A number of recent authors (Galles and Pearl, Found Sci 3 (1):151–182, 1998; Hiddleston, Noûs 39 (4):232–257, 2005; Halpern, J Artif Intell Res 12:317–337, 2000) advocate a causal modeling semantics for counterfactuals. But the precise logical significance of the causal modeling semantics remains murky. Particularly important, yet particularly under-explored, is its relationship to the similarity-based semantics for counterfactuals developed by Lewis (Counterfactuals. Harvard University Press, 1973b). The causal modeling semantics is both an account of the truth conditions (...) of counterfactuals, and an account of which inferences involving counterfactuals are valid. As an account of truth conditions, it is incomplete. While Lewis's similarity semantics lets us evaluate counterfactuals with arbitrarily complex antecedents and consequents, the causal modeling semantics makes it hard to ascertain the truth conditions of all but a highly restricted class of counterfactuals. I explain how to extend the causal modeling language to encompass a wider range of sentences, and provide a sound and complete axiomatization for the extended language. Extending the truth conditions for counterfactuals has serious consequences concerning valid inference. The extended language is unlike any logic of Lewis's: modus ponens is invalid, and classical logical equivalents cannot be freely substituted in the antecedents of conditionals. (shrink)

Team semantics is a highly general framework for logics which describe dependencies and independencies among variables. Typically, the dependencies considered in this context are properties of sets of configurations or data records. We show how team semantics can be further generalized to support languages for the discussion of interventionist counterfactuals and causal dependencies, such as those that arise in manipulationist theories of causation. We show that the “causal teams” we introduce in the present paper can be used for (...) modelling some classical counterfactual scenarios which are not captured by the usual causal models. We then analyse the basic properties of our counterfactual languages and discuss extensively the differences with respect to the Lewisian tradition. (shrink)

A number of authors have recently used causal models to develop a promising semantics for non-backtracking counterfactuals. Briggs shows that when this semantics is naturally extended to accommodate right-nested counterfactuals, it invalidates modus ponens, and therefore violates weak centering given the standard Lewis/stalnaker interpretation of the counterfactual in terms of nearness or similarity of worlds. In this paper, I explore the possibility of abandoning the Lewis/stalnaker interpretation for some alternative that is better suited to accommodate the causal modeling (...) semantics. I argue that a revision of McGee’s semantics can accommodate CM semantics without sacrificing weak centering, and that CM semantics can therefore be situated within a general semantics for counterfactuals that is based on the nearness or similarity of worlds. (shrink)

In this paper I present a limitation to what may be called strictly-interventionistic causal-model semantic theories for subjunctive conditionals. And I offer a line of response to Briggs’ counterexample to Modus Ponens—given within a strictly-interventionistic framework—for the subjunctive conditional. The paper also contains some discussion of backtracking counterfactuals and backtracking interpretations. The limitation inherent to strict interventionism is brought out via a class of counterexamples. A causal-model semantics is strictly interventionistic just in case the procedure it gives for evaluating (...) a subjunctive conditional requires making the values of the variables implicated in the antecedent independent from the values of the parents of these antecedent variables. Most causal-model semantic theories that have gained attention are strictly interventionistic. (shrink)

In (Barbero and Sandu 2020 Journal of Philosophical Logic, 50, 471-521), we showed that languages encompassing interventionist counterfactuals and causal notions based on them (as e.g. in Pearl’s and Woodward’s manipulationist approaches to causation) as well as information-theoretic notions (such as learning and dependence) can be interpreted in a semantic framework which combines the traditions of structural equation modeling and of team semantics. We now present a further extension of this framework (causal multiteams) which allows us to talk (...) about probabilistic causal statements. We analyze the expressivity resources of two causal-probabilistic languages, one finitary and one infinitary. We show that many causal-probabilistic notions from the literature on causal inference can already be expressed in the finitary language, and we prove a normal form theorem that throws a new light on Pearl’s “ladder of causation”. In addition, we provide an exact semantic characterization of the infinitary language, which shows that this language captures precisely those causal-probabilistic statements that do not commit us to any specific interpretation of probability; and we prove that no usual, countable language is apt for this task. (shrink)

We examine a formal semantics for counterfactual conditionals due to Judea Pearl, which formalizes the interventionist interpretation of counterfactuals central to the interventionist accounts of causation and explanation. We show that a characteristic principle validated by Pearl’s semantics, known as the principle of reversibility, states a kind of irreversibility: counterfactual dependence (in David Lewis’s sense) between two distinct events is irreversible. Moreover, we show that Pearl’s semantics rules out only mutual counterfactual dependence, not cyclic dependence in general. (...) This, we argue, suggests that Pearl’s logic is either too weak or too strong. (shrink)

This article uses the interventionist theory of causation, a counterfactual theory taken from philosophy of science, to strengthen causal analysis in process tracing research. Causal claims from process tracing are re-expressed in terms of so-called hypothetical interventions, and concrete evidential tests are proposed which are shown to corroborate process tracing claims. In particular, three steps are prescribed for an interventionist investigation, and each step in turn is shown to make the causal analysis more robust, amongst others by disambiguating (...) causal claims and clarifying or strengthening the existing methodological advice on counterfactual analysis. The article's claims are then illustrated using a concrete example, Haggard and Kaufman's analysis of the Argentinian transition to democracy. It is shown that interventionism could have strengthened the authors’ conclusions. The article concludes with a short Bayesian analysis of its key methodological proposals. (shrink)

