Ignoring statistical base rates (how common something is in the population) in favor of specific case information or stereotypes.
When judging probability, people focus on individual case details while ignoring population statistics. If told someone is shy and likes poetry, people judge 'librarian' as more likely than 'farmer,' even though farmers vastly outnumber librarians. The representativeness heuristic (does this person match my librarian stereotype?) overrides base rate information (librarians are rare). This leads to systematic errors in diagnosis, prediction, and decision-making across domains from medicine to investing.
A doctor sees symptoms matching a rare disease and diagnoses it, ignoring that the base rate (how common the disease is) makes a common disease with similar symptoms far more likely.
Individual case information is more diagnostic than population statistics—base rates are often more informative than case-specific details.
Why do people judge 'librarian' as more likely than 'farmer' for someone who is shy and likes poetry, even though farmers vastly outnumber librarians?
A doctor sees symptoms that match a rare disease affecting 1 in 10,000 people. The symptoms also match a common condition affecting 1 in 100 people. What error might base rate neglect cause?
Logically equivalent choices produce different decisions when framed differently (as gains vs. losses, or with different reference points).
PrincipleContinuing an endeavor because of previously invested resources (time, money, effort) that cannot be recovered, even when continuing is irrational.
PrincipleFast, automatic, unconscious cognitive processing that operates through pattern recognition and associative memory without deliberate effort.
Mental ModelSlow, effortful, conscious cognitive processing required for complex calculations, unfamiliar tasks, and deliberate reasoning.
Mental ModelThe tendency to rely too heavily on the first piece of information encountered (the anchor) when making decisions, even when it's arbitrary or irrelevant.
PrincipleJudging the frequency or probability of events by how easily examples come to mind, leading to overestimation of vivid, recent, or emotional events.
PrincipleJudging probability by similarity to stereotypes or prototypes, while ignoring base rates and sample size.
PrincipleWhen faced with a difficult question, System 1 automatically substitutes an easier question without conscious awareness of the switch.
FrameworkIgnoring statistical base rates (how common something is in the population) in favor of specific case information or stereotypes.
A doctor sees symptoms matching a rare disease and diagnoses it, ignoring that the base rate (how common the disease is) makes a common disease with similar symptoms far more likely.
Individual case information is more diagnostic than population statistics—base rates are often more informative than case-specific details.
Base Rate Neglect is explored in depth in "Thinking, Fast and Slow" by Daniel Kahneman. Distilo provides a deep AI-powered analysis with key insights, audio narration, and practical frameworks.