Data-driven governance, smart urbanism and risk-class inequalities: Security and social credit in China

Abstract

This article contributes to the politicisation of smart urbanism and data-driven governance by making visible some of the potential inequalities emerging from these transitions through a provisional risk-class analysis. To pursue this analysis, it focuses on the case of smart urbanism and its associated process of data-driven governance in China. It looks specifically at the manner in which Chinese smart urbanism, in terms of its security measures, including widespread use of facial recognition and the roll-out of social credit scoring, is affecting inequalities. This article proposes risk-class analysis as a toolbox that can pose new questions in the search for what types of potential risks and inequalities emerge from the smart urbanism and data-driven governance being rolled out in the Chinese context.