We analyze the causal-observational languages that were introduced in Barbero and Sandu (2018), which allow discussing interventionist counterfactuals and functional dependencies in a unified framework. In particular, we systematically investigate the expressive power of these languages in causal team semantics, and we provide complete natural deduction calculi for each language. Furthermore, we introduce a generalized semantics which allows representing uncertainty about the causal laws, and we analyze the expressive power and proof theory of the causal-observational languages over this (...) enriched semantics. (shrink)

This article defends the use of interventionist counterfactuals to elucidate causal and explanatory claims against criticisms advanced by James Bogen and Peter Machamer. Against Bogen, I argue that counterfactual claims concerning what would happen under interventions are meaningful and have determinate truth values, even in a deterministic world. I also argue, against both Machamer and Bogen, that we need to appeal to counterfactuals to capture the notions like causal relevance and causal mechanism. Contrary to what both authors (...) suppose, counterfactuals are not "unscientific" - a substantial tradition within statistics and the causal modelling literature makes heavy use of them. (shrink)

This paper aims to bridge philosophical and psychological research on causation, counterfactual thought, and the problem of backtracking. Counterfactual approaches to causation such as that by Lewis have ruled out backtracking, while on prominent models of causal inference interventionist counterfactuals do not backtrack. However, on various formal models, certain backtracking counterfactuals end up being true, and psychological evidence shows that people do sometimes backtrack when answering counterfactual questions in causal contexts. On the basis of psychological research, I (...) argue that while ordinarily both kinds of counterfactuals may be employed, non-backtracking counterfactuals are more easily used in causal inference because they are consistent with temporal order information embedded in the mental simulation heuristic, and they match reasoners’ experience of causation. While this approach is incompatible with the ambitions of counterfactual theories that seek to establish the non-backtracking interpretation as the only legitimate one, it can provide support for perspectival views on causation and open further inquiry on the functions of causal and counterfactual thought in the context of causal models. (shrink)

The paper focuses on a recent challenge brought forward against the interventionist approach to the meaning of counterfactual conditionals. According to this objection, interventionism cannot account for the interpretation of right-nested counterfactuals, the problem being its strict interventionism. We will report on the results of an empirical study supporting the objection. Furthermore, we will extend the well-known logic of intervention with a new operator expressing an alternative notion of intervention that does away with strict interventionism. This new notion (...) of intervention operates on the valuation of the variables in a causal model, and not on their functional dependencies. (shrink)

Here I consider the relative merits of two recent models of explanation, James Woodward's interventionist-counterfactual model and the model model. According to the former, explanations are largely constituted by information about the consequences of counterfactual interventions. Problems arise for this approach because countless relevant interventions are possible in most cases and because it overlooks other kinds of equally relevant information. According the model model, explanations are largely constituted by cognitive models of actual mechanisms. On this approach, explanations tend not (...) to represent any of the aforementioned information explicitly but can instead be used to produce it on demand. The model model thus offers the more plausible account of the information of which we are aware when we have an explanation and of the ratiocinative process through which we derive many kinds of information that are relevant to the evaluation of explanations. (shrink)

Counterfactual reasoning -- envisioning hypothetical scenarios, or possible worlds, where some circumstances are different from what (f)actually occurred (counter-to-fact) -- is ubiquitous in human cognition. Conventionally, counterfactually-altered circumstances have been treated as "small miracles" that locally violate the laws of nature while sharing the same initial conditions. In Pearl's structural causal model (SCM) framework this is made mathematically rigorous via interventions that modify the causal laws while the values of exogenous variables are shared. In recent years, however, this purely (...) class='Hi'>interventionist account of counterfactuals has increasingly come under scrutiny from both philosophers and psychologists. Instead, they suggest a backtracking account of counterfactuals, according to which the causal laws remain unchanged in the counterfactual world; differences to the factual world are instead "backtracked" to altered initial conditions (exogenous variables). In the present work, we explore and formalise this alternative mode of counterfactual reasoning within the SCM framework. Despite ample evidence that humans backtrack, the present work constitutes, to the best of our knowledge, the first general account and algorithmisation of backtracking counterfactuals. We discuss our backtracking semantics in the context of related literature and draw connections to recent developments in explainable artificial intelligence (XAI). (shrink)

Counterfactual theories of causation of the sort presented in Mackie, 1974, and Lewis, 1973 are a familiar part of the philosophical landscape. Such theories are typically advanced primarily as accounts of the metaphysics of causation. But they also raise empirical psychological issues concerning the processes and representations that underlie human causal reasoning. For example, do human subjects internally represent causal claims in terms of counterfactual judgments and when they engage in causal reasoning, does this involves reasoning about counterfactual claims? This (...) paper explores several such issues from a broadly interventionist perspective. (shrink)

Philosophers have recently highlighted substantial affinities between causation and grounding, which has inclined some to import the conceptual and formal resources of causal interventionism into the metaphysics of grounding. The prospect of grounding interventionism raises two important questions: exactly what are grounding interventions, and why should we think they enable knowledge of grounding? This paper will approach these questions by examining how causal interventionists have addressed (or might address) analogous questions and then comparing the available options for grounding interventionism. I (...) argue that grounding interventions must be understood in worldly terms, as adding something to or deleting something from the roster of entities, or making some fact obtain or fail to obtain. I consider three bases for counterfactual assessment: imagination, structural equation models, and background theory. I conclude that grounding interventionism requires firmer epistemological foundations, without which the interventionist's epistemology of grounding is incomplete and ineffectually rationalist. (shrink)

