Tightening the OODA Loop: Police Militarization, Race, and Algorithmic Surveillance

This Article examines the role military (and military-style) automated surveillance and intelligence systems have supported a self-reinforcing racial bias when used by civilian police departments to enhance predictive policing programs. I will focus on two facets of this problem. First, my research will take an inside-out perspective, studying the role played by advanced military technologies and methods within civilian police departments, and how they have enabled a new focus on deterrence and crime prevention by creating a system of structural surveillance where decision support relies increasingly upon algorithms and automated data analysis tools, and which automates de facto penalization and containment based on race. Second, I will explore these systems—and their effects—from an outside-in perspective, paying particular attention to racial, societal, economic, and geographic factors that play into the public perception of these policing regimes. I will conclude by identifying critical areas within this problem, which promote social instability by acting as barriers to a true community policing model.