Are the assumptions on this project sufficiently robust?
Will the economy grow in the coming months?
Is the person I want to hire sufficiently skilled to manage the role effectively?
Questions like these dot our day: our effectiveness in making appropriate assessments depends on the outcome of situations, sometimes very complex.
This book will help you understand how people make judgments from which they base their decisions. The ones who revolutionized studies of the formation of human judgment were Kahneman and Tversky in the 1970s, who introduced their heuristics and biases approach and challenged the strictly rational models that dominated research at the time.
Their work unfolded over decades and led in 2002 to Kahneman, one of the founders of behavioural economics, being awarded the Nobel Prize in economics for integrating findings from psychological research into economic science, especially concerning human judgment and decision theory under conditions of uncertainty.
Their research highlighted the reflexive mental operations employed to make complex problems manageable and highlighted how the same processes can lead to both accurate and dangerously erroneous judgments.
The heuristics and biases framework has generated huge amounts of research in psychology, which has profoundly influenced studies in economics, law, medicine, management, and political science.
Daniel Kahneman’s studies enabled the application of research in cognitive psychology to understand economic decision-making; he collaborated extensively with Amos Tversky, showing how human decisional processes systematically violate some principles of rationality, while microeconomic theories assume that the decision behaviour should be rational and maximize usefulness.
This book collects research that has most influenced the shaping of what we now know as heuristics and biases since the first collection in 1982 (by Kahneman, Slovic, and Tversky): the different papers develop and critically analyze the initial work, integrate it with emerging theory and empirical findings, and extend the framework to new real-world applications.
It is the chapter on real-world applications the book finds all its interest in, giving a tangible measure of how easy it is to incur misjudgments and make even major mistakes.
Want to know more about the errors we can make?
Listen to Daniel Kahneman in this short video, then go to the contents.
Editors
Thomas Gilovich
Professor of Psychology at Cornell University, member of the Cornell Center for Behavioral Economics and Decision Research
Dale Griffin
Associate Professor at the Graduate School of Business, Stanford University
Daniel Kahneman
Eugene Higgins Professor of Psychology and Professor of Public Affairs at the Woodrow Wilson School of Public Affairs, Princeton University
Contents
Introduction – Heuristics and Biases: Then and Now (Thomas Gilovich and Dale Griffin)
PART ONE. THEORETICAL AND EMPIRICAL EXTENSIONS
A. Representativeness and Availability
Extensional versus Intuitive Reasoning: The Conjunction Fallacy in Probability Judgment (Amos Tversky and Daniel Kahneman)
Representativeness Revisited: Attribute Substitution in Intuitive Judgment (Daniel Kahneman and Shane Frederick)
How Alike Is It? versus How Likely Is It?: A Disjunction Fallacy in Probability Judgments (Maya Bar-Hillel and Efrat Neter)
Imagining Can Heighten or Lower the Perceived Likelihood of Contracting a Disease: The Mediating Effect of Ease of Imagery (Steven J. Sherman, Robert B. Cialdini, Donna F. Schwartzman, and Kim D. Reynolds)
The Availability Heuristic Revisited: Ease of Recall and Content of Recall as Distinct Sources of Information (Norbert Schwarz and Leigh Ann Vaughn)
B. Anchoring, Contamination, and Compatibility
Incorporating the Irrelevant: Anchors in Judgments of Belief and Value (Gretchen B. Chapman and Eric J. Johnson)
Putting Adjustment Back in the Anchoring and Adjustment Heuristic (Nicholas Epley and Thomas Gilovich)
