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.
Authors
- Joel Miller (ORCID: https://orcid.org/0009-0003-3817-9042)
- Chris Kanich (ORCID: https://orcid.org/0000-0002-3836-2168)
- E. Glen Weyl (ORCID: https://orcid.org/0000-0001-8824-6977)
Institutions
- Microsoft (United States) (US)
- University of Illinois Chicago (US)
- Microsoft Research (United Kingdom) (GB)
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