Best research practices for using the Implicit Association Test

Greenwald, Anthony G.; Brendl, C. Miguel; Cai, Huajian; Cvencek, Dario; Dovidio, John F.; Friese, Malte; Hahn, Adam; Hehman, Eric; Hofmann, Wilhelm; Hughes, Sean; Hussey, Ian; Jordan, Christian H.; Kirby, Teri A.; Lai, Calvin K.; Lang, Jonas W. B.; Lindgren, Kristen P.; Maison, Dominika; Ostafin, Brian D.; Rae, James R.; Ratliff, Kate A.; Spruyt, Adriaan; Wiers, Reínout W.

doi:10.3758/s13428-021-01624-3

Cited by 69 publications

(112 citation statements)

References 72 publications

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“…The standard IAT procedure is described fully in Appendix A. The scoring method is described fully in Appendix B of Greenwald et al (2021). An interpretation of how the measure succeeds follows.…”

Section: What Is Known About Implicit Biasmentioning

confidence: 99%

Implicit-Bias Remedies: Treating Discriminatory Bias as a Public-Health Problem

Greenwald

Dasgupta

Dovidio

et al. 2022

Psychol Sci Public Interest

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Accumulated findings from studies in which implicit-bias measures correlate with discriminatory judgment and behavior have led many social scientists to conclude that implicit biases play a causal role in racial and other discrimination. In turn, that belief has promoted and sustained two lines of work to develop remedies: (a) individual treatment interventions expected to weaken or eradicate implicit biases and (b) group-administered training programs to overcome biases generally, including implicit biases. Our review of research on these two types of sought remedies finds that they lack established methods that durably diminish implicit biases and have not reproducibly reduced discriminatory consequences of implicit (or other) biases. That disappointing conclusion prompted our turn to strategies based on methods that have been successful in the domain of public health. Preventive measures are designed to disable the path from implicit biases to discriminatory outcomes. Disparity-finding methods aim to discover disparities that sometimes have obvious fixes, or that at least suggest where responsibility should reside for developing a fix. Disparity-finding methods have the advantage of being useful in remediation not only for implicit biases but also systemic biases. For both of these categories of bias, causes of discriminatory outcomes are understood as residing in large part outside the conscious awareness of individual actors. We conclude with recommendations to guide organizations that wish to deal with biases for which they have not yet found solutions.

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Section: What Is Known About Implicit Biasmentioning

confidence: 99%

Implicit-Bias Remedies: Treating Discriminatory Bias as a Public-Health Problem

Greenwald

Dasgupta

Dovidio

et al. 2022

Psychol Sci Public Interest

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“…The current debate seems to have launched this kind of reflection. Perhaps we should capitalize on this opportunity to familiarize ourselves with concerns about measurement (Machery, 2021a) and measurement of implicit bias in particular (Gawronski, 2019;Greenwald et al, 2021). If nothing else, it may serve as a reminder of what we can and cannot infer from implicit bias experiments (Byrd, 2019).…”

Section: Discussionmentioning

confidence: 99%

Testing for Implicit Bias: Values, Psychometrics, and Science Communication

Byrd¹,

Thompson²

2022

Preprint

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Our understanding of implicit bias and how to measure it has yet to be settled. Various debates between cognitive scientists are unresolved. Moreover, the public’s under-standing of implicit bias tests continues to lag behind cognitive scientists’. These discrepancies pose potential problems. After all, a great deal of implicit bias research has been publicly funded. Further, implicit bias tests continue to feature in discourse about public- and private-sector policies surrounding discrimination, inequality, and even the purpose of science. We aim to do our part by reconstructing some of the re-cent arguments in ordinary language and then revealing some of the operative norms or values that are often hidden beneath the surface of these arguments. This may help the public learn more about the science of implicit bias. It may also help both laypeople and scientists reflect on the values, interests, and stakeholders involved in establishing, justifying, and communicating scientific research.

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“…Next, we administered a common version of the race IAT and specifically followed recommendations from several methodological reviews on its use (Nosek, Greenwald & Banaji, 2007;Greenwald, Nosek & Banaji, 2003). A newer review with more recommendations on using the IAT (Greenwald et al, 2021) was not available when we collected the data in 2019/2020, however, our procedures were in line with the recommendations outlined therein. This test measures the association strength between White/Black faces and negative/positive words, respectively.…”

Section: Methodsmentioning

confidence: 99%