Fair Decisions through Plurality: Results from a Crowdfunding Platform

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.

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Publication Details

Published
2025-10-29
DOI
https://doi.org/10.1145/3757887.3763019
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
0.00
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article

Fair Decisions through Plurality: Results from a Crowdfunding Platform

Joel Miller, Chris Kanich, E. Glen Weyl
FinTech, Crowdfunding, Digital Finance
article

Fair Decisions through Plurality: Results from a Crowdfunding Platform

Joel Miller, Chris Kanich, E. Glen Weyl
article en

Abstract

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.

Microsoft (United States) (US), University of Illinois Chicago (US), Microsoft Research (United Kingdom) (GB)
Openalex Percentile: Top 50%
FinTech, Crowdfunding, Digital Finance
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