Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.

Partial explanations are everywhere. That is, explanations citing causes that explain some but not all of an effect are ubiquitous across science, and these in turn rely on the notion of degree of explanation. I argue that current accounts are seriously deficient. In particular, they do not incorporate adequately the way in which a cause’s explanatory importance varies with choice of explanandum. Using influential recent contrastive theories, I develop quantitative definitions that remedy this lacuna, and relate it to existing measures (...) of degree of causation. Among other things, this reveals the precise role here of chance, as well as bearing on the relation between causal explanation and causation itself. (shrink)

This paper combines the ancient idea that causes necessitate their effects with Angelika Kratzer’s semantics of modality. On the resulting view, causal claims quantify over restricted domains of possible worlds determined by two contextually determined parameters. I argue that this view can explain a number of otherwise puzzling features of the way we use and evaluate causal language, including the difference between causing an effect and being a cause of it, the sensitivity of causal judgements to normative facts, and the (...) semantics of causal disagreements. (shrink)

Judea Pearl has been at the forefront of research in the burgeoning field of causal modeling, and Causality is the culmination of his work over the last dozen or so years. For philosophers of science with a serious interest in causal modeling, Causality is simply mandatory reading. Chapter 2, in particular, addresses many of the issues familiar from works such as Causation, Prediction and Search by Peter Spirtes, Clark Glymour, and Richard Scheines. But philosophers with a more general interest in (...) causation will also profit from reading Pearl’s book, especially the material in chapters 7, 9, and 10, which is self-contained and less technical than other parts of the book. The present review is aimed primarily at readers of the second type. (shrink)

The primary aim of this paper is to analyze the concept of degrees of causal contribution for actual events and examine the way in which it can be formally defined. This should go some way to filling out a gap in the legal and philosophical literature on causation. By adopting the conception of a cause as a necessary element of a sufficient set (the so-called NESS test) we show that the concept of degrees of causation can be given clear and (...) even empirical meaning. We then apply a game theoretical framework to derive a measure of causal contribution. Our favoured measure turns out to be a generalised version of the normalized Penrose-Banzhaf index of voting power. (shrink)

The primary aim of this paper is to analyze the concept of degrees of causal contribution for actual events and examine the way in which it can be formally defined. This should go some way to filling out a gap in the legal and philosophical literature on causation. By adopting the conception of a cause as a necessary element of a sufficient set (the so-called NESS test) we show that the concept of degrees of causation can be given clear and (...) even empirical meaning. We then apply a game theoretical framework to derive a measure of causal contribution. Our favoured measure turns out to be a generalised version of the normalized Penrose–Banzhaf index of voting power. (shrink)

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.

The concept of causation is fundamental to ascribing moral and legal responsibility for events. Yet the precise relationship between causation and responsibility remains unclear. This book clarifies that relationship through an analysis of the best accounts of causation in metaphysics, and a critique of the confusion in legal doctrine. The result is a powerful argument in favour of reforming the moral and legal understanding of how and why we attribute responsibility to agents.

The concept of causation is fundamental to ascribing moral and legal responsibility for events. Yet the precise relationship between causation and responsibility remains unclear. This book clarifies that relationship through an analysis of the best accounts of causation in metaphysics, and a critique of the confusion in legal doctrine.

This paper poses an original puzzle about the relationship between causation and moral responsibility called The Moral Difference Puzzle. Using the puzzle, the paper argues for three related ideas: (1) the existence of a new sort of moral luck; (2) an intractable conflict between the causal concepts used in moral assessment; and (3) inability of leading theories of causation to capture the sorts of causal differences that matter for moral evaluation of agents’ causal contributions to outcomes.