A Critique of Current Methods of Racial Bias Measurement

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

Self-report is the earliest and most well-established method for measuring racial bias. Unfortunately, self-report measures are highly susceptible to social desirability bias resulting in individuals distorting their results to appear less prejudiced (Quillian, 2006). Due to the issues that arise from researching prejudice using predominantly self-report, such measures are most beneficial when combined with other units of analysis. 

However, implicit methods present their own challenges when trying to evaluate prejudiced responding. Some researchers have used the term racial bias to describe the differences on physiological (e.g. amygdala activity, fMRI) and behavioral measures (e.g. IAT) whereas others have argued that the term bias is inappropriate. These researchers argue that implicit measures do not directly examine racial bias. Rather, they test the strength of an association learned through cultural stereotypes (e.g. White-Good or Black-Bad). What is actually being captured through the observed neurobiological, physiological, and behavioral responses is social knowledge of negative stereotypes associated with racial and ethnic minorities.  Knowledge of these negative stereotypes may increase amygdala activation, scores on the IAT, and other physiological and sociological measures (Eberhardt, 2005). 

A shared critique of explicit and implicit racial bias measurement is that both methods focus on individual differences. As a result, many of the studies in this area describe prejudice and related phenomenon but fall short of intervening in prejudiced behaviors (Jost et al., 2014). Another shortcoming is that explicit and implicit racial bias measures require individual administration. The cheapest forms of measurement (e.g. self-report) are largely inaccurate whereas more effective physiological measurement systems are too expensive or time consuming for practical use in widespread evaluations. 

The ultimate goal of measuring racial bias should be to identify it so that it can be addressed and eliminated from our institutions, policies, and systems. With the current measurement’s focus on individual differences, racist beliefs are centered as the target issue rather than the systemic and institutional nature of racism. Identifying racial prejudice on an individual level merely describes a part of a larger structural issue. 

The limited utility of existing racial bias measures for implementation of structural change raises the question - Is quantifying bias essential to reducing it? This is not to discount the valuable knowledge that racial bias measurement has contributed in terms of understanding how expressions of prejudice have changed over time. However, these contributions have the most utility on an individual level rather than a systemic level. The intent behind racial bias assessments is that once people become aware of their implicit biases, then they can exert cognitive control to mitigate them. The IAT has some evidence of predictive validity and is often used as a projection of behavioral intent.

However, a 2017 meta-analysis that included 492 studies found that reducing implicit bias did not result in changed behavior (Forscher et al., 2019). In a recent example, 27-year-old Derrick Sanderlin worked for years at the San Jose police department offering implicit bias training. In May 2020 Sanderlin was shot with rubber bullets by officers from that same police department while attempting to de-escalate tensions between civilians and police at a protest following the murder of George Floyd. Sanderlin suffered injuries that required emergency surgery and may prevent him from having children (Koran, 2020). 

Sanderlin’s example underscores that reducing implicit bias is insufficient. Diversity, equity, and inclusion, trainings as stand-alone interventions may also be insufficient. In a second meta-analyses of nearly one thousand intervention studies aimed at prejudice reduction (e.g. workplace diversity initiatives, sensitivity training, educational programs cognitive interventions) researchers found weak evidence that any type of intervention reduced biased behavior in real-world settings (Paluck & Green, 2009).

Even if an individual’s bias was able to be reduced through measurement and intervention, those changes would be short-lived without systemic intervention. Research on intergroup bias suggests that being in a prejudiced environment makes prejudice more socially acceptable and makes people more willing to express private prejudices (Effron & Knowles, 2015). Selecting the least biased individuals for civil roles would be ineffective because those same individuals would become more biased over time by being surrounded by and a participant in a biased system.

A New Way Forward: Systemic Intervention

During heightened times such as these, there is a natural urge for individuals and organizations to leap into action. Before engaging in training, stockpiling resources, and planning organizational overhauls, we must recognize a few simple truths. Institutional racism is an issue that is hundreds of years in the making. Simple solutions and quick fixes like attitudinal surveys and employee training are insufficient for the magnitude of the problem we hope to solve. 

Our impulse for measurement is in the right spirit but headed in the wrong direction. Rather than focus on the quantification of individual bias, attention must be trained on measures that capture inequitable outcomes, interventions that address them, and re-evaluation and iterating until equity is achieved. Such efforts should naturally include community accountability and collaboration.



References

Eberhardt, J. L. (2005). Imaging race. American Psychologist, 60(2), 181.

Effron, D. A., & Knowles, E. D. (2015). Entitativity and intergroup bias: How belonging to a cohesive group allows people to express their prejudices. Journal of Personality and Social Psychology, 108(2), 234.

Forscher, P. S., Lai, C. K., Axt, J. R., Ebersole, C. R., Herman, M., Devine, P. G., & Nosek, B. A. (2019). A meta-analysis of procedures to change implicit measures. Journal of Personality and Social Psychology, 117(3), 522.

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.

Koran, M. (2020). An activist gave police anti-bias training. Officers still brutalized him at a protest. The Guardian.

Paluck, E. L., & Green, D. P. (2009). Prejudice reduction: What works? A review and assessment of research and practice. Annual Review of Psychology, 60, 339–367.

Quillian, L. (2006). New approaches to understanding racial prejudice and discrimination. Annu. Rev. Sociol., 32, 299–328.

Dr. Vinson Receives invitation to Task Force to Examine State Courts’ Response to Mental Illness.

This past month, The Conference of Chief Justices (CCJ) and Conference of State Court Administrators (COSCA) invited Dr. Sarah Vinson to become a member of the National Judicial Task Force to Examine State Courts’ Response to Mental Illness.

The responsibly of the Task Force is to examine the impact that individuals with mental illness have on the operations of state judicial systems. As a continuation and transition of the work of the National Initiative Advisory Committee (est. 2019; National Initiative Advisory Committee), the team will make policy and practice recommendations to help improve the state courts’ response.

In May 2020, CCJ and COSCA established the Task Force to assume leadership of the project, transitioning the Advisory Committee’s work to the Task Force. This report includes information about the current activities of the project. The work of the Task Force is led by an Executive Committee and each of the members will be assigned to and work within one of three Work Groups: Criminal Justice, Civil, Family and Probate, and Education and Partnerships. Dr. Vinson, along with the other members of the group, will use her field expertise to help ensure court systems play a leading role in understanding the issues and aid in providing practicable solutions for individuals suffering from mental illness at every intersection point within the justice system.


About The Conference of Chief Justices — The Conference of Chief Justices (CCJ) was founded in 1949 to provide an opportunity for the highest judicial officers of the states to meet and discuss matters of importance in improving the administration of justice, rules and methods of procedure, and the organization and operation of state courts and judicial systems, and to make recommendations and bring about improvements on such matters.

About The Conference of State Court Administrators (COSCA) — The Conference of State Court Administrators (COSCA), established in 1955, is dedicated to the improvement of state court systems. Its membership consists of the state court administrator or equivalent official in each of the fifty states, the District of Columbia, Puerto Rico, American Samoa, Guam, Northern Mariana Islands, and the Virgin Islands.

Logos - MFHT

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.

SOCIAL JUSTICE

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.