Causal selection is the task of picking out, from a field of known causally relevant factors, some factors as elements of an explanation. The Causal Parity Thesis in the philosophy of biology challenges the usual ways of making such selections among different causes operating in a developing organism. The main target of this thesis is usually gene centrism, the doctrine that genes play some special role in ontogeny, which is often described in terms of information-bearing or programming. This paper is (...) concerned with the attempt of confronting the challenge coming from the Causal Parity Thesis by offering principles of causal selection that are spelled out in terms of an explicit philosophical account of causation, namely an interventionist account. I show that two such accounts that have been developed, although they contain important insights about causation in biology, nonetheless fail to provide an adequate reply to the Causal Parity challenge: Ken Waters's account of actual-difference making and Jim Woodward's account of causal specificity. A combination of the two also doesn't do the trick, nor does Laura Franklin-Hall's account of explanation (in this volume). We need additional conceptual resources. I argue that the resources we need consist in a special class of counterfactual conditionals, namely counterfactuals the antecedents of which describe biologically normal interventions. (shrink)

One of the main line of responses to the infamous causal exclusion problem has been based on the counterfactual account of causation. However, arguments have begun to surface to the effect that the counterfactual theory is in fact ill-equipped to solve the exclusion problem due to its commitment to downward causation. This argumentation is here critically analysed. An analysis of counterfactual dependence is presented and it is shown that if the semantics of counterfactuals is taken into account carefully enough, (...) the counterfactual notion of causation does not need to be committed to downward causation. However, it is a further question whether this is eventually enough to solve the exclusion problem for the analysis shows how the problem itself can take various different forms. (shrink)

Causal models show promise as a foundation for the semantics of counterfactual sentences. However, current approaches face limitations compared to the alternative similarity theory: they only apply to a limited subset of counterfactuals and the connection to counterfactual logic is not straightforward. This paper addresses these difficulties using exogenous interventions, where causal interventions change the values of exogenous variables rather than structural equations. This model accommodates judgments about backtracking counterfactuals, extends to logically complex counterfactuals, and validates familiar (...) principles of counterfactual logic. This combines the interventionist intuitions of the causal approach with the logical advantages of the similarity approach. (shrink)

Causal models show promise as a foundation for the semantics of counterfactual sentences. However, current approaches face limitations compared to the alternative similarity theory: they only apply to a limited subset of counterfactuals and the connection to counterfactual logic is not straightforward. This article addresses these difficulties using exogenous interventions, where causal interventions change the values of exogenous variables rather than structural equations. This model accommodates judgments about backtracking counterfactuals, extends to logically complex counterfactuals, and validates familiar (...) principles of counterfactual logic. This combines the interventionist intuitions of the causal approach with the logical advantages of the similarity approach. (shrink)

“If the tower is any taller than 320 ms, it may collapse,” Eiffel thinks out loud. Although understanding this counterfactual poses no trouble, the most successful interventionist semantics struggle to model it because the antecedent can come about in infinitely many ways. My aim is to provide a semantics that will make modeling such counterfactuals easy for philosophers, computer scientists, and cognitive scientists who work on causation and causal reasoning. I first propose three desiderata that will guide my (...) theory: it should be general, yet conservative, yet useful. Next, I develop a formalization of events in the form of an algebra. I identify an event with all the ways in which it can be brought about and provide rules for determining the referent of an arbitrary event description. I apply this algebra to counterfactuals expressed using underdeterministic causal models-models that encode non-probabilistic causal indeterminacies. Specifically, I develop semaphore interventions, which represent how the target system may be modified from without in a coordinated fashion. This, in turn, allows me to bring about any event within a single model. Finally, I explain the advantages of this semantics over other interventionist competitors. (shrink)

Causal selection is the task of picking out, from a field of known causally relevant factors, some factors as elements of an explanation. The Causal Parity Thesis in the philosophy of biology challenges the usual ways of making such selections among different causes operating in a developing organism. The main target of this thesis is usually gene centrism, the doctrine that genes play some special role in ontogeny, which is often described in terms of information-bearing or programming. This paper is (...) concerned with the attempt of confronting the challenge coming from the Causal Parity Thesis by offering principles of causal selection that are spelled out in terms of an explicit philosophical account of causation, namely an interventionist account. I show that two such accounts that have been developed, although they contain important insights about causation in biology, nonetheless fail to provide an adequate reply to the Causal Parity challenge: Ken Waters's account of actual-difference making and Jim Woodward's account of causal specificity. A combination of the two also doesn't do the trick, nor does Laura Franklin-Hall's account of explanation (in this volume). We need additional conceptual resources. I argue that the resources we need consist in a special class of counterfactual conditionals, namely counterfactuals the antecedents of which describe biologically normal interventions. (shrink)

It has been argued that nonreductive physicalism’s problems with mental causation disappear if we abandon the intuitive but naïve production-based conception of causation in favor of one based on counterfactual dependence and difference-making. In recent years, this response has been thoroughly developed and defended by James Woodward, who contends that Kim’s causal exclusion argument, widely thought to be the most serious threat to nonreductive mental causation, cannot even be given a coherent formulation within Woodward’s preferred interventionist framework. But Woodward (...) has, even more recently, defended a pair of necessary conditions on mental causation and higher-order causation more generally, and it is here that the interventionist framework proves less friendly to nonreductive mental causation. Functionalism is arguably the most important species of nonreductive physicalism concerning specifically mental properties, but, as I argue, functional properties fail both of Woodward’s tests of causal relevance, one of them in two different ways. The problem, moreover, seems unique to functionalism, for other types of higher-order properties appear to pass Woodward’s tests. If functionalism faces defeat even in such friendly territory, its problems with mental causation are not an artifact of naïve metaphysics. They run deep. (shrink)

