Andrew G. Ferguson, The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement (New York, NY: NYU Press, 2017). 272 pp. $28.00 (hardcover), ISBN: 1479892823

Published date01 September 2019
Date01 September 2019
AuthorIan T. Adams
Book Reviews 791
Public Administration Review,
Vol. 79, Iss. 5, pp. 791–793. © 2019 by
The American Society for Public Administration.
DOI: 10.1111/puar.13096.
Andrew G. Ferguson, The Rise of Big Data Policing:
Surveillance, Race, and the Future of Law Enforcement
(New York, NY: NYU Press, 2017). 272 pp. $28.00
(hardcover), ISBN: 1479892823
Between 2012 and 2018, New Orleans Mayor
Mitch Landrieu contracted with big data
analytics firm Palantir, using the company’s
predictive policing technology to address the city’s
murder rate, which was the sixth highest in the
nation. The partnership between city government
and private sector big data provides fertile ground for
the public policy questions swirling around the big
data, algorithmic bias, and the future of public service
work. On the one hand, the partnership was born
and lived in secrecy, and the powers of surveillance it
granted were out of balance with what is commonly
expected for local government. As one critic summed
up, “It’s almost as if New Orleans were contracting its
own version of the NSA to conduct 24/7 surveillance
of the lives of its people” (Winston 2018).
By other measures, the program was successful in its
aim. New Orleans used Palantir’s data and methods
to identify the top 1 percent of “violent crime drivers”
(34), as well as those most likely to be the victims of
homicide. The murder rate in New Orleans fell by
nearly 22 percent, and gang-related murders fell by
55 percent, all in a relatively short span between 2011
and 2014. The comparative murder rates during the
same period fell nationally by 4 percent, whereas the
rate for the regional South was unchanged (FBI 2012,
Big data is new technology, but some of the questions
it poses for public administration are old—how
do we craft public policy that is effective, efficient,
and equitable? However, simple questions do not
suggest simple answers. Framing the New Orleans
example with those values in mind, the rapid and
significant reduction of homicides is undoubtedly
effective, but there are reasons to suspect the big data
solution was also an equitable one. Homicides in New
Orleans disproportionately victimized black men.
An analysis of the sharp drop in homicides between
2012 and 2015 (Asher 2016, 6) shows that “Murder
was down citywide almost exclusively because of
drops in murder among African Americans.” How
should public administration scholars weigh the
policy implications of 32 fewer black men killed in
2015 compared to 2012 against the disproportionate
impact of big data policing on those who reside in
a community targeted for high-risk offenders and
Author and Intent
Andrew Guthrie Ferguson dives into the New
Orleans example, as well as numerous other U.S.
examples, in his accounting of the use of big data in
policing. The Rise of Big Data Policing is a substantial
contribution to the emerging field of surveillance
studies. It is not without limitations, but those
limitations are primarily the result of constraints that
all scholarship in this area is confronting. Because
the big data in question is held privately but proxied
through governmental use, research in this area is
notably difficult. In Ferguson’s conception, this is a
form of “black data.” The data and algorithms used
by companies such as Palantir hide behind patents
and other commercial protections and, despite
having a tremendous impact on public policy, are
not easily forced into the public (and scholarly) view
through traditional means, such as the Freedom of
Information Act (FOIA).
Ferguson intends to examine the impacts of big data
policing. He recognizes that the promise of “smarter”
policing is balanced against the “fear of totalizing
surveillance” (5) and writes that his aim “is to look
at the dangers of black data arising at this moment
in history.” Ferguson is a professor of law at the
University of the District of Columbia, but his legal
scholarship background does not limit his critique
to merely the constitutional or judicial. He uses case
examples across the United States to illustrate his aims
and speaks to two audiences with his book—scholars
interested in the nexus of technology and criminal
justice and police administrators.
For researchers interested in where to begin
researching how policing agencies are using big data,
Ian T. Adams
University of Utah
Book Reviews
Galia Cohen, Editor
Ian T. Adams is a doctoral student in
the Department of Political Science at the
University of Utah. His research interests
focus on emotional labor, policing, and
body-worn cameras. Before his academic
work, he served for over 12 years in state
and municipal law enforcement.

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