Judgment under Uncertainty: Heuristics and Biases

American Association for the Advancement of Science (AAAS) - Tập 185 Số 4157 - Trang 1124-1131 - 1974
Amos Tversky1, Daniel Kahneman1
1Hebrew University, Jerusalem, Israel

Tóm tắt

This article described three heuristics that are employed in making judgments 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 judgments and decisions in situations of uncertainty.

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Tài liệu tham khảo

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Thông tin xuất bản

American Association for the Advancement of Science (AAAS)

Tập 185 Số 4157

1124-1131

Thông tin tác giả