Look up base rates before forming a resemblance judgment
Before deciding "this looks like X," ask how common X actually is in the relevant population.
Why it works
Representativeness substitutes "how typical is this?" for "how probable is this?" — an easier question that feels like the right one. The substitution goes unnoticed because the resemblance judgment is computed automatically and feels like evidence. Anchoring on a base rate first forces the harder question to the front, making it much more likely that probability judgment is correctly calibrated rather than distorted by surface similarity.
How to do it
- Name the category you’re about to assign something to ("this person is probably a doctor").
- Before using resemblance as evidence, ask: "What fraction of people in the context I encountered this person are doctors?"
- Write down that base rate as your starting probability.
- Update for specific observed features only if those features are genuinely more common in the category than outside it.
Evidence
Kahneman and Tversky’s original 1973 research on the engineer/lawyer problem showed that subjects ignored explicit base rate information (70/30 split) when they had a representative description. Many follow-up studies replicate base-rate neglect, though instruction on base rates can partially correct it. (observational)
Base-rate neglect is stronger when the description is vivid and individuating; it reduces (but doesn’t vanish) when no description is given or when subjects are prompted to think like statisticians.
Sources
- Kahneman & Tversky (1973), On the psychology of prediction, Psychological Review
Common mistake
Treating resemblance as only one factor while still weighting it heavily — if you thought of the base rate at all but still landed on the representative answer, the heuristic won.
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More practices for The Representativeness Heuristic — Judging by Resemblance
- Identify which features are actually diagnostic
Separate features that genuinely differentiate categories from ones that just complete the picture.
- Recognize that random sequences don’t "owe" balance
Random processes have no memory — a run of heads doesn’t make tails more likely.
- Treat small samples with explicit skepticism
A short sequence can look representative without being statistically reliable — adjust confidence for sample size.
- Audit person-judgments for prototype substitution
Check whether a judgment about a person is based on their actual behavior or on resemblance to a type.
- Expect extreme results to regress toward average
Unusually good or bad performance predicts more average performance next time — account for this before giving praise or blame.
- Name the prototype you’re comparing against before deciding
Make the prototype you’re using as a reference explicit — hidden templates bias decisions without scrutiny.