Utilitarian Distortion Under Probabilistic Voting
Hamidreza Alipour, Mohak Goyal
TL;DR
This work studies utilitarian distortion under probabilistic voting, modeling voter rankings via the Plackett-Luce mechanism with inverse temperature $β$. It shows that normatively appealing rules like Copeland and Borda achieve distortion bounds independent of the number of candidates, specifically at most $β\frac{1+e^{-β}}{1-e^{-β}}$, with near-tight lower bounds $\ge (1-ε)β$ for Copeland and $\ge (1-o(1))β$ for Borda. In contrast, top-choice based rules such as Plurality, PluralityVeto, and RandomDictator incur distortion that grows with $m$ or exponentially in $β$, and a universal lower bound of $(\frac{5}{8}-ε)β$ is shown for all deterministic finite-precision tournament rules. The results align distortion notions with normative intuitions once probabilistic noise in rankings is accounted for, and reveal a nuanced trade-off between information usage and welfare guarantees in probabilistic voting. The findings have implications for AI alignment and preference aggregation, suggesting that incorporating full pairwise information via tournament-based rules yields robust welfare performance under realistic noisy voting dynamics.
Abstract
The utilitarian distortion framework evaluates voting rules by their worst-case efficiency loss when voters have cardinal utilities but express only ordinal rankings. Under the classical model, a longstanding tension exists: Plurality, which suffers from the spoiler effect, achieves optimal $Θ(m^2)$ distortion among deterministic rules, while normatively superior rules like Copeland and Borda have unbounded distortion. We resolve this tension under probabilistic voting with the Plackett-Luce model, where rankings are noisy reflections of utilities governed by an inverse temperature parameter $β$. Copeland and Borda both achieve at most $β\frac{1+e^{-β}}{1-e^{-β}}$ distortion, independent of the number of candidates $m$, and within a factor of 2 of the lower bound for randomized rules satisfying the probabilistic Condorcet loser criterion known from prior work. This improves upon the prior $O(β^2)$ bound for Borda. These upper bounds are nearly tight: prior work establishes a $(1-o(1))β$ lower bound for Borda, and we prove a $(1-ε)β$ lower bound for Copeland for any constant $ε>0$. In contrast, rules that rely only on top-choice information fare worse: Plurality has distortion $Ω(\min(e^β, m))$ and Random Dictator has distortion $Θ(m)$. Additional `veto' information is also insufficient to remove the dependence on $m$; Plurality Veto and Pruned Plurality Veto have distortion $Ω(β\ln m)$. We also prove a lower bound of $(\frac{5}{8}-ε)β$ (for any constant $ε>0$) for all deterministic finite-precision tournament-based rules, a class that includes Copeland and any rule based on pairwise comparison margins rounded to fixed precision. Our results show that the distortion framework aligns with normative intuitions once the probabilistic nature of real-world voting is taken into account.