Self-Anchoring in Conversation: Why Language Users Do Not Do What They “Should” (Boaz Keysar and Dale J. Ban)
Inferential Correction (Daniel T. Gilbert)
Mental Contamination and the Debiasing Problem (Timothy D. Wilson, David B. Centerbar, and Nancy Brekke)
Sympathetic Magical Thinking: The Contagion and Similarity “Heuristics” (Paul Rozin and Carol Nemeroff)
Compatibility Effects in Judgment and Choice (Paul Slovic, Dale Griffin, and Amos Tversky)
C. Forecasting, Confidence, and Calibration
The Weighing of Evidence and the Determinants of Confidence (Dale Griffin and Amos Tversky)
Inside the Planning Fallacy: The Causes and Consequences of Optimistic Time Predictions (Roger Buehler, Dale Griffin, and Michael Ross)
Probability Judgment across Cultures (J. Frank Yates, Ju-Whei Lee, Winston R. Sieck, Incheol Choi, and Paul C. Price)
Durability Bias in Affective Forecasting (Daniel T Gilbert, Elizabeth C. Pinel, Timothy D. Wilson, Stephen J. Blumberg, and Thalia P. Wheatley)
D. Optimism
Resistance of Personal Risk Perceptions to Debiasing Interventions (Neil D. Weinstein and William M. Klein)
Ambiguity and Self-Evaluation: The Role of Idiosyncratic Trait Definitions In Self-Serving Assessments of Ability (David Dunning, Judith A. Meyerowitz, and Amy D. Holzberg)
When Predictions Fail: The Dilemma of Unrealistic Optimism (David A. Armor and Shelley E. Taylor)
E. Norms and Counterfactuals
Norm Theory: Comparing Reality to Its Alternatives (Daniel Kahneman and Dale T. Miller)
Counterfactual Thought, Regret, and Superstition: How to Avoid Kicking Yourself (Dale T. Miller and Brian R. Taylor)
PART TWO. NEW THEORETICAL DIRECTIONS
A. Two Systems of Reasoning
Two Systems of Reasoning (Steven A. Sloman)
The Affect Heuristic (Paul Slovic, Melissa Finucane, Ellen Peters, and Donald G. MacGregor)
Individual Differences in Reasoning: Implications for the Rationality Debate? (Keith E. Stanovich and Richard F. West)
B. Support Theory
Support Theory: A Nonextensional Representation of Subjective Probability (Amos Tversky and Derek J. Koehler)
Unpacking, Repacking, and Anchoring: Advances in Support Theory (Yuval Rottenstreich and Amos Tversky)
Remarks on Support Theory: Recent Advances and Future Directions (Lyle A. Brenner, Derek J. Koehler, and Yuval Rottenstreich)
C. Alternative Perspectives on Heuristics
The Use of Statistical Heuristics in Everyday Inductive Reasoning (Richard E. Nisbett, David H. Krantz, Christopher Jepson, and Ziva Kunda)
Feelings as Information: Moods Influence Judgments and Processing Strategies (Norbert Schwarz)
Automated Choice Heuristics (Shane Frederick)
How Good Are Fast and Frugal Heuristics? (Gerd Gigerenzer, Jean Czerlinski, and Laura Martignon)
Intuitive Politicians, Theologians, and Prosecutors: Exploring the Empirical Implications of Deviant Functionalist Metaphors (Philip E. Tetlock)
PART THREE. REAL-WORLD APPLICATIONS
A. Everyday Judgment and Behavior
The Hot Hand in Basketball: On the Misperception of Random Sequences (Thomas Gilovich, Robert Vallone, and Amos Tversky)
Like Goes with Like: The Role of Representativeness In Erroneous and Pseudo-Scientific Beliefs (Thomas Gilovich and Kenneth Savitsky)
When Less Is More: Counterfactual Thinking and Satisfaction among Olympic Medalists (Victoria Husted Medvec, Scott F. Madey, and Thomas Gilovich)
Understanding Misunderstanding: Social Psychological Perspectives (Emily Pronin, Carolyn Puccio, and Lee Ross)
B. Expert Judgment
Assessing Uncertainty in Physical Constants (Max Henrion and Baruch Fischhoff)
Do Analysts Overreact? (Werner P. M. De Bondt and Richard H. Thaler)
The Calibration of Expert Judgment: Heuristics and Biases Beyond the Laboratory (Derek J. Koehler, Lyle Brenner, and Dale Griffin)
Clinical versus Actuarial Judgment (Robyn M. Dawes, David Faust, and Paid E. Meehl)
Heuristics and Biases in Application (Baruch Fischhoff)
Theory-Driven Reasoning about Plausible Pasts and Probable Futures In World Politics (Philip E. Tetlock)