There have been a number of explanations proposed for why the base rate fallacy occurs. One of the main theories posits that it is a matter of relevance, such that we ignore base rate information because we classify it as irrelevant and therefore feel that it should be ignored. It has also been suggested that the base rate fallacy results from the representativeness heuristic.
Maya Bar-Hillel’s 1980 paper, “The base-rate fallacy in probability judgments”5 addresses the limitations of previous theories of base rate fallacy and presents an alternate explanation: relevance. Specifically, we ignore base rate information because we believe it to be irrelevant to the judgment we are making. Bar-Hillel contends that, prior to making a judgment, we categorize the information given to us into different levels of relevance. If something is deemed irrelevant, we discard it and do not factor it into the conclusion we draw. Thus, it is not that we are incapable of integrating different types of information; if two types of information are assigned equal relevance, we will give them equal consideration. It is misattributions of relevance that cause us to ignore vital information, value certain information more than we should, or focus on one source of information when we should be integrating multiple.
Furthermore, Bar-Hillel explains that part of what makes us view certain pieces of information as more relevant than others is specificity. The more specific information is to the situation at hand, the more relevant it seems. Individuating information is, by nature, incredibly specific. As such, we denote it as highly relevant. Base rate information, on the other hand, is very general. We categorize it as low relevance information. In making a judgment, we take into consideration the information we consider to be relevant and ignore that which has been deemed irrelevant. To us, this may feel like an effective strategy, but it can actually compromise the accuracy of our judgments.
Bar-Hillel contends that representativeness is not a sufficient explanation for why the base rate fallacy occurs, as it cannot account for this fallacy in all contexts.6 That being said, representativeness may be one of the factors that contributes to the base rate fallacy, specifically in cases like the Tom W. study described by Kahneman and Tversky.7
Heuristics are mental shortcuts we use to facilitate judgment and decision-making. The representativeness heuristic, which was introduced by Kahneman and Tversky, describes our tendency to judge the probability of something based on the extent to which the object or event in question is similar to the prototypical exemplar of the category it falls into. We mentally categorize objects and events, grouping them based on similar features. Each category has a prototype, which is the average example of all the objects and events sorted into that category. The more the object or event resembles that prototype, the more representative of that category we judge it to be. The more representative it is, the more likely we believe its outcomes will align with those of the prototype.8
The representativeness heuristic can give rise to the base rate fallacy, as we may view an event or object as extremely representative and make a probability judgment based solely off of that, without stopping to consider base rate values. To refer back to Tom W., judgments about his field of study were inferred from his appearance and personality. He was deemed to be representative of a computer science graduate student, thereby leading participants to rank him as more likely to be pursuing studies in that field than in programs with far greater enrolment rates. Since there were far more students in both education and humanities than in computer science, it was more probable that he was studying the former, rather than the later. Yet, representativeness caused participants to overlook the base rate information, which proved to be essential.