Eliminating Racial Bias in Police Officer Decisions to Shoot: Implications for the Control of Automatic Bias

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In today's world, police officers face difficult split-second decisions that require them to determine whether criminal suspects are armed and constitute an imminent threat. When suspects are members of ethnic minorities there may be a greater tendency for police officers to believe that they are armed. Examples of this include the shooting of an unarmed young Black man by police officers who mistook the cellular phone that he was carrying for a weapon. When tragedies like this occur, the question arises as to whether police officers' split-second decisions to shoot may be influenced by the suspect's race. There is mounting evidence that police officers are more likely to mistakenly shoot unarmed Black suspects compared to unarmed White suspects. This research examines the efficacy of a training program to eliminate this type of racial bias in responses to criminal suspects. The goals of this research are to: 1) Develop a deeper understanding of how to eliminate racial bias in police responding; 2) Identify the behaviors and responses that can be influenced by training on a bias reduction simulation; and 3) Explore whether there are factors that affect either the degree of racial bias initially present or the efficacy of a training simulation. A series of studies employing computer simulations is proposed to programmatically examine each of these issues. In this work, law enforcement personnel participate, and complete a computer simulation where they must decide whether to shoot at suspects who appear on screen. Here, the race of suspect is unrelated to weapon possession such that attending to race and being influenced by race impairs performance on the simulation. Initial evidence indicates that this approach is effective in eliminating racial biases in responses to the simulation even 24 hours after training.