arXiv subjects

Zoi Terzopoulou

Publications and source records attributed to Zoi Terzopoulou.

6 recordsLinked to original sources

arXiv2026

Anchor-proofness in Voting with Ranked Ballots

When voters evaluate alternatives sequentially, an anchoring bias makes their ballots depend on the order in which alternatives are presented. For approval ballots, no non-constant voting rule is robust to this dependence. We show that ranked ballots change the picture sharply: a rank-based rule is robust to the presentation order if and only if it is tops-only. Robustness to anchoring is thus available, but only at the price of ignoring everything a voter reports beyond her favourite alternative.

econ.TH↗

arXiv2026

Anchor-proofness in Voting

We study how order-dependent individual evaluations affect collective decision-making. We consider a voting environment in which voters have intrinsic preference rankings and acceptability thresholds, but form approval ballots sequentially as alternatives are presented by a social planner. Because alternatives encountered early on serve as anchors, approval ballots may depend on the presentation order even when intrinsic preferences remain unchanged. We ask when approval-based voting rules are robust to this order dependence, a property we call anchor-proofness. We first show that no non-constant approval-based voting rule is anchor-proof. We then study weaker forms of robustness and characterize anchor-proof profiles for the classical approval voting rule and the nomination rule. Finally, we examine the strategic role of the social planner under different information structures. We show that, while a planner with no information about voters' preferences cannot safely manipulate any rule satisfying weak and total unanimity, even limited information about voters' acceptability or plurality assessments can restore manipulation. Overall, we highlight presentation order as an important design feature of collective decision-procedures when voters are subject to anchoring.

econ.TH↗

arXiv2025

Learning How to Vote with Principles: Axiomatic Insights Into the Collective Decisions of Neural Networks

Can neural networks be applied in voting theory, while satisfying the need for transparency in collective decisions? We propose axiomatic deep voting: a framework to build and evaluate neural networks that aggregate preferences, using the well-established axiomatic method of voting theory. Our findings are: (1) Neural networks, despite being highly accurate, often fail to align with the core axioms of voting rules, revealing a disconnect between mimicking outcomes and reasoning. (2) Training with axiom-specific data does not enhance alignment with those axioms. (3) By solely optimizing axiom satisfaction, neural networks can synthesize new voting rules that often surpass and substantially differ from existing ones. This offers insights for both fields: For AI, important concepts like bias and value-alignment are studied in a mathematically rigorous way; for voting theory, new areas of the space of voting rules are explored.

cs.AI↗

arXiv2024

Enabling the Digital Democratic Revival: A Research Program for Digital Democracy

This white paper outlines a long-term scientific vision for the development of digital-democracy technology. We contend that if digital democracy is to meet the ambition of enabling a participatory renewal in our societies, then a comprehensive multi-methods research effort is required that could, over the years, support its development in a democratically principled, empirically and computationally informed way. The paper is co-authored by an international and interdisciplinary team of researchers and arose from the Lorentz Center Workshop on ``Algorithmic Technology for Democracy'' (Leiden, October 2022).

cs.CY↗

arXiv2022

Let's Agree to Agree: Targeting Consensus for Incomplete Preferences through Majority Dynamics

We study settings in which agents with incomplete preferences need to make a collective decision. We focus on a process of majority dynamics where issues are addressed one at a time and undecided agents follow the opinion of the majority. We assess the effects of this process on various consensus notions -- such as the Condorcet winner -- and show that in the worst case, myopic adherence to the majority damages existing consensus; yet, simulation experiments indicate that the damage is often mild. We also examine scenarios where the chair of the decision process can control the existence (or the identity) of consensus, by determining the order in which the issues are discussed.

cs.GT↗

arXiv2021

Egalitarian Judgment Aggregation

Egalitarian considerations play a central role in many areas of social choice theory. Applications of egalitarian principles range from ensuring everyone gets an equal share of a cake when deciding how to divide it, to guaranteeing balance with respect to gender or ethnicity in committee elections. Yet, the egalitarian approach has received little attention in judgment aggregation -- a powerful framework for aggregating logically interconnected issues. We make the first steps towards filling that gap. We introduce axioms capturing two classical interpretations of egalitarianism in judgment aggregation and situate these within the context of existing axioms in the pertinent framework of belief merging. We then explore the relationship between these axioms and several notions of strategyproofness from social choice theory at large. Finally, a novel egalitarian judgment aggregation rule stems from our analysis; we present complexity results concerning both outcome determination and strategic manipulation for that rule.

cs.AI↗