Toward a meaningful metric of implicit prejudice

Abstract

[Correction Notice: An Erratum for this article was reported in Vol 100(5) of Journal of Applied Psychology (see record 2015-40760-001). there are errors in some of the values listed in Table 6 that do not alter any of the conclusions or substantive statements in the original article. The corrected portion of Table 6 is in the correction. The positive intercepts in this table represent the estimated IAT score when the criterion has a value of zero (suggesting attitudinal neutrality), except in the equation examining voter preference in Greenwald et al. (2009), where the intercept estimated the IAT score of Obama voters.] The modal distribution of the Implicit Association Test (IAT) is commonly interpreted as showing high levels of implicit prejudice among Americans. These interpretations have fueled calls for changes in organizational and legal practices, but such applications are problematic because the IAT is scored on an arbitrary psychological metric. The present research was designed to make the IAT metric less arbitrary by determining the scores on IAT measures that are associated with observable racial or ethnic bias. By reexamining data from published studies, we found evidence that the IAT metric is "right biased," such that individuals who are behaviorally neutral tend to have positive IAT scores. Current scoring conventions fail to take into account these dynamics and can lead to faulty inferences about the prevalence of implicit prejudice.