Smart urbanism and data-driven governance bring together the state and market actors in new and significant ways, ways that raise eminently political questions. Yet at the same time a massive effort in de-politicization is being pursued under the shield of technical progress, better opportunities, and expertise. This paper works to contribute to the politicization of the 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, this paper focuses on the case of smart urbanism and its associated process of data-driven governance in China, focusing specifically on 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 risk-class inequalities. The intention of this paper then is to propose risk-class analysis as a toolbox that can pose new questions in the search for what type of incipient futures there are for smart urbanism through a detailed case study.
About the Speaker:
Prof. Alan Smart (PhD Anthropology, U of Toronto, 1986) is a Professor in the Department of Anthropology and Archaeology, University of Calgary. His research interests include Hong Kong, China, Canada, urban studies, housing, smart cities, informality, globalization, borders, and political economy. He has published “Making Room: Squatter Clearance in Hong Kong”(HKU Press 1992), “The Shek Kip Mei Myth: Squatters, Fires and Colonial Rule, 1950-1963” (HKU Press 2006), and “Posthumanism: Anthropological Insights” (U Toronto Press, 2017), as well as numerous journal articles and book chapters.
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