In this article, I analyze historical counterfactuals. Historical counterfactuals are conditional statements in which the antecedent refers to some change in the past. We ask what would have happened, had that change occurred. I discuss the nature of such counterfactuals. I then identify important functions that historical counterfactuals have. I point out that they are at the heart of explanations and, therefore, reveal issues related to contingency and actual history. I then discuss counterfactual reasoning in historiography. (...) I argue that the problem of suitable antecedent conditions has been exaggerated, and more serious issues concern the tracking of counterfactual scenarios. Throughout the paper, I argue that the interventionist way of thinking about historical counterfactuals clarifies both historical explanations and the nature of historical counterfactuals and should be adopted as the standard. I conclude by noting that historical counterfactuals may not fundamentally differ from more familiar forms of historiography. (shrink)

According to James Woodward’s influential interventionist account of causation, X is a cause of Y iff, roughly, there is a possible intervention on X that changes Y. Woodward requires that interventions be merely logically possible. I will argue for two claims against this modal character of interventions: First, merely logically possible interventions are dispensable for the semantic project of providing an account of the meaning of causal statements. If interventions are indeed dispensable, the interventionist theory collapses into a (...) counterfactual theory of causation. Thus, the interventionist theory is not tenable as a theory of causation in its own right. Second, if one maintains that merely logically possible interventions are indispensable, then interventions with this modal character lead to the fatal result that interventionist counterfactuals are evaluated inadequately. Consequently, interventionists offer an inadequate theory of causation. I suggest that if we are concerned with explicating causal concepts and stating the truth-conditions of causal claims we best get rid of Woodwardian interventions. (shrink)

In Making Things Happen, James Woodward influentially combines a causal modeling analysis of actual causation with an interventionist semantics for the counterfactuals encoded in causal models. This leads to circularities, since interventions are defined in terms of both actual causation and interventionist counterfactuals. Circularity can be avoided by instead combining a causal modeling analysis with a semantics along the lines of that given by David Lewis, on which counterfactuals are to be evaluated with respect to (...) worlds in which their antecedents are realized by miracles. I argue, pace Woodward, that causal modeling analyses perform just as well when combined with the Lewisian semantics as when combined with the interventionist semantics. Reductivity therefore remains a reasonable hope. (shrink)

I argue that one central aspect of the epistemology of causation, the use of causes as evidence for their effects, is largely independent of the metaphysics of causation. In particular, I use the formalism of Bayesian causal graphs to factor the incremental evidential impact of a cause for its effect into a direct cause-to-effect component and a backtracking component. While the “backtracking” evidence that causes provide about earlier events often obscures things, once we our restrict attention to the cause-to-effect component (...) it is true to say promoting (inhibiting) causes raise (lower) the probabilities of their effects. This factoring assumes the same form whether causation is given an interventionist, counterfactual or probabilistic interpretation. Whether we think about causation in terms of interventions and causal graphs, counterfactuals and imaging functions, or probability raising against the background of causally homogenous partitions, if we describe the essential features of a situation correctly then the incremental evidence that a cause provides for its effect in virtue of being its cause will be the same. (shrink)

: Among the current philosophical accounts of causation two are the most prominent. The first is James Woodward's interventionist counterfactual approach; the second is the mechanistic approach advocated by Peter Machamer, Lindley Darden, Carl Craver, Jim Bogen and Stuart Glennan. Thecounterfactual approach takes it that causes make a difference to their effects, where this difference-making is cashed out in terms of actual and counterfactual interventions. The mechanistic approach takes it that two events are causally related if and only if (...) there is a mechanism that connects them. In this paper I examine them both in some detail. After pointing out some important problems that both approaches face, I argue that there is a sense in which the counterfactual approach is more basic than the mechanistic one in that a proper account of mechanisms depends on counterfactuals while counterfactuals need not be supported (or depend on) mechanisms. Nonetheless, I also argue that if both approaches work in tandem in practice, they can offer us a better understanding of aspects of Hume's secret connexion and hence a glimpse of it. (shrink)

James Woodward offers a conception of explanation and mechanism in terms of interventionist counterfactuals. Based on a case from ecology, I show that ecologists’ approach to that case satisfies Woodward’s conditions for explanation and mechanism, but his conception does not fully capture what ecologists view as explanatory. The new mechanistic philosophy likewise aims to describe central aspects of mechanisms, but I show that it is not sufficient to account for ecological mechanisms. I argue that in ecology explanation involves (...) identification of invariant and insensitive causal relationships and descriptions of the mechanistic characteristics that make these relations possible. †To contact the author, please write to: Department of Philosophy, University of Dayton, 300 College Park, Dayton, OH 45469‐1546; e‐mail: paslarvi@notes.udayton.edu. (shrink)

