The implicit-association test (IAT) is an assessment intended to detect subconscious associations between mental representations of objects (concepts) in memory.
[3][4] The implicit-association test is the subject of significant academic and popular debate regarding its validity, reliability, and usefulness in assessing implicit bias.
This would allow researchers to understand attitudes that cannot be measured through explicit self-report methods due to lack of awareness or social-desirability bias.
[1] In essence, the purpose of the IAT was to reliably assess individual differences in a manner producing large effect sizes.
[12] Since its original publication date, the seminal IAT article has been cited over 4,000 times,[13] making it one of the most influential psychological developments over the past couple of decades.
[3] Finally, as is characteristic of any psychological instrumentation, discussion and debate of the IAT's reliability and validity has continued since its introduction, particularly because these factors vary between different variations of the test.
[14] A computer-based measure, the IAT requires that users rapidly categorize two target concepts with an attribute (e.g. the concepts "male" and "female" with the attribute "logical"), such that easier pairings (faster responses) are interpreted as more strongly associated in memory than difficult pairings (slower responses).
[2] The IAT may allow researchers to get around the difficult problem of social-desirability bias and for that reason it has been used extensively to assess people's attitudes towards commonly stigmatized groups, such as African Americans and individuals who identify as homosexual.
[21] An idiographic approach using the IAT and the SC-IAT for measuring implicit anxiety showed that personalized stimulus selection did not affect the outcome, reliabilities and correlations to outside criteria.
[22] The Go/No-go Association Test (GNAT) is a variation of the IAT that assesses implicit attitudes or beliefs by measuring the relationship between a target concept and two different extremes of an attribute.
the earlier "doll experiment" developed by psychologists Kenneth and Mamie Clark during the early civil rights era).
Unlike the GNAT, the Brief IAT doesn't not use accuracy of correctly identifying the specific concept and attribute requested.
[34] De Houwer theorizes that the IAT is a measure of a response compatibility effect, in which participants first learn to associate positive and negative words and concepts with pressing specific keys on the keyboard.
Later in the test, when participants are instructed to sort words and concepts that are both negative and positive with the same keyboard key, De Houwer argues that much of the latency and incorrect responses that result from this change are due to the increased cognitive complexity of the task, and not necessarily a reflection of implicit bias.
[14][35] Brendl, Markman, and Messner have proposed a random walk model process to explain responses in the critical portions of the IAT.
They theorize that test respondents base their responses on a process of mental evidence-gathering that continues until the evidence for one option or the other (right or left key) reaches a threshold, at which time a decision is made, and action is taken.
[37] In 2002, Greenwald and his colleagues introduced the balanced-identity design as a method to test correlational predictions of Heider's balance theory.
The triad system of "me—male—being good at math" will be used as an example here, and its typical result acquired from the Implicit Association Test (IAT) will be shown below.
Although self-reports don't necessarily reflect the predicted consistency patterns from Heider's theory, it is often used to compare with the results from the Implicit Association Test (IAT).
[41] For instance, feedback may report that someone has a [minimal/slight/moderate/strong] automatic preference for [European Americans/African Americans], though critics contest the degree to which such conclusions can be drawn from an IAT.
[43] Since its introduction into the scientific literature in 1998, a great deal of research has been conducted in order to examine the psychometric properties of the IAT as well as to address other criticisms on validity and reliability.
A follow-up meta-analysis lead-authored by Frederick L. Oswald criticised Greenwald's study for overestimating the correlations between IAT scores and discriminatory behavior by including studies that didn't actually measure discriminatory behavior (such as those which found a link between high IAT scores and certain brain patterns) and treating published findings in which high IAT scores correlated with better behavior toward out-group than in-group members as evidence of implicitly biased individuals overcompensating.
Some research has found that the IAT tends to be a better predictor of behavior in socially sensitive contexts (e.g. discrimination and suicidal behaviour)[45] than traditional "explicit" self-report methods,[36] whereas explicit measures tend to be better predictors of behavior in less socially sensitive contexts (e.g. political preferences).
Specifically, the IAT has been shown to predict voting behavior (e.g. ultimate candidate choice of undecided voters),[46] mental health (e.g. a self-injury IAT differentiated between adolescents who injured themselves and those who did not),[47] medical outcomes (e.g. medical recommendations by physicians),[48] employment outcomes (e.g. interviewing Muslim-Arab versus Swedish job applicants),[49] education outcomes (e.g. gender-science stereotypes predict gender disparities in nations' science and math test scores),[50] and environmentalism (e.g., membership of a pro-environmental organisation).
For example, in one study, a simple reminder from the experimenter ("Please be careful not to stereotype on the next section of the task") was sufficient to significantly reduce the expression of biased associations on a race IAT.
[65] Older subjects also tend to have more extreme IAT scores, and this may be related to cognitive fluency, or slower overall response times.
One example of the latter case is that scores on the Race IAT are known to be less biased against African Americans when those taking it imagine positive Black exemplars beforehand (e.g. Martin Luther King).
[74] Similar results were found in the United States when administering an English and Spanish IAT on bilingual Hispanic Americans.
[76] After establishing the IAT in the scientific literature, Greenwald, along with Mahzarin Banaji (Professor of Psychology at Harvard University) and Brian Nosek (Associate Professor of Psychology at the University of Virginia), co-founded Project Implicit,[77] a virtual laboratory and educational outreach organization that facilitates research on implicit cognition.
The IAT has been profiled in major media outlets (e.g. in the Washington Post)[78] and in the popular book Blink, where it was suggested that one could score better on the implicit racism test by visualizing respected black leaders such as Nelson Mandela.