JUDGMENT UNDER UNCERTAINTY - HEURISTICS AND BIASES
JUDGMENT UNDER UNCERTAINTY - HEURISTICS AND BIASES
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DOI：
10.1126/science.185.4157.1124
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发表时间：
1974-01-01
期刊：
影响因子：
56.9
通讯作者：
KAHNEMAN, D
中科院分区：
文献类型：
--
作者：
TVERSKY, A;KAHNEMAN, D
本文描述了在不确定性条件下做出判断时使用的三种启发式方法：(i)代表性，通常在要求人们判断物体或事件A属于类或过程B的概率时使用；（ii）实例或场景的可获得性，当人们被要求评估某类课程的频率或某一特定发展的合理性时，通常使用实例或场景；（iii）锚点的平差，当有相关值时，通常用于数值预测。这些启发式方法非常经济，通常也很有效，但它们会导致系统性和可预测的错误。更好地理解这些启发式和它们所导致的偏见，可以在不确定的情况下改善判断和决策。
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.