Collective Intelligence for Democracy: Empowering Minorities and Everyone in Participatory Budgeting

Abstract

Currently, there are increasing attempts to better involve citizens in the political decision processes. A successful approach in that regard has been participatory budgeting (PB), which allows citizens to propose projects and then to decide how to distribute a given budget over them. In the meanwhile, literature on collective intelligence (CI) has shown that groups of people can solve complex problems and even outperform experts. Thus by combining CI and PB it should be possible for citizens to identify problems and create their own solutions. In this article, we first explore how a system combining CI and PB produces solutions that strongly penalize minorities, as solution’s quality depends on group’s size. Then, we introduce an approach that can overcome the issue. Indeed, by using a common knowledge base for the storage of partial solutions, the quality of solutions of minorities can benefit from the work of the majority, thereby promoting fairness. Interestingly, this approach also benefits majorities, as the quality of their solutions is further improved by the work of the minorities, thus, reaching better solutions for everyone. This stresses the potential and importance of an open innovation approach, which is committed to information sharing.

Keywords: participatory budgeting, collective intelligence, agent-based modelling