The Rise of Big Data Policing

November 15, 2017

In a time where police departments are increasingly under scrutiny for their tactics and facing serious allegations of racial bias in policing, departments are turning to "data-driven policing": the use of data and algorithms to determine when, where, how, and who to police. Indeed, Ferguson's (law, David A. Clarke Sch. of Law, Univ. of the District of Columbia; Why Jury Duty Matters) timely book does describe how technology can help improve police accountability. It also describes how, far from being neutral and objective, these technologies can serve to mask and even amplify bias and discrimination. Ferguson explains with great clarity how the prejudices and inequities in the "real world" end up reflected in the algorithms behind these predictive policing technologies. His writing is clear and engaging without sacrificing depth and detail. VERDICT Important and relevant, this book will be indispensable to criminal justice researchers and others interested in the practice of policing. General readers will also find it valuable for the critical civil rights and constitutional issues it raises.--Rachel Bridgewater, Portland Community Coll. Lib., OR

Copyright 2017 Library Journal, LLC Used with permission.

Starred review from August 1, 2017
A survey of predictive policing: how data makes it possible, its benefits and pitfalls, and what it may portend for American law enforcement and race relations.In an important book that goes to the heart of issues at the forefront of contemporary life, Ferguson (Law/Univ. of the District of Columbia; Why Jury Duty Matters: A Citizen's Guide to Constitutional Action, 2012) examines how police departments are now using supposedly "objective" data-driven surveillance technologies to work more effectively in a budget-cutting era and to avoid claims of racial bias. In this engaging, well-written narrative, based on studies and a deep understanding of policing, the author describes the growing police use of shared data (the National Crime Information Center database is "reportedly accessed 12 million times a day by authorities"), its effects on how and where police work, and its usefulness in predicting future criminals (just as Amazon uses data to identify repeat shoppers). Some uses of data are surprising, as in Chicago, New Orleans, and other cities, where police maintain "heat lists" of individuals likely to be involved in crimes and then write to and visit the listed suspects, warning them to avoid criminal activity. The data used in predictive policing is prone to bias and error, warns Ferguson, and it includes "black data," which is opaque, hidden in complex algorithms deemed proprietary by software vendors who work with police. Using erroneous data can lead to "aggressive police presence, surveillance, and perceived harassment" in poor communities of color. In fact, "big data policing reifies many of the systemic inequalities of traditional policing," writes the author, who is candid in his assessment of the role of implicit bias in law enforcement. He concludes with questions he urges police departments to ask about racial bias, error, and accountability in data-driven policing. Essential reading for anyone who wants to understand how technology is changing American policing.

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