Anthony Greenwald, Debbie McGhee and Jordan Schwartz introduced the Implicit Association Test in 1998, a computer sorting task measuring how quickly a person pairs concepts (such as a racial or age category) with positive or negative attributes, intended as an indirect measure of automatic mental associations a person may not consciously endorse or even be aware of. The measure became widely used in both research and public diversity training, and has also drawn sustained methodological debate.
Facts
Disputed
Key FindingIndividual IAT scores show only middling test-retest reliability, around 0.60, and a meta-analysis by Oswald and colleagues found implicit measures were only weakly predictive of discriminatory behavior and no better than explicit self-report measures at predicting it, while other researchers maintain the test still captures a real, if imperfectly measured, automatic association. 1 The test's reliability and its link to real-world behavior are both actively disputed in the field, distinct from whether the sorting-speed measurement itself works as designed. Cross-Tradition Connections
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Open Questions (1 open question)
Does the Implicit Association Test measure a stable trait or situational noise?
Individual Implicit Association Test scores show only middling test-retest reliability, around 0.60, and researchers dispute whether the test measures a stable automatic association, widely shared cultural knowledge regardless of the test-taker's own attitude, or the momentary salience of certain attributes, with a meta-analysis by Oswald and colleagues finding implicit measures only weakly predictive of actual discriminatory behavior and no better than explicit self-report at predicting it.
What would resolve this Converging physiological, behavioral and longitudinal measures of the same individuals over time, isolating how much variation in IAT score reflects a stable trait versus test-retest noise or momentary situational context.
Psychometrics and social cognitionWikipedia: Implicit-Association Test
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