TOWARDS CIVIC PARTICIPATION IN THE DATAFIED SOCIETY: CAN CITIZEN ASSEMBLIES DEMOCRATIZE ALGORITHMIC GOVERNANCE?

Resumen

Citizens are increasingly assessed, profiled, categorized and scored according to data analytics, their future behavior is predicted, and services are allocated accordingly. State-citizen relations become quasi-automated and dependent on algorithmic decision-making, yet (largely) without people’s knowledge and without avenues to meaningfully engage and intervene. This raises significant challenges for democratic processes and active citizenship. How do we participate as citizens in a society in which we are constantly rated and categorized in ways that we do not understand? How do we affect the development and management of the very data systems that increasingly organize society? How do we develop new democratic practices to ensure participation and accountability? This paper explores emerging opportunities for participatory and deliberative forms of governing the implementation of data analytics, particularly in the public sector. It investigates how models of engagement and deliberation – from citizen juries and citizen assemblies to deliberative polls and public dialogues – can advance civic participation in the roll-out and implementation of data analytics and thus democratize algorithmic governance. It assesses the suitability of these practices by evaluating, e.g., the level of participation, policy impcts, and institutional challenges and obstacles, bringing together insights from the fields of critical data studies and democratic innovation. The paper draws on findings from 15 expert interviews conducted between 2019 and 2021 with members of government and civil society as well as a fact-finding workshop that form part of a two-year project investigating the practices, structures and constraints of citizen engagement with datafied governance.