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Judgment under uncertainty: heuristics and biases

Editor(s): Daniel Kahneman, Paul Slovic, Amos Tversky
Year Published: 1986
Description:

This is a classic textbook written by three well known authors (Kahneman recently won the Nobel Prize for economics) who have spent their careers working in the psychological fields of understanding how people make decisions under uncertainty. The introduction to this edited volume identifies three heuristics (in other words, rules of thumb) that are employed in making judgments under uncertainty: representativeness, availability, and adjustment from an anchor. Representativeness is used when people are asked to judge whether one thing belongs to another thing, is representative of another thing, or resembles another thing. Availability is used when people assess the frequency or probability of an event by the ease in which occurrences come to mind. Adjustment from an anchor is used when people make numerical estimates by starting from an initial available value. While these heuristics can be effective, the authors argue that they can also lead to predictable biases and errors. Therefore, they propose a better understanding of these heuristics and their biases in order to improve judgments and decisions in uncertain situations. There are 10 parts in this volume, which aim to provide a comprehensive sample of judgmental heuristics and their effects. The first part provides a review of heuristics and biases of intuitive judgments. Part II discusses the representative heuristic and Part III deals primarily with problems of causal attribution (extending from the representative heuristic). Part IV discusses the availability heuristic and social judgment. Part V illustrates the perception and learning of judgments of lay people and experts. Part VI describes probability assessors and overconfidence in prediction and explanation. Part VII discusses multistage inference biases. Part VIII describes procedures for correcting and improving judgment. Part IX summarizes the effects of judgmental biases in the perception of risk. And finally, Part X discusses conceptual and methodological issues involved in the study of heuristics and biases. This book is oriented toward academic audiences, but that shouldn’t sway people from looking into it, particularly if they want to gain a deeper understanding of the heuristics and biases. Notable chapters include those on learning from experience, hindsight bias, and understanding perceived risk.

Citation: Kahneman D, Slovic P, Tversky A. eds. 1986. Judgment under uncertainty: heuristics and biases. New York: Cambridge University Press, 544 p.
Topic(s): Risk
Ecosystem(s): None
Document Type: Book or Chapter or Journal Article
NRFSN number: 15910
Record updated: Nov 27, 2017