Futarchy in decentralized science: empirical and simulation evidence for outcome-based conditional markets in DeSci DAOs

Abstract

Introduction This study explores the feasibility of embedding futarchy, specifically policy-binding conditional prediction markets anchored to democratically chosen key performance indicators (KPIs) in Decentralized Science (DeSci) governance. By externalizing belief formation to speculative markets while anchoring values democratically, futarchy offers a structurally distinct alternative to existing Decentralized Autonomous Organization (DAO) governance models. Methods Through an empirical analysis of governance data from 13 DeSci DAOs, this study examines governance, participation, and cadence patterns that condition futarchic adoption. A retrospective simulation using proposals from VitaDAO assessed the degree to which historical decisions align with futarchy-preferred outcomes. Results The results indicate full directional alignment under deterministic modeling, suggesting latent compatibility between futarchy and existing DeSci governance. Discussion The analysis further outlines the design principles for implementation, emphasizing measurable KPIs and epistemic diversity. Futarchy, if carefully instantiated, may serve as a governance alternative for funding truth-tracking science through probabilistic decision making and market-based information aggregation.