Voting Biases in Decentralized Autonomous Organization (DAO) Governance
2026-07-10 • Computers and Society
Computers and SocietyHuman-Computer Interaction
AI summaryⓘ
The authors studied how votes are distributed within Decentralized Autonomous Organizations (DAOs) at the level of individual choices in proposals. They found that voting power tends to concentrate on choices made by the proposal's author, approval-type choices, and choices listed first. Specifically, author-selected choices receive the most attention, increasing voting power by nearly 59%. The study suggests that factors like the order of choices and signals from authors influence voting beyond the actual proposal content, highlighting the importance of interface design in DAO governance.
Decentralized Autonomous OrganizationsDAO votingtoken-weighted votingvoting power concentrationproposal choicesapproval votingposition effectsgovernance designsocial signalsinstitutional design
Authors
Stefano Balietti, Pietro Saggese, Markus Strohmaier
Abstract
Decentralized Autonomous Organizations (DAOs) use token-weighted voting to allocate resources, set protocol rules, and legitimate collective decisions. Yet, support in DAO voting is strikingly concentrated. What happens inside the ballot that produces this concentration? We study DAOs' governance at the proposal-choice level, linking each choice's voting-power share to three observable features: whether it expresses an approval-oriented stance, where it appears in the choice list, and whether it is selected by the proposal author. We find that (i) author-selected choices show the strongest and most robust association with voting-power share, with a 58.8% increase relative to non-author choices; (ii) approval-oriented choices retain a positive but slightly less consistent advantage (27.1%); and (iii) first-listed choices also attract systematically higher shares, consistent with position and order effects (7.7%). Results are robust across several specifications, which include subtracting an author's own voting power from computations. We use bias descriptively, to denote systematic associations rather than proven causal distortion. The results shift attention from proposal outcomes alone to the interface and social signals through which choices are presented. In DAO governance, ordering, author signals, and vote visibility should be treated as institutional design choices, not neutral implementation details.