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.
Recommended Citation
Jeffrey L. Vagle,
Tightening the OODA Loop: Police Militarization, Race, and Algorithmic Surveillance,
22
Mich. J. Race & L.
101
(2016).
Available at:
https://repository.law.umich.edu/mjrl/vol22/iss1/4
Included in
Civil Rights and Discrimination Commons, Fourth Amendment Commons, Law and Race Commons, Law Enforcement and Corrections Commons, Science and Technology Law Commons
