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 date: 01 September 2019
• DOI: http://doi.org/10.1111/puar.13096
• Date: 01 September 2019

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,

2015).

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

victims?

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.

E-mail: ian.adams@utah.edu