Representativeness Heuristic
Updated 2026-08-06
INTRODUCTION
English translation pending.
CORE DEFINITION
Identified by Daniel Kahneman and Amos Tversky, the representativeness heuristic is the tendency to judge whether an object belongs to a category by how closely it resembles the typical member, rather than by the category's base rate. A shy person who wears glasses seems more likely to be a librarian than a farmer, even though farmers vastly outnumber librarians. The heuristic is fast and often serviceable, but it produces systematic errors in probability judgment and sustains stereotypes.
SCAFFOLDING EFFECT
Reduce cognitive load
- Separate similarity from probability: ask how common the category is, not just how typical the case looks. - Check the base rate: get the actual frequency before judging category membership. - Replace resemblance with evidence: use past performance or measured data instead of whether someone fits the type.
Anchor fast decisions
Similarity is easy to compute from the features at hand, while base rates require retrieving external statistics that are not present in the scene. The mind therefore substitutes the available similarity judgment for the probability question it was asked. Because the substitution happens without notice, the resulting estimate feels like a probability even though it measures resemblance.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Representativeness_heuristicverified
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