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The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement

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by Andrew Guthrie Ferguson

New York University Press

11/15/2019, paperback

SKU: 9781479869978

 

Winner, 2018 Law & Legal Studies PROSE Award

The consequences of big data and algorithm-driven policing and its impact on law enforcement.

In a high-tech command center in downtown Los Angeles, a digital map lights up with 911 calls, television monitors track breaking news stories, surveillance cameras sweep the streets, and rows of networked computers link analysts and police officers to a wealth of law enforcement intelligence.

This is just a glimpse into a future where software predicts future crimes, algorithms generate virtual "most-wanted" lists, and databanks collect personal and biometric information. The Rise of Big Data Policing introduces the cutting-edge technology that is changing how the police do their jobs and shows why it is more important than ever that citizens understand the far-reaching consequences of big data surveillance as a law enforcement tool.

Andrew Guthrie Ferguson reveals how these new technologies --viewed as race-neutral and objective--have been eagerly adopted by police departments hoping to distance themselves from claims of racial bias and unconstitutional practices. After a series of high-profile police shootings and federal investigations into systemic police misconduct, and in an era of law enforcement budget cutbacks, data-driven policing has been billed as a way to "turn the page" on racial bias.

But behind the data are real people, and difficult questions remain about racial discrimination and the potential to distort constitutional protections.

In this first book on big data policing, Ferguson offers an examination of how new technologies will alter the who, where, when and how we police. These new technologies also offer data-driven methods to improve police accountability and to remedy the underlying socio-economic risk factors that encourage crime.

The Rise of Big Data Policing is a must read for anyone concerned with how technology will revolutionize law enforcement and its potential threat to the security, privacy, and constitutional rights of citizens.

Reviews:

"The case Ferguson makes is inherently interesting and increasingly urgent."--Los Angeles Review of Books

"A valuable foundation for understanding how prediction has suffused policing, in much the same way it has suffused the rest of society. Ferguson's criticisms are cogent, but more importantly he communicates clearly a broad factual picture of the situation as it stands today."--The Washington Free Beacon

"Ferguson has an incredible command of the many subjects that fall under the 'big data' umbrella, and his writing is at its best when social, cultural, and technological dynamics coalesce into one story. The book is particularly strong when Ferguson takes on how classism and racism shape smart policing datasets, which epitomize how 'big data' policing is held back by the many limitations of larger legal structures but is presented as the solution to that very problem."--Gizmodo

"In an important book that goes to the heart of issues at the forefront of contemporary life, Ferguson 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, [Ferguson] describes the growing police use of shared data, its effects on how and where police work, and its usefulness in predicting future criminals . . .Essential reading for anyone who wants to understand how technology is changing American policing."--Starred Kirkus Review

Author:

Andrew Guthrie Ferguson is Professor of Law at the University of the District of Columbia's David A. Clarke School of Law. Professor Ferguson is a national expert on predictive policing, big data surveillance, and the Fourth Amendment. He is the author of Why Jury Duty Matters (NYU Press, 2012).