Base Rate Neglect

What is it?

Base rate neglect (or base rate fallacy) is the tendency to ignore general statistical information (base rates) in favor of specific case information, even when the base rate is more predictive. In Kahneman and Tversky's classic "lawyer-engineer problem," people given a personality description largely ignored whether the person was drawn from a pool of 70% lawyers or 70% engineers—the description dominated their judgment. We are drawn to stories, not statistics. This creates systematic errors. When evaluating a job candidate's impressive interview, we neglect how often strong interviewees turn out to be ordinary performers. When excited about a startup's compelling pitch, we neglect that most startups fail. Medical diagnosis is particularly vulnerable: a positive test result feels definitive, but interpretation requires knowing the base rate of the disease and false positive rate of the test. Base rate neglect leads to overconfidence in individual predictions and underuse of statistical regularities. Correcting it requires consciously asking "what's the base rate?" before being swayed by individual-case information, using Bayesian reasoning that combines base rates with case-specific evidence, and creating decision processes that force consideration of relevant statistics.