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Daniel Kahneman, Paul Slovic, Amos Tversky.
Judgment Under Uncertainty: Heuristics and Biases.
1982

In the last ten years, a great deal of research effort has been devoted to understanding and evaluating the ways in which people judge uncertain events. We now know that people’s intuitive inferences, predictions, probability assessments, and diagnoses do not conform to the laws of probability theory and statistics. Instead, people replace the laws of chance by judgmental strategies or heuristics. Although these are efficient and effective in many circumstances, all too often they lead to judgmental biases that are large, persistent, and serious in their implications for decision making. The blemished portrait of human capabilities that emerges from this work thus stands in sharp contrast to the highly favorable image of “rational man” that dominated the study of thinking and decision making in the two decades following World War II.

The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce, not only in laboratory experiments but in important social, medical, and political situations as well. Individual chapters discuss the representativeness and availability heuristics, problems in judging covariation and control, overconfidence, multistage inference, social perception, medical diagnosis, risk perception, and methods for correcting and improving judgments under uncertainty. About half of the chapters are edited versions of classic articles; the remaining are newly written for this book. Most review multiple studies or entire subareas of research and application rather than describing single experimental studies. This book will be useful to a wide range of students and researchers, as well as to decision makers seeking to gain insight into their judgments and to improve them.