The Emergence of Big Data Policing
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The past decade has seen both the proliferation of surveillance in everyday life and the rise of “big data.” Analysis of this big data has expanded into finance, health, social science, sports, marketing, security, and criminal justice. Focusing on the Los Angeles Police Department (LAPD), this brief explores whether and how adopting big data analytics transforms police surveillance practices. Big data analytics have the potential to reduce bias, increase efficiency, and improve prediction accuracy. However, they also have the potential—through predictive algorithms and other means—to reinforce bias and deepen existing patterns of inequality. Being at the forefront of data analytics makes the LAPD an important site for this research. Therefore, its practices may forecast broader trends that could play out in other law enforcement agencies in the coming years. This brief is based on fieldwork conducted between March 2013 and August 2015 with the LAPD, the Los Angeles County Sherriff’s Department, other regional and federal agencies, as well as at surveillance industry conferences and with individuals working at technology firms that design analytic platforms used by the LAPD.1 Using interviews with 75 police officers, detectives, civilian employees, surveillance technology employees, and others, in addition to observations of data analysts, ride-alongs in police cars, and archival research of surveillance industry literature, this research demonstrates that, in some cases, the adoption of big data analytics is associated with mere amplifications in prior practices, but in others, it is associated with fundamental transformations in surveillance activities.