This paper articulates an account of causation as a collection of information-theoretic relationships between patterns instantiated in the causal nexus. I draw on Dennett’s account of real patterns to characterize potential causal relata as patterns with specific identification criteria and noise tolerance levels, and actual causal relata as those patterns instantiated at some spatiotemporal location in the rich causal nexus as originally developed by Salmon. I develop a representation framework using phase space to precisely characterize causal relata, including their degree (...) of counterfactual robustness, causal profiles, causal connectivity, and privileged grain size. By doing so, I show how the philosophical notion of causation can be rendered in a format that is amenable for direct application of mathematical techniques from information theory such that the resulting informational measures are causal informational measures. This account provides a metaphysics of causation that supports interventionist semantics and causal modeling and discovery techniques. (shrink)

What is it for an event not to occur? This is an urgent, yet under explored, question for counterfactual analyses of causation quite generally. In this paper I take a lead from Lewis in identifying two different possible standards of non-occurrence that we might adopt and I argue that we need to apply them asymmetrically: one standard for the cause, another for the effect. This is a surprising result. I then offer a contextualist refinement of the Lewis approach in light (...) of initial problems, and discuss how the asymmetry remained hidden until now. I then relate the non-occurrence problem to issues of transitivity and proportionality in causation, before showing that a parallel problem exists for contrastivist and interventionist approaches to causation too. (shrink)

This paper discusses von Wright's theory of causation from Explanation and Understanding and Causality and Determinism in contemporary context. I argue that there are two important common points that von Wright's view shares with the version of manipulability currently supported by Woodward: the analysis of causal relations in a system modelled on controlled experiments, and the explanation of manipulability through counterfactuals - with focus on the counterfactual account of unmanipulable causes. These points also mark von Wright's departure from previous (...) action-based theories of causation. Owing to these two features, I argue that, upon classifying different versions of manipulability theories, von Wright's view should be placed closer to the interventionist approach than to the agency theory, where it currently stands. Furthermore, given its relevance in contemporary context, which this paper aims to establish, I claim that von Wright's theory can be employed to solve present problems connected to manipulability approaches to causation. (shrink)

Counternomics—counterfactuals whose antecedents run contrary to the laws of nature—are commonplace in science but have enjoyed relatively little philosophical attention. This article discusses a puzzle about our counternomic epistemology, focusing on cases in which experimental observations are used as evidence for counternomic claims. I show that these cases resist being characterized in familiar interventionist lines, and I suggest a characterization of my own.

The application of the formal framework of causal Bayesian Networks to children’s causal learning provides the motivation to examine the link between judgments about the causal structure of a system, and the ability to make inferences about interventions on components of the system. Three experiments examined whether children are able to make correct inferences about interventions on different causal structures. The first two experiments examined whether children’s causal structure and intervention judgments were consistent with one another. In Experiment 1, children (...) aged between 4 and 8 years made causal structure judgments on a three-component causal system followed by counterfactual intervention judgments. In Experiment 2, children’s causal structure judgments were followed by intervention judgments phrased as future hypotheticals. In Experiment 3, we explicitly told children what the correct causal structure was and asked them to make intervention judgments. The results of the three experiments suggest that the representations that support causal structure judgments do not easily support simple judgments about interventions in children. We discuss our findings in light of strong interventionist claims that the two types of judgments should be closely linked. (shrink)

Many explanations rely on identity facts. In this paper, I propose an account of how identity facts explain: roughly, the fact that A is identical to B explains another fact whenever that other fact depends, counterfactually, on A being identical to B. As I show, this account has many virtues. It avoids several problems facing accounts of explanatory identities, and when precisified using structural equations, it can be used to defend interventionist accounts of causation against an objection.

This dissertation begins by addressing the question of when a causal model is apt for deciding questions of actual causation with respect to some target situation. I first provide relevant background about causal models, explain what makes them promising as a tool for analyzing actual causation, and motivate the need for a theory of aptness as part of such an analysis (Chapter 1). I then define what it is for a model on a given interpretation to be accurate of, that (...) is, say only true things about, some target situation. This involves a systematization of various representational principles mentioned and/or discussed throughout the literature into a method of interpretation, which I propose be taken as standard (Chapter 2). Next, I explain and address two reasons for which accuracy as I’ve defined it is insufficient for aptness. The first reason – already discussed in the literature – is the problem of structural isomorphs. In response, I propose the aptness condition of Explicit Partial Mediation (Chapter 3). The second reason – which has yet to be noticed – is the problem of the indeterminacy of accuracy. As I demonstrate, a model is accurate of a target situation only relative to a set of background possibilities – what I call a modal profile. It follows that a model represents a situation only relative to some modal profile or other. I go on to discuss the ramifications of this observation for a theory of actual causation in terms of models. I argue that the relativity be taken at face value and built into our metaphysical account of causation, resulting in a view that I call causal relativism (Chapter 4). I explore one advantage of this view in detail: that the resulting account can defend the principle of strong proportionality against several objections (Chapter 5). Finally, I apply the earlier discussion of aptness to attempts to provide a semantics of counterfactuals in terms of causal models – an interventionist semantics. I show how just as a similarity semantics relies on an opaque notion of similarity, an interventionist semantics relies on an analogous notion of aptness. The challenge of articulating aptness thus undermines the claim that an interventionist semantics avoids representational problems inherent in a similarity semantics (Chapter 6). I close with a recap and suggestions for future research (Chapter 7). -/- . (shrink)

