Base rate fallacy

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The base rate fallacy, also called base rate neglect, is an error that occurs when the conditional probability of some hypothesis H given some evidence E is assessed without taking sufficient account of the "base rate" or "prior probability" of H.

For example, in a country with 100 terrorists and one million non-terrorists, surveillance cameras with automatic face recognition software are installed in the street. If the system sees a known terrorist it will ring a bell with 99% probability. If the camera sees a non-terrorist it will ring 1% of the time. so the misidentification rate is 1%.

Suppose the system identifies somebody as a terrorist. What is the chance it is really a terrorist? If all 1,000,100 people in the country were scanned by the cameras, about 99 terrorists trigger a ring — and so would 10,000 nonterrorists. Therefore, the probability that the person who made the bell ring is actually a terrorist is only 99 in 10,099 (about 1/100). The base rate fallacy consists in ignoring the fact that nonterrorists outnumber terrorists, and claiming that, if the failure rate of the device is 1 in 100, then the false alarm rate must be 1 in 100 as well, and hence that if the device rings at anyone, the probability that he is a terrorist is 99/100.

Findings in psychology

In some experiments, students were asked to estimate the grade point averages (GPAs) of hypothetical students. When given relevant statistics about GPA distribution, students tended to ignore them if given descriptive information about the particular student, even if the new descriptive information was obviously of little or no relevance to school performance. This finding has been used to argue that interviews are an unnecessary part of the college admissions process because interviewers are unable to pick successful candidates better than basic statistics.

Psychologists Daniel Kahneman and Amos Tversky attempted to explain this finding in terms of the representativeness heuristic. Richard Nisbett has argued that some attributional biases like the fundamental attribution error are instances of the base rate fallacy: people underutilize "consensus information" (the "base rate") about how others behaved in similar situations and instead prefer simpler dispositional attributions.

See also

• Bayesian probability
• Inductive argument
• Misleading vividness

References

• Bar-Hillel, M. (1980). The base-rate fallacy in probability judgments. Acta Psychologica, 44, 211-233.
• Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological Review, 80, 237-251. (summary here)
• Nisbett, R. E., Borgida, E., Crandall, R., & Reed, H. (1976). Popular induction: Information is not always informative. In J. S. Carroll & J. W. Payne (Eds.), Cognition and social behavior, 2, 227-236.

External links

• Psychology of Intelligence Analysis: Base Rate Fallacy

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