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Judgment under Uncertainty: Heuristics and Biases | | Amos Tversky
; Daniel Kahneman
; | | Date: |
27 Sep 1974 | | Journal: | Science, 185 (4157), 1124-1131 | | Abstract: | This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, 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 judgements and decisions in situations of uncertainty. | | Source: | PubMed, pmid17835457 doi: 10.1126/science.185.4157.1124 | | Services: | Forum | Review | Favorites | |
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