Base rate fallacy definition
The Base Rate Fallacy occurs when we are too quick to make judgments, ignoring base rates or probabilities in favour of new information. This phenomenon is clearly demonstrated in the famous "cab driver problem" experiment outlined by the behavioural psychologist Daniel Kahneman.
In Kahneman's experiment, the subjects were presented with a fictional situation. They were told there had been a hit and run accident at night involving a taxi cab, and that the only eyewitness had identified the cab as being blue. They were told that there were two taxi companies in the city, one with green cabs (responsible for 85% of the cabs in the city), and the other with blue cabs (responsible for the remaining 15%). Finally, they were told that the court had tested the reliability of the eyewitness. In night-time conditions, the witness identified colours correctly 80% of the time.
Kahneman's subjects were then asked: "What is the likelihood that the cab involved in the accident was blue rather than green?" Most of the subjects said that that there was an 80% chance that the cab was blue.
This is an example of Base Rate Fallacy because the subjects neglected the initial base rate presented in the problem (85% of the cabs are green and 15% are blue). The problem should have been solved as follows:
- There is a 12% chance (15% x 80%) the witness correctly identified a blue car.
- There is a 17% chance (85% x 20%) the witness incorrectly identified a green as blue.
- There is a 29% chance (12% + 17%) the witness will identify the cab as blue.
- This results in a 41% chance (12% ÷ 29%) the identification is correct.
Accordingly, Base Rate Neglect is our tendency to misjudge the likelihood of a situation by not considering the statistical context. Instead, we tend to focus on the most recent piece of information we have received.
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