Balancing Power in Decentralized Governance: Quadratic Voting and Information Aggregation

Abstract

While decentralized platforms offer transformative potential, their success relies on effective governance models for aggregating user information. Most platforms currently use Linear Voting mechanisms (LV) like stake-weighted voting, which are not always optimal. One promising alternative is Quadratic Voting (QV), where the cost of acquiring voting power is convex rather than linear. QV restores optimality when users are certain about the quality of the proposals they are voting on. But what if they aren't? We show that quality uncertainty can not only break optimality but can also make QV underperform LV. Intuitively, this is because cost convexity can disincentivize better-informed voters from conveying their private information. This effect, however, fades as voter numbers increase. In fact, both mechanisms become optimal asymptotically, highlighting the importance of managing voter participation in decentralized governance.

Keywords: decentralized governance, blockchain, dApps, Information Aggregation, crowdsourcing, Voting