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

Digital democracy and 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, inclusive and legitimate collective decision-making processes for citizens' assemblies, participatory budgeting and elections. So far, a systematic human experimentation with different voting methods is cumbersome and costly. This paper introduces VoteLab, an open-source and well-documented platform for modular and adaptive design of voting experiments. It supports a visual and interactive building of reusable campaigns with 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 have been used in an online lab experiment to study the consistency of voting outcomes. This demonstrates the Votelab capability to support rigorous experimentation of complex voting scenarios.