Data-driven policing ordinarily occurs out of the public eye, and police often try to soothe concerns by claiming that the path to ending systemic bias and racism runs through enhanced technology even while activists point out that technology is only as effective as the bias of its creators. Sociologist Sarah Brayne’s new book, Predict and Surveil: Data, Discretion, and the Future of Policing, is an in-depth examination of the marriage between data, technology, and policing that reveals just how troubling to the public that relationship should be.
Sarah Brayne is an associate professor at the University of Texas at Austin. She spent months in the field doing ridealongs with police in Los Angeles and other California cities as they used software from tech companies like Palantir and PredPol, which merge data from crime and arrest reports, automated license plate readers, rap sheets, and other sources.
Her book shows how data are distorted in the service of law enforcement, but her work does so in an unusual way. “Most sociological research and criminal justice has focused on those who are being policed,” she said. “I very deliberately wanted to flip the lens to focus on those doing the surveilling – on the police themselves.”
Other scholars have taken notice of her work. Andrew Guthrie Ferguson, author of The Rise of Big Data Policing: Surveillance, Race and the Future of Law Enforcement and a professor at American University, observed that Brayne’s book “is a completely original inside look at the development of big data surveillance ... Sarah has been given access to the reality of big data policing in a way no one else has – and probably, because of her success, no one else ever will.”
The drive toward integrating technology into policing that Brayne’s book examines has a long history in America, but the push became more noticeable after 9-11. The newly created Department of Homeland Security doled out $35 billion in grants to state and local police to develop data infrastructure that could assist federal authorities in identifying and tracking potential terror threats. Police departments soon realized that this same tech could be used in their normal policing activities, and so the predictive analytics and data collation of the national security apparatus was brought to bear on American communities.
Brayne’s book offers her first-hand account of what encounters between big data policing and communities look like. She describes data collection tools like Operation LASER, funded in Los Angeles by a grant from the federal Bureau of Justice Assistance. Every person an officer encounters who is deemed “suspicious” is entered into the system, and records of these encounters are built that track peoples’ movements and who they associate with, even though there is no evidence of a crime being committed.
The data gathered through Operation LASER are collated into a database that can execute customer searches via the software of Palantir Gotham. Brayne watched a Palantir engineer search through 140 million records looking for a hypothetical non-descript man driving a black four-door sedan. The search narrowed to 13 people, but the engineer had no response when asked about assumptions in the system, bad data, or simple glitches could affect the outcome.
Police administrators generally gush over the potential of data analytics to erase many of the problems in policing that are currently under scrutiny. None of them, however, offer any explanation as to why data-driven policies advise more policing of already over-policed communities or how software could overcome the systemic biases in how police collect and quantify data.
On a more practical level, the cops who are tasked with integrating the new tech into daily use have complaints of their own. One sergeant told Brayne that while the new tech “looks bitching ... it’s completely worthless.” Others complained about the inability to effectively use the system in patrol vehicles, while unions have raised issues with the system’s ability to track the movements of officers themselves.
What is clear throughout Brayne’s book is that the momentum toward more data-driven policing, with all its assorted side effects, is not likely to abate anytime soon. The most important aspect of her work is that it removes the critique of this disturbing trend out of the halls of academia and places it squarely in real locations where it affects real lives. Forrest Stuart, a sociologist at Stanford, hopes Brayne’s book “makes us take real pause and recognize the faults in this techno-optimist dream.”
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