📖 Business
Implicit Association Test
The Implicit Association Test (IAT) is a computer-based diagnostic tool developed by Anthony Greenwald in 1998 that measures the strength of automatic associations between mental concepts and evaluations. Unlike surveys or self-reports, the IAT captures reaction-time differences when people pair concepts (e.g., "Black faces" with "good words" vs. "White faces" with "good words") to reveal preferences the test-taker may not consciously endorse or even recognize. It has been taken by millions of people through Project Implicit at Harvard and remains the most widely used instrument for measuring implicit bias.
2
Minutes
2
Concepts
+45
XP
1
How It Works
- Reaction-time measurement — The IAT works by measuring how quickly you can sort items when categories are paired in congruent vs. incongruent ways. If you sort faster when "Male" is paired with "Career" than when "Male" is paired with "Family," that speed difference reveals an implicit association.
- Seven-block structure — A standard IAT has seven sorting blocks that progressively pair target concepts with evaluative attributes, alternating between compatible and incompatible pairings to isolate the association strength.
- D-score calculation — The IAT produces a D-score that quantifies the strength of implicit preference. Scores range from strong preference for one group to strong preference for the other, with most people showing moderate automatic preferences.
- Domains tested — IATs exist for race, gender, age, weight, sexuality, disability, religion, skin tone, and more. Each reveals a distinct dimension of implicit bias that may differ from a person's explicit attitudes.
- Population-level patterns — Across millions of test-takers, approximately 75% of White Americans show an implicit preference for White over Black faces. These population-level patterns hold even among people who explicitly reject racial bias, demonstrating the dissociation between conscious values and automatic associations.