Toward a meaningful metric of implicit prejudice

Hart Blanton, James Jaccard, Erin Strauts, Gregory Mitchell, Philip E. Tetlock

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)1468-1481
Number of pages14
JournalJournal of Applied Psychology
Issue number5
StatePublished - Sep 1 2015


  • Arbitrary metrics
  • Discrimination
  • Implicit association test
  • Implicit attitudes
  • Prejudice

ASJC Scopus subject areas

  • Applied Psychology


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