A critical analysis of recent interventionist responses to the causal exclusion problem is presented. It is argued that the response can indeed offer a solution to the problem, but one that is based on renouncing the multiple realizability thesis. The account amounts to the rejection of nonreductive physicalism and would thus be unacceptable to many. It is further shown that if the multiple realizability thesis is brought back in and conjoined with the interventionist notion of causation, inter-level causation (...) is ruled out altogether. (shrink)

This chapter explores the idea of one variable making a causal contribution to another variable, and how this idea applies to economics. It also explores the related concept of what-if questions in economics. In particular, it contrasts the modular theory of causal contributions and what-if questions (advocated by interventionists) with the ceteris paribus theory (advocated by Jim Heckman and others). It notes a problem with the modular theory raised by Nancy Cartwright. And it notes how, according to the ceteris paribus (...) theory, causal contributions and what-if questions are often indeterminate in economics. (shrink)

In this paper, we examine the causal framework within which integrated information theory of consciousness makes it claims. We argue that, in its current formulation, IIT is threatened by the causal exclusion problem. Some proponents of IIT have attempted to thwart the causal exclusion problem by arguing that IIT has the resources to demonstrate genuine causal emergence at macro scales. In contrast, we argue that their proposed solution to the problem is damagingly circular as a result of inter-defining information and (...) causation. As a solution, we propose that IIT should adopt the specific interventionist causal framework that we offer and show how IIT can harness this interventionist framework to avoid the causal exclusion problem. We demonstrate how our argument remains fully compatible with the methodology, empirical data, and conceptual aims of the theory. (shrink)

There is a systematic and suggestive analogy between grounding and causation. In my view, this analogy is no coincidence. Grounding and causation are alike because grounding is a type of causation: metaphysical causation. In this paper I defend the identification of grounding with metaphysical causation, drawing on the causation literature to explore systematic connections between grounding and metaphysical dependence counterfactuals, and I outline a non-reductive counterfactual theory of grounding along interventionist lines.

An important component in the interventionist account of causal explanation is an interpretation of counterfactual conditionals as statements about consequences of hypothetical interventions. The interpretation receives a formal treatment in the framework of functional causal models. In Judea Pearl’s influential formulation, functional causal models are assumed to satisfy a “unique-solution” property; this class of Pearlian causal models includes the ones called recursive. Joseph Halpern showed that every recursive causal model is Lewisian, in the sense that from the causal model (...) one can construct a possible worlds model in David Lewis’s well-known semantics that satisfies the exact same formulas in a certain language. Moreover, he demonstrated that some Pearlian (non-recursive) models are not Lewisian in this sense. This raises the question regarding the exact contour of Lewisian causal models. In this paper, we provide a characterization of the class of Lewisian causal models and a complete axiomatization with respect to this class. Our results have philosophically interesting consequences, two of which are especially worth noting. First, the class of Stalnakerian causal models, a subclass of Lewisian causal models, is precisely the class of Pearlian models that do not contain any cycle of counterfactual dependence (in a sense of counterfactual dependence akin to Lewis’s famous relation between distinct events). Second, a more natural class of causal models is actually a superclass of Lewisian causal models, the logic of which respects only weak centering rather than centering. (shrink)

This is one of a pair of discussion notes comparing some features of the account of causation in Wolfgang Spohn’s Laws of Belief with the “interventionist” account in James Woodward’s Making Things Happen. This note locates the core difference of the accounts in the fact that Woodward’s account follows an epistemological order, while Spohn’s follows a conceptual order. This unfolds in five further differences: type- versus token-level causation, reference to time, actual/counterfactual intervention versus epistemic/suppositional wiggling, a circular versus a (...) circle-free conception of the circumstances of a direct causal relation, and absolute versus model-relative causation. (shrink)

I argue that manipulationist theories of causation fail as accounts of causal structure, and thereby as theories of “actual causation” and causal explanation. I focus on two kinds of problem cases, which I call “Perceived Abnormality Cases” and “Ontological Dependence Cases.” The cases illustrate that basic facts about social systems—that individuals are sensitive to perceived abnormal conditions and that certain actions metaphysically depend on institutional rules—pose a challenge for manipulationist theories and for counterfactual theories more generally. I then show how (...) law-based accounts of causal structure can answer such challenges. The moral of the story is that the basic manipulationist idea that our interest in causal structure is driven by our interest in manipulating our environment faces decisive problems in a central domain of application, the social sciences. (shrink)

Let ‘semantic relevance’ be the thesis that the wide semantic properties of representational mental states (like beliefs and desires) are causally relevant to behavior. A popular way of arguing for semantic relevance runs as follows: start with a sufficient counterfactual condition for causal or explanatory relevance, and show that wide semantic properties meet it with respect to behavior (e.g., Loewer & Lepore (1987,1989), Rescorla (2014), Yablo (2003)).This paper discusses an in‐principle limitation of this strategy: even the most sophisticated counterfactual criteria (...) systematically misclassify irrelevant properties as relevant when they stand in certain kinds of modal co‐variation or ‘entanglement’ relations to genuinely relevant properties. This entanglement problem, I argue, is more general and more serious than proponents of the counterfactual strategy have recognized: it threatens recent interventionist arguments for semantic relevance, and is not easily solved by appeal to proportionality or naturalness. I end by suggesting that proponents of semantic relevance may need to shift their attention from patterns of counterfactuals to the lawful psychological generalizations that explain them. (shrink)

This paper outlines a non-reductive counterfactual account of grounding along interventionist lines, and uses the account to argue that taking grounding seriously requires ascribing non-trivial truth-conditions to a range of counterpossible counterfactuals. This result allows for a diagnosis of a route to scepticism about grounding, as deriving at least in part from scepticism about non-trivial counterpossible truth and falsity.

