Implicit association test
In 1995 Mahzarin Banaji and Anthony Greenwald developed a test, the Implicit Association Test (IAT) to measure the strength of automatic associations, revealing people’s hidden biases about gender, race, age, disability, sexuality and 90 other topics. See Project Implicit for more information on the IAT
The IAT presents respondents with different stimuli dependent on the category; for example for the Race IAT, white faces, black faces, "good" words, and "bad" words. Respondents complete trials in which they sort white/good pairings from black/bad pairings and white/bad pairings from black/good pairings.
Implicit racial bias is demonstrated by measuring the respondents’ "response latency," i.e., the difference in time it takes to complete the different trials.
While there is some debate as to whether the IAT measures future discriminatory behaviour, it may measure familiarity and learned associations which in turn can impact fast and unquestioned decision making and assessments of people and situations without us realising. Measures of unconscious bias and implicit associations may therefore increase personal awareness of stereotyped views and opinions and of their full impact and implications.