Designing Digital Voting Systems for Citizens: Achieving Fairness and Legitimacy in Participatory Budgeting

Author:

Yang Joshua C.1ORCID,Hausladen Carina I.1ORCID,Peters Dominik2ORCID,Pournaras Evangelos3ORCID,Hnggli Fricker Regula4ORCID,Helbing Dirk1ORCID

Affiliation:

1. Computational Social Science, ETH Zurich, Zürich, Switzerland

2. CNRS, LAMSADE, Université Paris Dauphine - PSL, Paris, France

3. University of Leeds, Leeds, United Kingdom of Great Britain and Northern Ireland

4. University of Fribourg, Fribourg, Switzerland

Abstract

Participatory Budgeting (PB) has evolved into a key democratic instrument for resource allocation in cities. Enabled by digital platforms, cities now have the opportunity to let citizens directly propose and vote on urban projects, using different voting input and aggregation rules. However, the choices cities make in terms of the rules of their PB have often not been informed by academic studies on voter behaviour and preferences. Therefore, this work presents the results of behavioural experiments where participants were asked to vote in a fictional PB setting. We identified approaches to designing PB voting that minimise cognitive load and enhance the perceived fairness and legitimacy of the digital process from the citizens’ perspective. In our study, participants preferred voting input formats that are more expressive (like rankings and distributing points) over simpler formats (like approval voting). Participants also indicated a desire for the budget to be fairly distributed across city districts and project categories. Participants found the Method of Equal Shares voting rule to be fairer than the conventional Greedy voting rule. These findings offer actionable insights for digital governance, contributing to the development of fairer and more transparent digital systems and collective decision-making processes for citizens.

Funder

Swiss National Science Foundation (SNSF) as part of the National Research Programme NRP 77 Digital Transformation

UKRI Future Leaders Fellowship

Publisher

Association for Computing Machinery (ACM)

Reference55 articles.

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2. Haris Aziz, Barton E. Lee, and Nimrod Talmon. 2018. Proportionally representative participatory budgeting: Axioms and algorithms. In Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 23–31. https://www.ifaamas.org/Proceedings/aamas2018/pdfs/p23.pdf

3. Participatory Budgeting: Models and Approaches

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