Implicit association test
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The Implicit Association Test (IAT) is a psychological test with the purpose of measuring how strongly a person unconsciously associates certain categories of people with certain concepts or ideas. Essentially, it is designed to be a detector of unconscious prejudices and biases against social groups. Although it has gained use in social psychology research, workplace talks, police trainings, and jury guidelines, its level of scientific credibility (like that of anything which has to do with the unconscious) is, in the best case, controversial.
The first article on IAT was published in 1998 by psychology researchers Anthony Greenwald, Debbie McGhee, and Jordan Schwartz, following some ideas on explicit and implicit memories published by Banaji and Greenwald three years before.
How it works
IAT is usually performed on a computer and consists in a series of tasks in which the subject is asked to categorize some words into two categories by pressing a left-hand key or a right-hand key. For example, an IAT to measure negative or positive unconscious biases against black or white people proceeds about as follows:
- First, the word "Black" and "White" appear in the top left-hand corner and top right-hand corner of the computer screen, respectively. In the middle of the screen some words which are typically associated with the categories of "Black" or "White" appears one after another. For each word the subject chooses the appropriate category by pressing the appropriate key.
- The second task is similar but, instead of "Black" and "White", now the words "Pleasant" and "Unpleasant" are shown, and words associated with pleasant or unpleasant appear in the middle of the screen.
- On the third task, the words "Black/Pleasant" and "White/Unpleasant" appear in the screen top corners, and the subject has to categorize the words into the category of "Black or Pleasant", and the category of "White or Unpleasant".
- The tasks are then repeated but inverting the positions of the words and with the pairing "Black/Unpleasant" and "White/Pleasant"
All the times of response are recorded, and the idea behind IAT is that the pairing reflecting the stronger mental association of the subject is the one that they categorize more quickly. For example, a subject with negative biases against white people, should more rapidly categorize the pairs White/Unpleasant and Black/Pleasant.
What does IAT actually measure?
IAT only measures the time of response to certain stimuli. Whether quicker responses should be interpreted as strong mental associations is an open problem and, in such a case, whether strong mental associations should be interpreted as prejudices or biases is an even a bigger open problem.
Researchers have claimed that the IAT may instead be measuring constructs such as familiarity, cultural knowledge, or salience of attributes, and, in particular, that IAT does not measure racial prejudice.
A 2014 study found that if participants are asked to guess their results before taking IATs, then their predictions are "surprisingly" accurate, suggesting that whatever IAT is measuring is not unconscious at all.
A 2013 meta-analysis on IAT studies concluded that: "IATs […] were typically poor predictors of the types of behavior, judgments, or decisions that have been studied as instances of discrimination, regardless of how subtle, spontaneous, controlled, or deliberate they were" and that IAT predictive utility is no greater than explicit measures, precisely: "Any distinction between the IATs and explicit measures is a distinction that makes little difference, because both of these means of measuring attitudes resulted in poor prediction of racial and ethnic discrimination."
A test which is easy to fake is of less value, because people will achieve the socially-desirable result rather than giving a true reflection of their personality. Research on faking the IAT has been conducted, suggesting that the IAT is harder to fake than some personality tests such as the Big Five, but it is still possible to fake it. Results can be faked by deliberately slowing responses on some questions; however this may be detectable by comparing the response time against unfaked results.
Whether IAT is able to detect implicit biases or not, its application raises ethical problems.
If IAT does not detect biases, then people who have no prejudices may wrongly believe they are biased against another race, gender or social group. This can cause psychological discomfort to such people, which have been "scientifically" convinced of being biased and may try to change their conditions in good will, but fail in doing so, simply because they have no biases at all. Moreover, IAT can also label as "without biases" people who in reality have strong prejudices, giving them one more reason to never confront their beliefs.
On the other hand, if IAT does actually detect implicit biases, this information could actually have a negative impact on the fight against prejudices. First, it could give the biased person an excuse to their behavior: "It is not my fault if I am a racist, IAT shows that I am born with these implicit biases." Second, it could move the fight against prejudices from "convincing biased people that their beliefs are wrong" to "making biased people pass an IAT", an approach whose ethicality and effectiveness is strongly questionable. Third, IAT could actually create new prejudices, in the form of: "I do not trust him because IAT shows he is biased," so that people who have implicit biases are treated differently, even when they are not expressing prejudices.
- Facebook. "Managing Unconscious Bias". https://managingbias.fb.com/.
- Google Re:Work. "Watch Unconscious Bias @ Work". https://rework.withgoogle.com/guides/unbiasing-raise-awareness/steps/watch-unconscious-bias-at-work/.
- Unber Ahmad. "Implicit Bias in the Workplace". Training Industry. https://www.trainingindustry.com/articles/performance-management/implicit-bias-in-the-workplace/.
- "Fair & Impartial Policing". http://www.fairimpartialpolicing.com/.
- Marella Gayla (2017). "A Federal Court Asks Jurors to Confront Their Hidden Biases". The Marshall Project. https://www.themarshallproject.org/2017/06/21/a-federal-court-asks-jurors-to-confront-their-hidden-biases.
- Greenwald; McGhee; Schwartz (1998). "Measuring Individual Differences in Implicit Cognition: The Implicit Association Test". Journal of Personality and Social Psychology 74 (6): 1464-1480. https://doi.org/10.1037/0022-35184.108.40.2064.
- Greenwald, A. G.; Banaji, M. R. (1995). "Implicit social cognition: Attitudes, self-esteem, and stereotypes". Psychological Review 102: 4–27. https://doi.org/10.1037/0033-295x.102.1.4.
- Ottaway; Hayden; Oakes (2001). "Implicit attitudes and racism: Effects of word familiarity and frequency on the implicit association test". Social Cognition 19: 97-144. https://doi.org/10.1521/soco.220.127.116.1106.
- Arkes; Tetlock (2004). ""Attributions of Implicit Prejudice, or "Would Jesse Jackson 'Fail' the Implicit Association Test?". Psychological Inquiry 15: 257-278. https://doi.org/10.1207/s15327965pli1504_01.
- Rothermund; Wentura (2004). "Underlying processes in the Implicit Association Test(IAT): Dissociating salience from associations". Journal of Experimental Psychology: General 133: 139-165. https://doi.org/10.1037/0096-3418.104.22.168.
- van Ravenzwaaij; van der Maas; Wagenmakers (2011). "Does the name-race implicit association test measure racial prejudice?". Experimental Psychology 58: 271-7. https://doi.org/10.1027/1618-3169/a000093.
- Hahn; Judd; Hirsh; Blair (2014). "Awareness of implicit attitudes". Journal of Experimental Psychology 143: 1369-92. https://doi.org/10.1037/a0035028.
- Oswald; Mitchell; Blanton; Jaccard; Tetlock (2013). "Predicting ethnic and racial discrimination: A meta-analysis of IAT criterion studies". Journal of Personality and Social Psychology 105: 171-192. https://doi.org/10.1037/a0032734.
- Steffens (2004). "Is the implicit association test immune to faking?". Experimental Psychology 51: 165-79. https://doi.org/10.1027/1618-322.214.171.124.
- Cvencek; Greenwald; Brown; Gray; Snowden (2010). "Faking of the Implicit Association Test Is Statistically Detectable and Partly Correctable". Basic and Applied Social Psychology 32. https://doi.org/10.1080/01973533.2010.519236.