Police Conflict Over the Use of Big Data

• In Event: 213 - Regular Session. Deviance and Social Control

Abstract

In this paper, I draw on fieldwork within a large urban police department to understand how the police themselves respond to the adoption of “big data” analytics. Despite media and social scientific portrayals of law enforcement as an organization with a voracious appetite for data-driven surveillance, I suggest the adoption of advanced analytics and new surveillant technologies is actually frequently contested within law enforcement, ultimately serving to entrench old divisions and create new distinctions within the department. I find levels of enthusiasm for big data varies both by position in the organizational hierarchy and by function in the department. I distinguish between six related, but analytically distinct grievances raised by those opposed to the adoption of data-driven practices within the department. First, police object to increases in their own surveillance associated with new technologies. Second, the emphasis placed on data-driven practices devalues officers’ local, experiential knowledge in favor of abstracted data. Third, the inscrutability of algorithms impedes officer buy-in to predictive analytics. Fourth, the adoption of big data analytics exacerbates friction between pre-existing divisions in the Department including local authorities/federal agencies, sworn officers/civilian employees, managers/street-level workers, and rookies/veterans. Fifth, interviewees in law enforcement raised privacy concerns about large-scale changes in surveillance practices. Finally, individuals raised questions about the efficacy or unanticipated consequences of specific analytic technologies. This research sheds light on new dimensions of surveillance in the age of big data and changes the way we understand data-driven policing, quantification, organizational practice, and inequality.

Author

• Sarah Brayne, University of Texas at Austin