This article describes research pursued by members of the McDonnell Collaborative on Causal Learning. A number of members independently converged on a similar idea: one of the central functions served by claims of actual causation is to highlight patterns of dependence that are highly portable into novel contexts. I describe in detail how this idea emerged in my own work and also in that of the psychologist Tania Lombrozo. In addition, I use the occasion to reflect on the nature (...) of interdisciplinary collaboration in general and on the interaction between philosophy and psychology in particular. (shrink)

In "Causes and "If P, Even If X, still Q," Philosophy 57 (July 1982), Ted Honderich cites my "The Direction of Causation and the Direction of Conditionship," journal of Philosophy 73 (April 22, 1976) as an example of an account of causal priority that lacks the proper character. After emending Honderich's description of the proper character, I argue that my attempt to account for one-way causation in terms of one-way causal conditionship does not totally lack it. Rather than (...) emphasize the singularity of an effect, as Honderich does, I emphasize the multiplicity of independent factors in a causal circumstance. (shrink)

This paper has two main goals. First, it asks whether causality is an adequate foundation for those theories of cognition and consciousness that are built upon it. The externalist revolution has reconceived all three dimensions of cognition -- the semantic, the epistemological, and the mental -- upon a foundation of 'causal connections of the appropriate type'. Yet, these new theories almost completely ignore the long-standing controversies surrounding the very nature of causality, and the very real threat that 'causality' may (...) be ill-equipped to do the work required of it. The second goal is to defend a kind of causality, largely ignored, that is grounded in the phenomenally conscious states of cognitive agents. While it is popular to try to reduce consciousness to causality, this is a kind of causality that ultimately reduces to (phenomenal) consciousness. (shrink)

ABSTRACT Causes must be distinct from their effects. If the temperature in a room is 15°F, this can cause water pipes to freeze. However, the temperature’s being 15°F is not a cause of the temperature’s being below the freezing point. In general, conceptual, logical, mathematical, and other non-causal dependence relations should not be misclassified as causal. In this paper, I discuss how interventionist theories of causation can meet the challenge of distinguishing between (direct or indirect) causal relations (...) and dependence relations that are due to non-causal factors. I survey several approaches to solving this problem, and propose a novel criterion based on the notion of supervenience. According to this criterion, variables are sufficiently distinct to qualify as the relata of a causal relation iff they do not have overlapping minimal supervenience bases. (shrink)

Ted Honderich's ‘Causes and If p, even if x, still q ’ contains many good points I shall not discuss. My discussion is restricted to some of the points Honderich makes about causal priority in the final two sections of his paper. He considers several proposals, new and old, for accounting for causal priority before he presents a tentativeproposal of his own. He thinks that some of these proposals, besides having difficulties peculiar to themselves, share the deficiency of (...) lacking the proper character. When we look for the difference between causal circumstances and causes, on the one hand, and their effects, on the other, he says, We are not pursuing any difference between these things. We arepursuing a difference of a certain character. What we are after has to do with what we say: that causes and causal circumstances make their effects happen , and not the other way on, and that causes and causal circumstances explain their effects , and not the other way on. (shrink)

This work presents a defense of causal contrastivism based on causal contexualism. As argued, our proposal on causal contextualism is compatible with both causal contrastivism and causal binarism, including explanations of why and in which sense secondary counterfactuals are relevant.

In “A Theory of Content, 11: The Theory,” Jerry Fodor presents two reasons why his asymmetric causal dependency theory does not lead to the conclusion that syntactic items “X” mean proximal sensory stimulations, rather than distal environmental objects. Here we challenge Fodor’s reasoning.

In “A Theory of Content, 11: The Theory,” Jerry Fodor presents two reasons why his asymmetric causal dependency theory does not lead to the conclusion that syntactic items “X” mean proximal sensory stimulations, rather than distal environmental objects. Here we challenge Fodor’s reasoning.

One of the principal presuppositions in the extended mind account of Clark and Chalmers establishes that extended and non-extended cognitive systems have somehow the same structure and that the distinctions between them can only be superficial. In contrast, this work presents some arguments for the idea that it is possible to find fundamental differences between both, mainly on the basis that a criterion that does not include the notion of knowledge is not strong enough to define cognitive processes. A brief (...) analysis on the non-transitivity of trust and the notion of causal dependence between information and cognitive systems might be helpful to support this position. It will be argued that the counterfactual block which supports the extended mind building does not seem to be firm. (shrink)

The paper displays the similarity between the theory of probabilistic causation developed by Glymour et al. since 1983 and mine developed since 1976: the core of both is that causal graphs are Bayesian nets. The similarity extends to the treatment of actions or interventions in the two theories. But there is also a crucial difference. Glymour et al. take causal dependencies as primitive and argue them to behave like Bayesian nets under wide circumstances. By contrast, I argue (...) the behavior of Bayesian nets to be ultimately the defining characteristic of causal dependence. (shrink)

In a pair of articles (1996, 1997) and in his recent book (1998), Miklos Redei has taken enormous strides toward characterizing the conditions under which relativistic quantum field theory is a safe setting for the deployment of causal talk. Here, we challenge the adequacy of the accounts of causal dependence and screening off on which rests the relevance of Redei's theorems to the question of causal good behavior in the theory.

