Humans often attribute the things that happen to one or another actual cause. In this chapter, we survey some recent philosophical and psychological research on causal attribution. We pay special attention to the relation between graphical causal modeling and theories of causal attribution. We think that the study of causal attribution is one place where formal and experimental techniques nicely complement one another.

Recent work in psychology and experimental philosophy has shown that judgments of actual causation are often influenced by consideration of defaults, typicality, and normality. A number of philosophers and computer scientists have also suggested that an appeal to such factors can help deal with problems facing existing accounts of actual causation. This article develops a flexible formal framework for incorporating defaults, typicality, and normality into an account of actual causation. The resulting account takes actual causation to be both graded and (...) comparative. We then show how our account would handle a number of standard cases. 1 Introduction2 Causal Models3 The HP Definition of Actual Causation4 The Problem of Isomorphism5 Defaults, Typicality, and Normality6 Extended Causal Models7 Examples7.1 Omissions7.2 Knobe effects7.3 Causes versus background conditions7.4 Bogus prevention7.5 Causal chains7.6 Legal doctrines of intervening causes7.7 Pre-emption and short circuits8 Conclusion. (shrink)

This paper explores the prospects of employing a functional approach in order to improve our concept of actual causation. Claims of actual causation play an important role for a variety of purposes. In particular, they are relevant for identifying suitable targets for intervention, and they are relevant for our practices of ascribing responsibility. I argue that this gives rise to the _challenge of purpose_. The challenge of purpose arises when different goals demand adjustments of the concept that pull in opposing (...) directions. More specifically, I argue that a common distinction between certain kinds of preempted and preempting factors is difficult to motivate from an interventionist viewpoint. This indicates that an appropriately revised concept of actual causation would not distinguish between these two kinds of factors. From the viewpoint of retributivist responsibility, however, the distinction between preempted and preempting factors sometimes is important, which indicates that the distinction should be retained. (shrink)

In the hopes of finding supporting evidence for various accounts of actual causation, many philosophers have recently turned to psychological findings about the influence of norms on counterfactual cognition. Surprisingly little philosophical attention has been paid, however, to the question of why considerations of normality should be relevant to counterfactual cognition to begin with. In this paper, I follow two aims. First, against the methodology of two prominent psychological accounts, I argue for a functional approach to understanding the selectivity of (...) counterfactual cognition. Second, I take some steps towards a systematic analysis by providing a qualitative, decision‐theoretic account of one important function of counterfactual thinking, namely, inferring, in the face of undesirable outcomes, corrective policies that prevent the occurrence of similar outcomes in future circumstances. I make a case for employing this analysis by (a) showing its value for assessing the rationality of imagination‐driven counterfactual generation, (b) highlighting its use for making sense of practices in history and policy analysis where counterfactual selection plays a central role, and (c) demonstrating its diagnostic value for identifying areas where counterfactual generation may lead us into epistemic and ethical troubles. (shrink)

This chapter presents an opinionated account of how to understand the contributions of experience, especially with respect to the role of cognitive science, in developing and assessing metaphysical theories of reality. I develop a methodological basis for the idea that, independently of work in experimental philosophy focused on explications of concepts, contemporary metaphysical theories with a role for experiential evidence can be fruitfully connected to empirical work in psychology, especially cognitive science. My argument is not that cognitive science should replace (...) the metaphysician’s use of a priori theorizing and ordinary experience as a guide to metaphysical reality. Rather, we should enrich our perspective on a priori theorizing and ordinary experience as a guide to metaphysical reality by drawing on any relevant work in cognitive science. (shrink)

Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...) psychology. Despite the ubiquity of causal reasoning, textbooks of cognitive psychology have neglected this growing field. The goal of The Oxford Handbook of Causal Reasoning is to fill this gap. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields. 1. Causal Reasoning: An Introduction Michael R. Waldmann Part I: Theories of Causal Cognition 2. Associative Accounts of Causal Cognition Mike E. Le Pelley, Oren Griffiths, and Tom Beesley 3. Rules of Causal Judgment: Mapping Statistical Information Onto Causal Beliefs José C. Perales, Andrés Catena, Antonio Cándido, and Antonio Maldonado 4. The Inferential Reasoning Theory of Causal Learning: Toward a Multi- Process Propositional Account Yannick Boddez, Jan De Houwer, and Tom Beckers 5. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World: Generalizing the Invariance of Causal Power Patricia W. Cheng and Hongjing Lu 6. The Acquisition and Use of Causal Structure Knowledge Benjamin Margolin Rottman 7. Formalizing Prior Knowledge in Causal Induction Thomas L. Griffiths 8. Causal Mechanisms Samuel G. B. Johnson and Woo-kyoung Ahn 9. Force Dynamics and Causation Phillip Wolff and Robert Thorstad 10. Mental Models and Causation P. N. Johnson- Laird and Sangeet S. Khemlani 11. Pseudocontingencies Klaus Fiedler and Florian Kutzner 12. Singular Causation David Danks 13. Cognitive Neuroscience of Causal Reasoning Joachim T. Operskalski and Aron K. Barbey Part II: Basic Cognitive Functions 14. Visual Impressions of Causality Peter White 15. Goal-Directed Actions Bernhard Hommel 16. Planning and Control Magda Osman 17. Reinforcement Learning and Causal Models Samuel J. Gershman 18. Causation and the Probability of Causal Conditionals David E. Over 19. Causal Models and Conditional Reasoning Mike Oaksford and Nick Chater 20. Concepts as Causal Models: Categorization Bob Rehder 21. Concepts as Causal Models: Induction Bob Rehder 22. Causal Explanation Tania Lombrozo and Nadya Vasilyeva 23. Diagnostic Reasoning Björn Meder and Ralf Mayrhofer 24. Inferring Causal Relations by Analogy Keith J. Holyoak and Hee-Seung Lee 25. Causal Argument Ulrike Hahn, Roland Bluhm, and Frank Zenker 26. Causality in Decision- Making York Hagmayer and Philip M. Fernbach Part III: Domains of Causal Reasoning 27. Intuitive Theories Tobias Gerstenberg and Joshua B. Tenenbaum 28. Space, Time, and Causality Marc J. Buehner 29. Causation in Legal and Moral Reasoning David A. Lagnado and Tobias Gerstenberg 30. The Role of Causal Knowledge in Reasoning About Mental Disorders Woo-kyoung Ahn, Nancy S. Kim, and Matthew S. Lebowitz 31. Causality and Causal Reasoning in Natural Language Torgrim Solstad and Oliver Bott 32. Social Attribution and Explanation Denis Hilton Part IV: Development, Phylogeny, and Culture 33. The Development of Causal Reasoning Paul Muentener and Elizabeth Bonawitz 34. Causal Reasoning in Non-Human Animals Christian Schloegl and Julia Fischer 35. Causal Cognition and Culture Andrea Bender, Sieghard Beller, and Douglas L. Medin. (shrink)

There have been several recent attempts to model ordinary intuitions about actual causation by combining a counterfactual definition of the causal relation with an abnormality-based account of causal judgments. In these models, the underlying psychological theory is that people automatically focus on abnormal events when judging the actual causes of an effect. This approach has enabled authors such as Halpern and Hitchcock to capture an impressive array of ordinary causal intuitions. However, in this paper I demonstrate how these abnormality-based accounts (...) still systematically fail to predict ordinary causal judgments in specific types of scenarios: those in which the effect is normal. I will argue that the reason for this is that the underlying psychological theory is wrong: the idea that intuitive actual causes are abnormal events is only partially correct. To model ordinary judgments more realistically, researchers working in this area must adopt a more plausible underlying psychological theory: the correspondence hypothesis about judgments of actual causation. One of the consequences of this correspondence hypothesis is that normal effects are judged to have normal causes. (shrink)

Cognitive Science, Volume 46, Issue 5, May 2022.

When comparing the roles of the lightning strike and the dry climate in causing the forest fire, one might think that the lightning strike is more of a cause than the dry climate, or one might think that the lightning strike completely caused the fire while the dry conditions did not cause it at all. Psychologists and philosophers have long debated whether such causal judgments are graded; that is, whether people treat some causes as stronger than others. To address this (...) debate, we first reanalyzed data from four recent studies. We found that causal judgments were actually multimodal: although most causal judgments made on a continuous scale were categorical, there was also some gradation. We then tested two competing explanations for this gradation: the confidence explanation, which states that people make graded causal judgments because they have varying degrees of belief in causal relations, and the strength explanation, which states that people make graded causal judgments because they believe that causation itself is graded. Experiment 1 tested the confidence explanation and showed that gradation in causal judgments was indeed moderated by confidence: people tended to make graded causal judgments when they were unconfident, but they tended to make more categorical causal judgments when they were confident. Experiment 2 tested the causal strength explanation and showed that although confidence still explained variation in causal judgments, it did not explain away the effects of normality, causal structure, or the number of candidate causes. Overall, we found that causal judgments were multimodal and that people make graded judgments both when they think a cause is weak and when they are uncertain about its causal role. (shrink)