Base Rate Fallacy
The base rate fallacy happens when people ignore general statistical information (the base rate) and focus only on specific details. This can lead to mistakes in probability judgments.
For example, imagine a town with 10,000 farmers and 10 librarians. Now, meet Emily, who is described as quiet, organized, and a lover of reading. When asked whether Emily is more likely to be a librarian or a farmer, many people might quickly say she's a librarian because her personality fits the stereotype of a librarian. However, this ignores the base rate - the actual number of farmers and librarians in the town.
Here's another example: Imagine only 10% of cases of food poisoning from milk come from consuming raw milk and 90% come from drinking pasteurized milk. Can we conclude that raw milk has a lower chance of causing food poisoning? No, not without considering the base rate. If only 1% of milk consumption is raw milk, we can conclude there is a much higher chance of contracting food poisoning from drinking raw milk.
To make accurate assessments and predictions, we must consider both the specific details and the base rates.
Note: I’ve called this the base rate fallacy because that’s the most common label, but it’s also called base rate neglect. It can show up both as a logical fallacy (a flawed argument) and as a cognitive bias—a predictable distortion in judgment where we overlook the base rate without realizing it. For more on the distinction between logical fallacies and cognitive biases, read Heuristics, Biases, and Fallacies: Definitions and Key Differences.
