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Racial and ethnic bias in decisions to shoot seen through a stronger lens: experimental results from high-fidelity laboratory simulations



Research on racial bias in the United States includes findings that Americans tend to view blacks as more dangerous than whites. Some have argued that this bias provides a likely explanation for the disproportionate number of ethnic and racial minorities shot by police. One piece of evidence for this proposition comes from experimental work in which research participants push “shoot” or “don’t shoot” buttons when still images of people and objects that may or may not be weapons are presented in rapid succession. These studies have established that participants tend to subconsciously pair black individuals with weapons and white individuals with neutral objects. However, it is not clear from these studies that the subconscious racial bias identified by researchers affects actual decisions to shoot, perhaps because the techniques used to assess the bias-shooting link bear so little resemblance to real-world shootings.


This paper reports on the results of a novel laboratory experiment designed to overcome this critical limitation by using high-fidelity deadly force judgment and decision-making simulators to assess both subconscious and behavioral bias among 48 research participants, recruited from the general population.


Study results suggest that subconscious associations between race and threat exhibited by participants are not linked to their shooting behavior.


The implications of this finding for understanding how race and ethnicity affect decisions to shoot, and for conducting empirical research on this important topic, are discussed.

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  1. 1.

    Since 2002, Correll and colleagues have extended their line of experimental “shoot”/”don’t shoot” research to include police officers as research subjects and expanded the “minority suspect” category beyond blacks to include Hispanics and Asians (Correll et al. 2006, 2007a, b; Sadler et al. 2012).

  2. 2.

    Advanced Interactive Systems’ (AIS) Professional Range Instruction Simulation (PRISim).

  3. 3.

    In NAT, complexity refers to the number of independent parts in a system (e.g. number of suspects, bystanders, officers, weapons etc.) and coupling refers to how much change in one part will effect change in another (e.g. distance between an officer and a suspect).

  4. 4.

    The headgear used was B-Alert X10 wireless ambulatory EEG caps; manufactured by Advanced Brain Monitoring in Carlsbad, CA, USA). These caps are comfortable and non-intrusive, and can be set up in less than 5 min. They can record up to 9 channels of high fidelity EEG, and have wireless acquisition and transmission up to 10 m, a vital feature given the size of the simulator ranges.

  5. 5.

    We chose alpha suppression as our indicator of threat response because it is easier to measure accurately than other neurophysiological phenomena, such as the P200 ERP’s used by Correll et al. (2006). ERP’s are brief in duration and can be difficult to detect because they co-occur with other electrical signals (Kolb and Whishaw 2001). Alpha waves, on the other hand, are of longer duration, are robust, and are relatively easy to monitor, which is an important consideration for experimental designs that involve substantial participant movement, such as the experiments described here.

  6. 6.

    Approved by the Washington State University Institutional Review Board.

  7. 7.

    Again using the R Project for statistical computing; model = lme(fixed = AlphaSupression ∼ Black + Hispanic + Difficulty, random = ∼1 | Subject, method = "ML"). See reaction time model above for an interpretation of the model.


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Research supported by Defense Advanced Research Projects Agency contract nos. NBCHC070101 and NBCHC090054, National Institute of Justice grant no. 2008-IJ-CX-0015, and Office of Naval Research DURIP grant no. N000140810802.

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Correspondence to Lois James.

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James, L., Klinger, D. & Vila, B. Racial and ethnic bias in decisions to shoot seen through a stronger lens: experimental results from high-fidelity laboratory simulations. J Exp Criminol 10, 323–340 (2014).

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  • Unconscious bias
  • Behavioral bias
  • Race/ethnicity
  • Decisions to shoot