This paper investigates what happens when we merge two different lines of theorizing about counterfactuals. One is the comparative closeness view, which was developed by Stalnaker and Lewis in the framework of possible worlds semantics. The second is the interventionist view, which is part of the causal models framework developed in statistics and computer science. Common lore and existing literature have it that the two views can be easily fit together, aside from a few details. I argue that, (...) on the contrary, transplanting causal-models-inspired ideas in a possible worlds framework yields a new semantics. The difference is grounded in different algorithms for handling inconsistent information, hence it touches on issues that are at the very heart of a semantics for contrary-to-fact conditionals. Roughly, Stalnaker/Lewis semantics requires us to evaluate the consequent of a counterfactual at all closest antecedent-verifying possibilities. Causal-models-based semantics also does this, but in addition uses the information contained in the antecedent, together with background causal information, to shift what worlds count as closest. This makes systematically different predictions and generates a new logic. The upshot is that we have a new semantics to study, and a substantial theoretical choice to make. (shrink)

Philosophy and statistics have studied two causal species, deterministic and probabilistic. There's a third species, however, hitherto unanalysed: underdeterministic causal phenomena, which are non-deterministic yet non-probabilistic. Here, I formulate a framework for modelling them. -/- Consider a simple case. If I go out, I may stumble into you but also may miss you. If I don’t go out, we won't meet. I go out. We meet. My going out is a cause of our encounter even if there was no determinate (...) probability of us meeting conditional on my going out. The cause is neither deterministic (it didn't necessitate the effect) nor probabilistic (the relevant conditional probabilities are undefined). Rather, it's underdeterministic: it raises the modal status of the effect from causally impossible to possible. -/- Here, I won't offer a theory of such token causes but develop the prerequisite for any such theory: the underdeterministic framework. The framework is like the deterministic structural-equations framework but with one consequential difference---an equation can return multiple values. This change allows me to define causal possibility and necessity, and corresponding notions of interventionist might- and would-counterfactuals. I also define conditional independence, which obeys the graphoid axioms, and prove that underdeterministic models satisfy the causal Markov condition. The framework can causally model situations that other frameworks cannot: decision-making under bounded uncertainty, games with multiple equilibria, infinite fair lotteries, and any other non-deterministic situation where indeterminacies are essentially non-probabilistic, or where we have a reason not to use probabilities. (shrink)

We clarify the status of the so-called causal minimality condition in the theory of causal Bayesian networks, which has received much attention in the recent literature on the epistemology of causation. In doing so, we argue that the condition is well motivated in the interventionist (or manipulability) account of causation, assuming the causal Markov condition which is essential to the semantics of causal Bayesian networks. Our argument has two parts. First, we show that the causal minimality condition, rather than (...) an add-on methodological assumption of simplicity, necessarily follows from the substantive interventionist theses, provided that the actual probability distribution is strictly positive. Second, we demonstrate that the causal minimality condition can fail when the actual probability distribution is not positive, as is the case in the presence of deterministic relationships. But we argue that the interventionist account still entails a pragmatic justification of the causal minimality condition. Our argument in the second part exemplifies a general perspective that we think commendable: when evaluating methods for inferring causal structures and their underlying assumptions, it is relevant to consider how the inferred causal structure will be subsequently used for counterfactual reasoning. (shrink)

The systems studied in the special sciences are often said to be causally autonomous, in the sense that their higher-level properties have causal powers that are independent of the causal powers of their more basic physical properties. This view was espoused by the British emergentists, who claimed that systems achieving a certain level of organizational complexity have distinctive causal powers that emerge from their constituent elements but do not derive from them. More recently, non-reductive physicalists have espoused a similar view (...) about the causal autonomy of special-science properties. They argue that since these properties can typically have multiple physical realizations, they are not identical to physical properties, and further they possess causal powers that differ from those of their physical realisers. Despite the orthodoxy of this view, it is hard to find a clear exposition of its meaning or a defence of it in terms of a well-motivated account of causation. In this paper, we aim to address this gap in the literature by clarifying what is implied by the doctrine of the causal autonomy of special-science properties and by defending the doctrine using a prominent theory of causation from the philosophy of science. (shrink)

