Information Processing in Participatory Governance

Abstract

Participatory governance institutions often aim to yield information useful to policymakers, whether about public preferences, problems, solutions, or perspectives. But how can large numbers of public contributions be processed into interpretable and actionable information outputs? As theorists and practitioners increasingly call for participatory governance to operate at larger scales, often enabled by new technologies, this challenge only becomes more important. Building on research across political theory, public administration, and political science, this paper develops and illustrates three claims: First, that information processing plays an essential and under-appreciated role in participatory governance. Second, that there are distinct types of information processing, best characterised by two dimensions of specificity and novelty. And third, that these types differ in their costs, in the extent to which they can be delegated to non-experts or to automation, and in their potential consequences for unrepresentative participation. Better recognising these differences will help both researchers and practitioners better understand the potential and the limitations of participatory governance institutions in different settings and with different goals.