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Representativeness Heuristic

Also Known As: Representativeness bias
Cognitive Bias ID: representativeness_heuristic

Definition

The tendency to judge the probability of an event by how similar it is to a prototype or stereotype, rather than by actual statistical likelihood. People substitute the question 'How probable is this?' with 'How similar is this to my mental model?' This heuristic is efficient but leads to systematic errors when similarity and probability diverge.

Examples

A person described as 'quiet, organized, and detail-oriented' is judged more likely to be a librarian than a salesperson, despite salespeople vastly outnumbering librarians. The description matches the librarian stereotype, overriding base rate information.

A hiring manager receives two resumes: one from a candidate who attended an Ivy League university and lists chess club and classical piano, and one from a state school graduate with extensive retail work experience. For a data analyst role, she instinctively favors the first, matching him to her mental image of an 'analytical type,' despite the second candidate's directly relevant skills.

When a tall, broad-shouldered man at a party mentions he works in sports, everyone assumes he is an athlete. In reality, he is a sports accountant — but his appearance so closely matches the prototype of 'athlete' that people never consider the far more common sports-adjacent professions.

Verification Steps
Verification Steps
Binary yes/no questions that an AI must answer to detect a reasoning pattern in a text.
Each of the 452 aspects has verification steps — simple yes/no questions designed to systematically detect whether a pattern appears in a text. For ad hominem: "Does the argument attack a person rather than their claim?" For false dichotomy: "Are only two options presented when more exist?" This ensures consistent, reproducible analysis.

Binary (yes/no) questions an LLM must answer to identify this aspect:

  1. 1

    Is probability being judged by resemblance to a stereotype rather than by data?

    Type: binary
  2. 2

    Are base rates being ignored in favor of how typical something looks?

    Type: binary
  3. 3

    Would the judgment change if the assessment were based on statistics rather than similarity?

    Type: binary
Deep Dive
The expandable detail section on each aspect page with examples, psychology, and counter-strategies.
The Deep Dive section provides in-depth information about each aspect: a real-world example showing the pattern in action, an explanation of why it works psychologically, practical advice on how to counter it, alternative names, and links to related aspects.

Hierarchical Context