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

At the risk of sounding banal, Sarah Brayne’s research on big data analytics in policing could not be timelier. During the year 2020, violent crime increased by historic proportions in many large cities, arrest rates dropped to near historic lows, and civil unrest resulted in great costs to communities. These issues are likely to continue in 2021 as evidenced by the acts of domestic terrorism that occurred at the U.S. Capitol Building on January 6, and the failed police response. Calls for reforms to law enforcement at the local level in 2020 and the federal level at the start of 2021 demonstrate the shortcomings of current policing practices, and the immediate need for research on new, innovative law enforcement practices. Big data analytics, when applied to policing strategies and tactics, is one innovative tool that could answer calls for police reform by increasing the efficacy, efficiency, and fairness of the police. In Predict and Surveil, Brayne documents this potential, but ultimately decides that big data analytics and its associated surveillance and data collection activities ultimately increase inequalities in the application of law enforcement. To this reviewer, although Brayne raises important points and provides support for the advantages and disadvantages of big data analytics, her book falls short of providing sufficient evidence that the disadvantages of big data analytics and its predictive algorithms outweigh the inefficacies, inefficiencies, and inequities in current and historic law enforcement practices and decision-making.