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

Abstract

This Article examines how military automated surveillance and intelligence systems and techniques, when used by civilian police departments to enhance predictive policing programs, have reinforced racial bias in policing. I will focus on two facets of this problem. First, I investigate the role played by advanced military technologies and methods within civilian police departments. These approaches 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 automates de facto penalization and containment based on race. Second, I will explore these militarized systems, and their effects, from an outside-in perspective, paying particular attention to the racial, societal, economic, and geographic factors that play into the public perception of these new policing regimes. I will conclude by proposing potential solutions to this problem that incorporate tests for racial bias to create an alternative system that follows a true community policing model.