Datafied and Divided: Techno–Dimensions of Inequality in American Cities

Abstract

This essay interrogates the effects that “big data” have on constructing space and subjects that reproduce inequality in the urban landscape. By comparing two different data–driven projects within the same city, data collection and collation is seen to contribute to existing divides along racial and class lines. As urban sociologists seek to capitalize on the vast quantity of data generated by automated devices and networked computation, they must first interrogate and deconstruct the hidden protocols and ideologies that define algorithmic classification systems. Predictive policing and “smart city” economic development operate to construct subjects tied to spatial markers encoded in databases. Therefore, technological structures must be theorized alongside racial and class structures as entrenching historical inequities.