Judgment under uncertainty: Heuristics and biases


Authors: 
Tversky, A., & Kahnman, D.
Category: 
Volume: 
185
Pages: 
1124-1131
Year: 
1974
Publisher: 
Science
Abstract: 

This article described three heuristics that are employed in making judgments under uncertainty: (i) representativness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgments and decisions in situations of uncertainty.