MIT as an assistant professor in political science and laptop science.
a16z Crypto Analysis
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