• DOI:10.1126/science.185.4157.1124
• Corpus ID: 143452957

Judgment under Uncertainty: Heuristics and Biases

@article{Tversky1974JudgmentUU,
  title={Judgment under Uncertainty: Heuristics and Biases},
  author={Amos Tversky and Daniel Kahneman},
  journal={Science},
  year={1974},
  volume={185},
  pages={1124 - 1131}
}

• A. Tversky, D. Kahneman
• Published 27 September 1974
• Economics
• Science

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.