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Hauptverfasser: Miller, Joel, Weyl, E. Glen, Kanich, Chris
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2509.18343
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author Miller, Joel
Weyl, E. Glen
Kanich, Chris
author_facet Miller, Joel
Weyl, E. Glen
Kanich, Chris
contents We discuss an algorithmic intervention aimed at increasing equity and economic efficiency at a crowdfunding platform that gives cash subsidies to grantees. Through a blend of technical and qualitative methods, we show that the previous algorithm used by the platform -- Quadratic Funding (QF) -- suffered problems because its design was rooted in a model of individuals as isolated and selfish. We present an alternative algorithm -- Connection-Oriented Quadratic Funding (CO-QF) -- rooted in a theory of plurality and prosocial utilities, and show that it qualitatively and quantitatively performs better than QF. CO-QF has achieved an 89% adoption rate at the platform and has distributed over $4 Million to date. In simulations we show that it provides better social welfare than QF. While our design for CO-QF was responsive to the needs of a specific community, we also extrapolate out of this context to show that CO-QF is a potentially helpful tool for general-purpose public decision making.
format Preprint
id arxiv_https___arxiv_org_abs_2509_18343
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Fair Decisions through Plurality: Results from a Crowdfunding Platform
Miller, Joel
Weyl, E. Glen
Kanich, Chris
Computer Science and Game Theory
Computers and Society
Human-Computer Interaction
We discuss an algorithmic intervention aimed at increasing equity and economic efficiency at a crowdfunding platform that gives cash subsidies to grantees. Through a blend of technical and qualitative methods, we show that the previous algorithm used by the platform -- Quadratic Funding (QF) -- suffered problems because its design was rooted in a model of individuals as isolated and selfish. We present an alternative algorithm -- Connection-Oriented Quadratic Funding (CO-QF) -- rooted in a theory of plurality and prosocial utilities, and show that it qualitatively and quantitatively performs better than QF. CO-QF has achieved an 89% adoption rate at the platform and has distributed over $4 Million to date. In simulations we show that it provides better social welfare than QF. While our design for CO-QF was responsive to the needs of a specific community, we also extrapolate out of this context to show that CO-QF is a potentially helpful tool for general-purpose public decision making.
title Fair Decisions through Plurality: Results from a Crowdfunding Platform
topic Computer Science and Game Theory
Computers and Society
Human-Computer Interaction
url https://arxiv.org/abs/2509.18343