Rational Choice in an Uncertain World: The Psychology of Judgment and Decision Making

Citation

Hastie, R., & Dawes, R. M. (2010). Rational Choice in an Uncertain World: The Psychology of Judgment and Decision Making (2nd ed.). SAGE Publications.

Chapter Summary

A textbook of 14 chapters (about 374 pages) on judgment and decision making. SAGE describes it as comparing the basic principles of rationality with actual behaviour, presenting theories and findings in a non-technical way with anecdotes as a teaching device, and aimed at advanced undergraduates and graduate students. The second edition adds chapter introductions, conclusions and cross-references, many examples from finance, medicine, law and engineering, and more weight on descriptive psychological models alongside the normative expected-utility approach. The notes below follow the section headings in the published contents.

Chapters 1–2: Thinking and Deciding; What Is Decision Making?

Chapter 1 argues that decision making is a skill and moves through automatic and controlled thinking, the computational model of the mind, and the passage from psychoanalytic theory and behaviourism to cognition, ending with the quality of choice (rationality) and the invention of modern decision theory. Chapter 2 defines a decision, shows ways of picturing decisions, and uses a legal example of incomplete thinking and sunk costs as over-inclusive thinking, before arguing for considering only the future and outlining the rest of the book.

Chapter 3: A General Framework for Judgment

Introduces a conceptual framework for judgment and prediction through the lens model, and research using it. Sections cover capturing judgment in statistical models, why those models beat human judgment, practical implications of the success of the linear model, and objections and rebuttals.

Chapters 4–6: Anchoring and Adjustment; Judging Heuristically; Explanation-Based Judgments

Chapter 4 treats anchoring and insufficient adjustment, including anchoring on ourselves and anchoring the past in the present. Chapter 5 covers heuristics for estimating frequencies and probabilities: availability (memory and imagination), judgment by similarity, representativeness and the ratio rule. Chapter 6 shifts to judgments based on stories and explanations, including the conjunction error, legal scenarios, hindsight, and scenarios about ourselves and the unthinkable.

Chapters 7–8: Chance and Cause; Thinking Rationally About Uncertainty

Chapter 7 covers misconceptions about chance, illusions of control, seeing causal structure where there is none, and regression toward the mean. Chapter 8 turns from errors to remedies: thinking in probabilities, inverse probabilities, avoiding subadditivity and conjunction errors, disjunctions, Bayes's theorem and statistical decision theory.

Chapters 9–10: Evaluating Consequences: Fundamental Preferences; From Preferences to Choices

Chapter 9 asks what happiness is worth and covers emotions in evaluation, the value of money, decision utility and the construction of values. Chapter 10 concerns deliberate choices among complex alternatives: ordering, grouping and choosing alternatives, and how to make good choices.

Chapters 11–12: A Rational Decision Theory; A Descriptive Decision Theory

Chapter 11 defines rationality formally, explains the axiomatic method and expected utility theory, and discusses traditional objections to the axioms and criticisms of decision analysis. Chapter 12 presents non-expected-utility theories, gain–loss framing effects and loss aversion.

Chapters 13–14: What's Next? New Directions in Research on Judgment and Decision Making; In Praise of Uncertainty

Chapter 13 surveys the neuroscience of decisions, emotions in decision making and dynamic decision experiments. Chapter 14 argues that uncertainty is not only negative, discusses the cost of denying it and ends by proposing ways of living with uncertainty.

Key Concepts

Chapters 1–8

• Lens model: a framework for analysing how judgments relate to the cues available.
• Linear models versus human judgment: statistical models often outperform unaided judges.
• Anchoring and adjustment, availability, representativeness: judgment heuristics and their biases.
• Regression toward the mean and illusions of control: misreadings of chance.
• Bayes's theorem: the rule for changing one's mind in light of evidence.

Chapters 9–14

• Decision utility and constructed values: how preferences are evaluated and formed.
• Expected utility theory: the axiomatic account of rational choice.
• Loss aversion and framing: core elements of descriptive theory.
• Neuroscience and emotion in decisions: the new directions in Chapter 13.

Critical Analysis

Strengths

• Balances rational and descriptive views. SAGE describes the book as balancing the cognitive-psychological analysis of heuristics, descriptive judgment models and rational models, and the contents give space to errors (Chapters 4–7), remedies (Chapter 8) and both rational and descriptive theory (Chapters 11–12).
• Student-friendly in design. The second edition adds chapter introductions, conclusions and cross-references, and uses examples from finance, medicine, law and engineering.
• Detailed structure. The published contents list sections within every chapter, so a reader can find a topic such as regression to the mean, hindsight or Bayes's theorem directly.
• Respected authors. Reviewers quoted by SAGE (Robert Goldstone, William Goldstein) praise the systematic scholarship, breadth and writing style.

Limitations

• Long for an introduction. With 14 chapters and about 374 pages, it is a substantial course text rather than a short primer.
• Formal theory in later chapters. Chapters 8 and 11 on probability, Bayes's theorem and the axiomatic method need a willingness to follow technical arguments, even though SAGE calls the treatment non-technical.
• Dated to its edition. The 2010 date means the new-directions chapter reflects research up to then; neuroscience and emotion topics have developed since.

Where It Fits in the Course

Among the judgment and decision making books, this is the most systematic first textbook, and it sits between the very short and the technical. Evans's Thinking and Reasoning: A Very Short Introduction is a compact overview and a good preliminary, and Kahneman's Thinking, Fast and Slow and Thaler and Sunstein's Nudge are trade books that cover heuristics, biases and choice design for general readers. Bazerman and Moore's Judgment in Managerial Decision Making is a short text applying the heuristics-and-biases tradition to decisions in organisations.

Baron's Thinking and Deciding is a comprehensive text built on normative, descriptive and prescriptive models and is the natural step after or alongside Hastie and Dawes, while Gigerenzer, Todd and the ABC Research Group's Simple Heuristics That Make Us Smart is a research monograph that argues for the accuracy of simple heuristics and offers a counterweight to the errors-focused chapters here.

How to Use This Book

SAGE targets advanced undergraduates and graduate students. Chapter 8 includes a section on getting started thinking in terms of probabilities, which suggests that probability is introduced in the text rather than assumed.

A practical plan: read Chapters 1–2 for the framework, then Chapters 3–7 as the core of the errors-and-heuristics material. Read Chapter 8 slowly, working the probability examples, before Chapters 9–12, which move to preferences and formal and descriptive decision theory. Chapters 13 and 14 can be read last as outlook, and a short course could skip parts of Chapters 10–11. Use the chapter conclusions and cross-references to revisit ideas, and compare its account of heuristics with a primary text such as Kahneman's.