VoteLab: A Modular and Adaptive Experimentation Platform for Online Collective Decision Making

TL;DR

VoteLab is an open-source platform enabling flexible, modular online voting experiments to study various voting methods and their outcomes in digital democracy contexts.

Contribution

It introduces a novel, adaptable platform for designing and conducting online voting experiments with multiple voting methods and interactive voter engagement.

Findings

Successfully tested four voting methods on COVID-19 questions

Demonstrated VoteLab's capability for rigorous experimentation

Showed consistency of voting outcomes across methods

Abstract

Digital democracy and new forms for direct digital participation in policy making gain unprecedented momentum. This is particularly the case for preferential voting methods and decision-support systems designed to promote fairer, more inclusive and legitimate collective decision-making processes in citizens assemblies, participatory budgeting and elections. However, a systematic human experimentation with different voting methods is cumbersome and costly. This paper introduces VoteLab, an open-source and thoroughly-documented platform for modular and adaptive design of voting experiments. It supports to visually and interactively build reusable campaigns with a choice of different voting methods, while voters can easily respond to subscribed voting questions on a smartphone. A proof-of-concept with four voting methods and questions on COVID-19 in an online lab experiment have been used to study the consistency of voting outcomes. It demonstrates the capability of VoteLab to support rigorous experimentation of complex voting scenarios.