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What is the representativeness heuristic? How does it affect decision making?
The representativeness heuristic is a bias that comes from trying to understand information by categorizing. The problem arises from stereotyping in these situations.
Read on to understand the representativeness heuristic.
The Representativeness Heuristic
The third heuristic Tversky and Kahneman identify is the representativeness heuristic, although it might be better termed the “similarity” heuristic. We use this heuristic when we categorize a phenomenon based on how similar it is to the stereotype of some category.
A simple example concerns our categorization of people based on their appearance. If we come across a diminutive white-haired man wearing glasses and a corduroy blazer and carrying a briefcase, we’re more likely to think “professor” than we are “professional basketball player.”
However, our bias toward “representativeness” becomes dangerous when we confront random processes. We tend to expect random processes to conform to our idea of randomness—as producing unpatterned, impossible-to-predict outcomes. Unfortunately, random processes, especially in the short run, can appear to have causal or predictable results. That means, again because of the “representativeness” heuristic, we ascribe those results to some particular cause rather than chance.
Representative Bias Example
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