Thinking and Deciding

Citation

Baron, J. (2023). Thinking and Deciding (5th ed.). Cambridge University Press.

Chapter Summary

The fifth edition has twenty chapters in three parts, running to about 550 pages with a preface, references and indexes. The organising idea comes from the opening of Part I: every topic is approached through three questions. The normative question asks by what standards thinking and decisions should be judged. The descriptive question asks how people actually think and what keeps them from meeting those standards. The prescriptive question asks what can be done to improve thinking, for individuals and for society.

Part I, Chapters 1–4: What is thinking?; The study of thinking; Rationality; Logic

Chapter 1 defines thinking, distinguishes thinking about decisions, beliefs and goals, and introduces the search-inference framework, followed by sections on problem solving, expertise, heuristics, and knowledge and understanding. Chapter 2 introduces the three kinds of question (descriptive, prescriptive and normative), the methods of empirical research, and a classification of biases. Chapter 3 explains good thinking as thinking that helps us achieve our goals, with sections on rationality and emotion, rationality and belief, and whether people are ever really irrational. Chapter 4 treats logic as an older normative standard for reasoning, including mental models, errors in logical reasoning and fallacies in informal logic.

Part II, Chapters 5–9: Normative theory of probability; Descriptive theory of probability judgment; Hypothesis testing; Judgment of correlation and contingency; Actively open-minded thinking (AOT)

Chapter 5, "Normative theory of probability", covers what probability is, aleatoric versus epistemic uncertainty, evaluating probability judgments and Bayes' theorem. Chapter 6 turns to the accuracy of probability judgments and to heuristics and biases in probability. Chapter 7 deals with hypothesis testing, first in science and then in psychology. Chapter 8 covers judgment of correlation and contingency, including attentional bias and illusory correlation. Chapter 9 introduces actively open-minded thinking, with sections on myside bias, irrational belief persistence and individual differences.

Part III, Chapters 10–14: Choice under uncertainty: Normative theory; Choice under uncertainty; Risk; Choice under certainty; Utility measurement

Chapter 10 presents expected-utility theory as the normative model of choice under uncertainty and explains why it is normative. Chapter 11 sets out the descriptive picture: experienced, predicted and decision utility, prospect theory, emotional effects of outcomes, and the ambiguity effect. Chapter 12 applies this to risk, including risk regulation, insurance and protective behaviour. Chapter 13 deals with choice under certainty, covering preference reversals, effects of the available options, and mental accounting with its sub-topics such as the endowment effect, default bias and the sunk-cost effect. Chapter 14 is about measuring utility, with methods from simple direct judgment to standard gambles, time trade-off and contingent valuation.

Part III, Chapters 15–16: Decision analysis and values; Quantitative judgment

Chapter 15 covers fundamental versus means values, discovering values, multiattribute utility theory, rules and trade-offs, and the value of human life. Chapter 16 treats quantitative judgment through multiple linear regression, the lens model, improving human judgment, the mechanism of judgment and classification by similarity to exemplars.

Part III, Chapters 17–19: Moral judgment and choice; Fairness and justice; Social dilemmas

Chapter 17 asks what moral judgments are, compares utilitarian and deontological views, and discusses protected values and omission bias. Chapter 18 takes up equity theory, intuitions about fair allocation and negotiation. Chapter 19 covers social dilemmas, from laboratory versions such as the prisoner's dilemma to motives, trust, voters' illusions, parochialism and solutions.

Chapter 20: Decisions about the future

The last chapter covers the choice of personal goals, good and bad reasons for sticking to plans, discounting, self-control, emotions and time, and the relation between morality and prudence.

Key Concepts

Part I

• Search-inference framework: the book's account of thinking as search followed by inference, introduced in Chapter 1.
• Normative, descriptive and prescriptive models: the three questions that organise every topic in the book.
• Rationality: thinking that helps people achieve their goals, rather than thinking without emotion.

Part II

• Aleatoric and epistemic uncertainty: the two kinds of uncertainty distinguished in Chapter 5.
• Bayes' theorem: the normative rule for updating probability judgments.
• Myside bias and actively open-minded thinking: bias in favour of one's own position, and the disposition that counters it.

Part III

• Expected-utility theory and prospect theory: the normative model of choice under uncertainty and the leading descriptive account of departures from it.
• Mental accounting: reference points, defaults, sunk costs and the endowment effect.
• Multiattribute utility and the lens model: formal tools for analysing values and for comparing judgment with a statistical model.
• Utilitarianism and omission bias: a normative theory of moral choice and a bias in moral judgment.
• Discounting and self-control: how people weigh the present against the future.

Critical Analysis

Strengths

• A consistent organising scheme. The three questions that Part I sets out are asked of each topic, and the contents show it: chapters often come in pairs, such as the normative theory of probability followed by the descriptive theory, and expected-utility theory followed by the account of actual choice.
• Breadth. The book covers logic, probability, hypothesis testing, utility, risk, moral judgment, fairness, social dilemmas and decisions about the future in one text, so it can serve as a single reference for the field.
• Accessible prerequisites. The publisher states that the book assumes no particular prerequisites beyond introductory high-school algebra, while addressing advanced undergraduates, early graduate students and researchers in fields such as business, politics, law, medicine, economics and philosophy.
• An established author and edition. This is the fifth edition, and the author taught at the University of Pennsylvania from 1974 to 2013 and is founding co-editor of the journal Judgment and Decision Making, according to the publisher's biography.

Limitations

• Long and encyclopedic. At about 550 pages, with Part III the longest part at eleven of the twenty chapters, the book works better as a reference or a two-semester course than as a quick introduction. Chapters 13 and 14 alone list about two dozen numbered subsections.
• Normative commitments. Chapters 10 and 17 present expected-utility theory and utilitarianism as normative models, and later chapters evaluate behaviour against them. Readers who reject those standards will need to read other sources on rationality.

Where It Fits in the Course

In the judgment and decision-making course, Baron is the comprehensive textbook, a place to go after a shorter introduction. Jonathan Evans's Thinking and Reasoning: A Very Short Introduction and Hastie and Dawes's Rational Choice in an Uncertain World are gentler first surveys of how people judge and choose, and Kahneman's Thinking, Fast and Slow and Thaler and Sunstein's Nudge are trade books that present the heuristics-and-biases tradition and its policy applications in narrative form.

Bazerman and Moore's Judgment in Managerial Decision Making is a shorter textbook for readers who make decisions in organisations, and Gigerenzer, Todd and the ABC Research Group's Simple Heuristics That Make Us Smart is a research monograph that argues for fast and frugal heuristics. After Baron, the natural next step is the primary literature on the topic of greatest interest.

How to Use This Book

The book suits advanced undergraduates, early graduate students and researchers, and it can also be read by readers in applied fields. The publisher says no prerequisite beyond introductory high-school algebra is needed; an introductory course in cognitive psychology or decision making helps, as does comfort with basic probability for Part II and Chapters 10 to 12.

A practical plan:

• Core: Part I (Chapters 1 to 3) in full, since it introduces the framework, then Chapters 5, 6, 10, 11 and 13 for the central contrast between normative theory and observed behaviour in probability and choice.
• Extensions: Chapters 7 to 9 on hypothesis testing, correlation and open-minded thinking for readers interested in belief formation; Chapters 12, 14 and 15 for risk, utility measurement and decision analysis.
• Social and moral topics: Chapters 17 to 19, which can be read independently of the probability chapters.
• Closing: Chapter 20 for readers interested in planning, discounting and self-control.
• Study approach: For each topic, write down the normative standard, the pattern of departure and any prescriptive remedy. The book's own three-question scheme is a good structure for notes.