Lorio Forensics

Measuring Implicit Racial Bias

This article is the second in a 3-part series regarding racial bias measurement and law enforcement. The first can be found here.

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Due to the limitations of self-report data, racial bias studies conducted post-World War II integrated physiological measures into methodology. In many of these studies, physiological indicators (e.g. skin conductance, neural imaging, and objective measures of brain processes) evaluate White participants’ arousal/brain activation in response to seeing photos of or looking at Black people. One apparent benefit of this trend is that physiological measures circumvent conscious biases and attitudes that distort self-report data.  While self-report measures make it easier for people to report non-prejudiced attitudes, this does not ensure that they can respond without bias across all domains. Early work measuring implicit bias relied on skin conductance measures, which, despite poor differentiation, did show that White American participants showed increased arousal when viewing photos of or interacting with Black Americans (Amodio et al., 2003; Ito & Bartholow, 2009). 

Current physiological research on prejudice continues the study of implicit mental processes related to racial stereotyping, prejudice, and discrimination by incorporating neural imaging (Jost, Nam, Amodio, & Van Bavel, 2014).  This literature has provided rich data areas of the brain that have been associated with imaging studies on race. As the subcortical brain structure responsible for social decision making, fear, emotional processing attitudes, and beliefs, the amygdala is often implicated in studies on race (Kubota et al., 2012). The amygdala refers to a small cluster of nuclei vital for the learning of emotional material. Information about race is learned and is typically tied to historical events with emotional charge. The emotionality often associated with race lead researchers to target the amygdala as a potential site for beginning brain-based research on race (Kubota et al., 2012). An important result derived from this sector of neuroscience research is that Whites display increased amygdala activation when looking at Black faces.  The degree of activation is impacted by other social cues such as the skin tone, facial expression, and eye-gaze direction of the target face (Richeson & Trawalter, 2008; Ronquillo et al., 2007; Trawalter, Todd, Baird, & Richeson, 2008). 

Alongside physiological measures, various implicit paradigms have been used to correct the fact that self-report data alone is insufficient to capture racially-biased responses (Amodio et al., 2003).  One such implicit measure is the Implicit Attitudes Test (IAT) which is often used when examining underlying racial attitudes.  The IAT “assesses strengths of associations between concepts by observing response latencies in computer-administered categorization tasks” (Greenwald, Poehlman, Uhlmann, & Banaji, 2009, p. 18). In other words, it relies on how much time the participants take to complete the categorizations. Participants may be shown categories such as “Black and White” and “good and bad” and asked to rapidly classify stimuli into categories.  When participants are asked to combine classification across initial categories (e.g., Black/good and White/bad), response times indicate the strength of association between racial groups and positive or negative associations (Greenwald et al., 2009). IAT studies have shown discrepancies between associations for in-group (similar) and out-group (different) members. For example, in White Americans, the IAT shows a substantial preference for positive stereotypes favoring Whites vs. Blacks.  Such results on the IAT are apparent even when self-report measures display no obvious racial preference (Kubota et al., 2012). 

These findings underscore why it can be helpful to utilize other measures outside of self-report: Apparent racial bias that is captured on implicit measures is not always captured on explicit ones. For example, amygdala activation is correlated with implicit measures of racial attitudes such as the IAT but has not been found to correlate with explicit self-report measures. In an fMRI study using White participants, Phelps et al. (2000) found that amygdala activation to unfamiliar Black faces were related to unconscious measures of racial bias (i.e., the startle eyeblink paradigm and the Implicit Attitudes Test).  However, increased activation to Black faces was not related to the self-report Modern Racism scale, which evaluates conscious attitudes towards Black Americans.


Sources:

Amodio, D. M., Harmon-Jones, E., & Devine, P. G. (2003). Individual differences in the activation and control of affective race bias as assessed by startle eyeblink response and self-report. Journal of Personality and Social Psychology, 84(4), 738.

Greenwald, A. G., Poehlman, T. A., Uhlmann, E. L., & Banaji, M. R. (2009). Understanding and using the Implicit Association Test: III. Meta-analysis of predictive validity. Journal of Personality and Social Psychology, 97(1), 17.

Jost, J. T., Nam, H. H., Amodio, D. M., & Van Bavel, J. J. (2014). Political neuroscience: The beginning of a beautiful friendship. Political Psychology, 35, 3–42.

Kubota, J. T., Banaji, M. R., & Phelps, E. A. (2012). The neuroscience of race. Nature Neuroscience, 15(7), 940–948.

Phelps, E. A., O’Connor, K. J., Cunningham, W. A., Funayama, E. S., Gatenby, J. C., Gore, J. C., & Banaji, M. R. (2000). Performance on indirect measures of race evaluation predicts amygdala activation. Journal of Cognitive Neuroscience, 12(5), 729–738.

Richeson, J. A., & Trawalter, S. (2008). The threat of appearing prejudiced and race-based attentional biases. Psychological Science, 19(2), 98–102.

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