Judgment Under Uncertainty

Judgment Under Uncertainty

Judgment Under Uncertainty

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 chapters 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.

Judgment Under Uncertainty

Judgment Under Uncertainty

Judgment Under Uncertainty

Amos Tversky and Daniel Kahneman's 1974 paper 'Judgement Under Uncertainty: Heuristics and Biases'is a landmark in the history of psychology. Though a mere seven pages long, it has helped reshape the study of human rationality, and had a particular impact on economics - where Tversky and Kahneman's work helped shape the entirely new sub discipline of 'behavioral economics.' The paper investigates human decision-making, specifically what human brains tend to do when we are forced to deal with uncertainty or complexity. Based on experiments carried out with volunteers, Tversky and Kahneman discovered that humans make predictable errors of judgement when forced to deal with ambiguous evidence or make challenging decisions. These errors stem from 'heuristics' and 'biases' - mental shortcuts and assumptions that allow us to make swift, automatic decisions, often usefully and correctly, but occasionally to our detriment. The paper's huge influence is due in no small part to its masterful use of high-level interpretative and analytical skills - expressed in Tversky and Kahneman's concise and clear definitions of the basic heuristics and biases they discovered. Still providing the foundations of new work in the field 40 years later, the two psychologists' definitions are a model of how good interpretation underpins incisive critical thinking.

Judgment under Uncertainty

Judgment under Uncertainty

Judgment under Uncertainty

Amos Tversky and Daniel Kahneman’s 1974 paper ‘Judgement Under Uncertainty: Heuristics and Biases’ is a landmark in the history of psychology. Though a mere seven pages long, it has helped reshape the study of human rationality, and had a particular impact on economics – where Tversky and Kahneman’s work helped shape the entirely new sub discipline of ‘behavioral economics.’ The paper investigates human decision-making, specifically what human brains tend to do when we are forced to deal with uncertainty or complexity. Based on experiments carried out with volunteers, Tversky and Kahneman discovered that humans make predictable errors of judgement when forced to deal with ambiguous evidence or make challenging decisions. These errors stem from ‘heuristics’ and ‘biases’ – mental shortcuts and assumptions that allow us to make swift, automatic decisions, often usefully and correctly, but occasionally to our detriment. The paper’s huge influence is due in no small part to its masterful use of high-level interpretative and analytical skills – expressed in Tversky and Kahneman’s concise and clear definitions of the basic heuristics and biases they discovered. Still providing the foundations of new work in the field 40 years later, the two psychologists’ definitions are a model of how good interpretation underpins incisive critical thinking.

Professional Judgment

Professional Judgment

Professional Judgment

Policy-capturing models, data-based aids, expert systems and decision analysis are the main decision-making techniques introduced here, with attention to their methodological bases and practical evaluation.

Decision Making Under Uncertainty

Decision Making Under Uncertainty

Decision Making Under Uncertainty

Introduction and basic concepts; Models and probability; Choices and preferences; Preference assessment procedures; Behavioral assumptions and limitations of decision analysis; Risk sharing and incentives; Choices with multiple attributes.