1932

Abstract

Law and social science scholars have long elucidated ways of governing built around state governance of populations and subjects. Yet many are now grappling with the growing prevalence of practices of governance that depart, to varying degrees, from received models. The profusion of digital data, and the deployment of machine learning in its analysis, are redirecting states’ and international organizations’ attention away from the governance of populations as such and toward the amassing, analysis, and mobilization of hybrid data repositories and real-time data flows for governance. Much of this work does not depend on state data sources or on conventional statistical models. The subjectivities nurtured by these techniques of governance are frequently not those of choosing individuals. Digital objects and mediators are increasingly prevalent at all scales. This article surveys how scholars are beginning to understand the nascent political technologies associated with this shift toward governance by data.

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2021-10-13
2024-04-16
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