pp. vii-viii

#### Preface

pp. ix-x

In The Graduate, Benjamin Braddock (Dustin Hoffman) is told that the future can be summed up in one word: “Plastics”. I still recall that in roughly 1990, Judea Pearl told me (and anyone else who would listen!) that the future was in causality. I credit Judea with inspiring my interest in causality. ...

#### Chapter 1: Introduction and Overview

pp. 1-8

Causality plays a central role in the way people structure the world. People constantly seek causal explanations for their observations. Why is my friend depressed? Why won’t that file display properly on my computer? Why are the bees suddenly dying? ...

#### Chapter 2: The HP Definition of Causality

pp. 9-76

In this chapter, I go through the HP definition in detail. The HP definition is a formal, mathematical definition. Although this does add some initial overhead, it has an important advantage: it prevents ambiguity about whether A counts as a cause of B. There is no need, as in many other definitions, to try to understand how to interpret the words. ...

#### Chapter 3: Graded Causation and Normality

pp. 77-106

In a number of the examples presented in Chapter 2, the HP definition gave counterintuitive ascriptions of causality. I suggested then that taking normality into account would solve these problems. In this chapter, I fill in the details of this suggestion and show that taking normality into account solves these and many other problems, in what seems to me a natural way. ...

#### Chapter 4: The Art of Causal Modeling

pp. 107-138

In the HP definition of causality, causality is relative to a causal model. X = x can be the cause of ϕ in one causal model and not in another. Many features of a causal model can impact claims of causality. It is clear that the structural equations can have a major impact on the conclusions we draw about causality. ...

#### Chapter 5: Complexity and Axiomatization

pp. 139-168

Is it plausible that people actually work with structural equations and (extended) causal models to evaluate actual causation? People are cognitively limited. If we represent the structural equations and the normality ordering in what is perhaps the most obvious way, the models quickly become large and complicated, even with a small number of variables. ...

#### Chapter 6: Responsibility and Blame

pp. 169-186

Up to now I have mainly viewed causality as an all-or-nothing concept. Although that position is mitigated somewhat by the notion of graded causality discussed in Chapter 3, and by the probabilistic notion of causality discussed in Section 2.5, it is still the case that either A is a cause of B or it is not (in a causal setting (M, u)). ...

#### Chapter 7: Explanation

pp. 187-202

Perhaps the main reason that people are interested in causality is that they want explanations. Consider the three questions I asked in the first paragraph of this book: Why is my friend depressed? Why won’t that file display properly on my computer? Why are the bees suddenly dying? The questions are asking for causes; the answers would provide an explanation. ...

#### Chapter 8: Applying the Definitions

pp. 203-214

In Chapter 1, I said that my goal was to get definitions of notions like causality, responsibility, and blame that matched our natural language usage of these words and were also useful. Now that we are rapidly approaching the end of the book, it seems reasonable to ask where we stand in this project. ...

pp. 215-224

pp. 225-229