Note: Sections at a more advanced level are indicated by ∞. Preface ix Acknowledgments x Introduction 1 I Nicolaus Copernicus: The Loss of Centrality 3 1 Ptolemy and Copernicus 3 2 A Clash of Two Worldviews 4 2.1 The geocentric worldview 5 2.2 Aristotle’s cosmology 5 2.3 Ptolemy’s geocentrism 9 2.4 A philosophical aside: Outlook 14 2.5 Shaking the presuppositions: Some medieval developments 17 3 The Heliocentric Worldview 20 3.1 Nicolaus Copernicus 21 3.2 The explanation of the seasons 25 3.3 (...) Copernicus and the Copernican turn 28 3.3.1 A philosophical aside: From empirical adequacy to theoretical validity 32 3.4 Copernicus consolidated: Kepler and Galileo 32 4 Copernicus was not a Scientifi c Revolutionary 37 4.1 The Copernican method 39 4.2 The relativity of motion 42 5 The Transition to Newton 43 5.1 On hypotheses 45 6 Some Philosophical Lessons 47 6.1 The loss of centrality 48 6.2 Was Copernicus a realist? 51 6.2.1 Lessons for instrumentalism and realism 52 6.3 Modern realism 55 6.4 The underdetermination of theories by evidence 58 6.4.1 The Duhem--Quine thesis 59 ∞ 6.4.2 The power of constraints 61 ∞ 6.5 Theories, models, and laws 64 ∞ 6.5.1 Theories and models 64 ∞ 6.5.2 Laws of nature, laws of science 68 ∞ 6.5.3 Philosophical views of laws 69 ∞ 6.5.3.1 The inference view 69 ∞ 6.5.3.2 The regularity view 70 ∞ 6.5.3.3 The necessitarian view 73 ∞ 6.5.3.4 The structural view 75 7 Copernicus and Scientifi c Revolutions 77 8 The Anthropic Principle: A Reversal of the Copernican Turn? 83 Reading List 87 Essay Questions 91 II Charles Darwin: The Loss of Rational Design 93 1 Darwin and Copernicus 93 2 Views of Organic Life 94 2.1 Teleology 94 2.1.1 The Great Chain of Being 97 2.1.2 Design arguments 99 2.1.3 Jean Baptiste Lamarck 104 3 Fossil Discoveries 106 3.1 Of bones and skeletons 108 3.2 The antiquity of man 110 4 Darwin’s Revolution 112 4.1 The Darwinian view of life 114 4.1.1 Principles of evolution 116 4.2 The descent of man 119 5 Philosophical Matters 124 5.1 Philosophical presuppositions: Mechanical worldview, determinism, materialism 125 5.2 From biology to the philosophy of mind 129 5.2.1 Empiricism 129 5.2.2 Philosophy of mind 132 5.2.3 Emergent minds 134 5.3 The loss of rational design 136 5.4 Intelligent design 139 6 A Question of Method 143 6.1 Darwinian inferences 143 6.2 Philosophical empiricism 147 6.3 Some principles of elimination 149 ∞ 6.4 Essential features of eliminative induction 150 6.5 Falsifi ability or testability? 155 6.6 Explanation and prediction 157 ∞ 6.7 Some models of scientifi c explanation 159 ∞ 6.7.1 Hempel’s models 160 ∞ 6.7.2 Functional models 161 ∞ 6.7.3 Causal models 163 6.7.3.1 A counterfactual-interventionist account 163 6.7.3.2 A conditional model of causation 165 ∞ 6.7.4 Structural explanations 169 6.8 A brief return to realism 172 6.9 Darwin and scientifi c revolutions 174 6.9.1 Philosophical consequences 176 Reading List 177 Essay Questions 183 III Sigmund Freud: The Loss of Transparency 185 1 Copernicus, Darwin, and Freud 185 2 Some Views of Humankind 187 2.1 Enlightenment views of human nature 188 2.2 Nietzsche’s view of human nature 190 3 Scientism and the Freudian Model of Personality 191 3.1 Freud’s model of the mind 192 3.1.1 A summary of psychoanalytic theory 192 3.1.2 Analogy with physics 195 3.1.3 Freud as an Enlightenment thinker 200 3.1.4 The scientifi c status of the Freudian model 202 3.1.4.1 Freud’s methods 202 ∞ 3.1.4.2 The method of eliminative induction, again 205 3.1.5 Freud stands between the empirical and the hermeneutic models 208 3.1.6 The role of mind in the social world 209 4 The Social Sciences beyond Freud 210 4.1 Two standard models of the social sciences -- some history 210 4.1.1 The naturalistic model 211 4.1.2 The hermeneutic model 213 4.2 Essential features of social science models 218 4.2.1 Essential features of the naturalistic model 218 4.2.2 Essential features of the hermeneutic model 221 4.3 Questions of methodology 224 ∞ 4.3.1 What is Verstehen? 225 ∞ 4.3.2 Weber’s methodology of ideal types 229 ∞ 4.3.3 Verstehen and objectivity 234 ∞ 4.4 Causation in the social sciences 236 ∞ 4.4.1 Weber on causation 236 ∞ 4.4.2 On the existence of social laws 239 4.4.3 Explanation and prediction in the social sciences 242 4.4.4 Underdetermination 243 4.4.5 Realism and relativism 244 ∞ 4.4.6 Reductionism and functionalism 248 5 Evolution and the Social Sciences 253 5.1 Sociobiology -- the fourth revolution? 254 5.2 Evolutionary psychology 257 6 Freud and Revolutions in Thought 261 6.1 Revolutions in thought vs. revolutions in science 263 Reading List 263 Essay Questions 269 Name Index 271 Subject Index 274. (shrink)

Some explanations appeal to facts about the causal structure of a system in order to shed light on a particular phenomenon; these are explanations which do more than cite the causes X and Y of some state-of-affairs Z, but rather appeal to “macro-level” causal features—for example the fact that A causes B as well as C, or perhaps that D is a strong inhibitor of E—in order to explain Z. Appeals to these kinds of “macro-level” causal features appear in a (...) wide variety of social scientific and biological research; statements about features such as “patriarchy,” “healthcare infrastructure,” and “functioning DNA repair mechanism,” for instance, can be understood as claims about what would be different in a system with a different causal structure. I suggest interpreting counterfactual questions involving structural features as questions about alternative parameter settings of causal models, and propose an extension of the usual interventionist framework for causal explanation which enables scientists to explore the consequences of interventions on “macro-level” structure. (shrink)