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Predict and Surveil

Predict and Surveil: Data, Discretion, and the Future of Policing

Sarah Brayne
Oxford University Press
2020
224 pp.
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The U.S. police system is experiencing a reckoning. Protesters across the country (and around the world) have taken to the streets, arguing that police brutality disproportionately harms minority communities, and the current value of policing is being debated by city councils, lawmakers, and members of the news media. Into this tumultuous context enters Sarah Brayne’s book, Predict & Surveil: Data, Discretion, and the Future of Policing.

A sociologist by training, Brayne synthesizes interview data and field notes from 5 years of observation within the Los Angeles Police Department, employing a firsthand ethnographic approach to reveal how big data are currently used in tech-forward police departments in America. She chronicles both consequential and mundane interactions between officers, civilians, and data. For example, she documents officers uploading license plate numbers, field interview notes, traffic citations, and potential gang affiliations onto a private industry data platform, as well as their active surveillance of hotspots in Los Angeles predicted to be criminogenic. This fly-on-the-wall perspective captures the human aspect of a police force grappling with automated systems and machine-learning decisions in real time, juxtaposing the experiences of individual officers with institutional directives being handed down from administrators and lawmakers.

Many police departments contend that the adoption of predictive analytics can improve objectivity and transparency, reduce bias, and increase accountability. Yet Brayne’s book reveals how few of these metrics actually improve with predictive policing and exposes the scant evidence that supports the idea that it reduces crime rates. On the contrary, she insists, predictive policing raises glaring civil rights concerns and reinforces harmful racial biases. We all leave digital traces throughout our daily lives, and innocent people can be caught in the dragnet and cataloged in a digital criminal justice system, where a case can be built from benign data. Police unions, Brayne notes, often vehemently oppose the tracking of their own officers. She records incidents of officers turning off their car locator signals, for example, as well as other tactics used to thwart tech-infused managerial oversight.

Many officers view policing as an art form rather than a scientific system that can be optimized. To some, big data policing threatens their sense of police instincts and identity. “They worry that they will become nothing more than line workers and insist that their years of accumulated experiential knowledge is irreplaceable,” observes Brayne.

Brayne’s book raises timely issues relevant to mass surveillance and policing amid a growing debate about facial recognition systems, which makes their omission from this work notable. Although banned in several major American cities, these systems remain a common tool for identifying potential offenders, despite abundant evidence of dangerous inconsistencies

Predictive policing can drive societal inequalities, but Brayne suggests that reducing instances of general police contact may mitigate disparities. In addition to offering immediate recommendations for changing law enforcement in the digital age, she asserts that effective programmatic reforms are typically influenced by external social organizing and guided by communities. (The likelihood of real transformation from within the police system is small, she believes.) For judicial and policing institutions genuinely seeking reform, this book provides powerful observations and analysis that suggest how we can begin.

About the author

The reviewer is at the Government Relations Office, American Psychological Association, Washington, DC 20002, USA.