In a pair of articles and in his recent book, Miklos Redei has taken enormous strides toward characterizing the conditions under which relativistic quantum field theory is a safe setting for the deployment of causal talk. Here, we challenge the adequacy of the accounts of causal dependence and screening off on which rests the relevance of Redei's theorems to the question of causal good behavior in the theory.

Jaegwon Kim argues that unreduced mental causes are excluded from efficacy because physical causes are sufficient in themselves. One response to this causal exclusion argument is to embrace some form of overdetermination. In this paper I consider two forms of overdetermination. Independent overdetermination suggests that two individually sufficient causes bring about one effect. This model fails because the sufficiency of one cause renders the other cause unnecessary. Dependent overdetermination suggests that a physical cause is necessary and sufficient for a (...) given effect, but it necessitates a mental cause of the effect as well. This model fails because the necessity of the mental cause renders the physical cause individually insufficient. (shrink)

A counterlegal is a counterfactual conditional containing an antecedent that is inconsistent with some set of laws. A backtracker is a counterfactual that tells us how things would be at a time earlier than that of its antecedent, were the antecedent to obtain. Typically, theories that evaluate counterlegals appropriately don’t evaluate backtrackers properly, and vice versa. Two cases in point: Lewis’ ordering semantics handles counterlegals well but not backtrackers. Hiddleston’s :632–657, 2005) causal-model semantics nicely handles backtrackers but not counterlegals. (...) Taking Hiddleston’s account as a starting point, I offer steps toward a theory capable of handling both counterlegals and backtrackers. The core contribution of this paper is a means for evaluating counterlegals relative to minimally-illegal models. (shrink)

The paper attempts to rationalize cooperation in the one-shot prisoners' dilemma (PD). It starts by introducing (and preliminarily investigating) a new kind of equilibrium (differing from Aumann's correlated equilibria) according to which the players' actions may be correlated (sect. 2). In PD the Pareto-optimal among these equilibria is joint cooperation. Since these equilibria seem to contradict causal preconceptions, the paper continues with a standard analysis of the causal structure of decision situations (sect. 3). The analysis then raises to (...) a reflexive point of view according to which the agent integrates his own present and future decision situations into the causal picture of his situation (sect. 4). This reflexive structure is first applied to the toxin puzzle and then to Newcomb's problem, showing a way to rationalize drinking the toxin and taking only one box with-out assuming causal mystery (sect. 5). The latter result is finally extended to a rationalization of cooperation in PD (sect. 6). (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)

The causal view of categories assumes that categories are represented by features and their causal relations. To study the effect of causal knowledge on categorization, researchers have used Bayesian causal models. Within that framework, categorization may be viewed as dependent on a likelihood computation (i.e., the likelihood of an exemplar with a certain combination of features, given the category's causal model) or as a posterior computation (i.e., the probability that the exemplar belongs to the category, (...) given its features). Across three experiments, in combination with computational modeling, we offer evidence that categorization is better accounted for by assuming that people compute posteriors and not likelihoods, though both probabilities are closely related. This result contrasts with existing analyses of causal-based categorization, which assume that likelihood computations give a good approximation of human judgments. We also find that people are able to compute likelihoods in a closely related task that elicits judgments of consistency rather than category membership judgments. Our analyses show that people do use causal probabilistic information as prescribed by a Bayesian model but that they flexibly compute likelihoods or posteriors depending on the task. We discuss our results in relation to the relevant literature on the topic. (shrink)

In (1990), Jerry Fodor has defended a naturalized conception of meaning for Mentalese expressions which relies on the notion of asymmetric dependence. According to this conception, any naturalized theory of meaning must be able to account for the fact that meaning is robust, namely that any token of a certain Mentalese expression “x” retains the expression’s meaning, X, for any Y (≠ X) which happens to cause it. Now, this robustness of “x”‘s meaning can precisely be explained in terms of (...) the subsistence of an asymmetric dependence of any nomic connection between Ys and “x”‘s tokens on another nomic connection between Xs and “x”‘s tokens. According to Fodor, then, this relation between nomic connections can account in perfectly naturalistic terms for “x” meaning X, by providing a sufficient condition for such a meaning. In what follows, however, I will try to show, first, that the subsistence of asymmetric dependencies of the kind envisaged by Fodor is not enough for assigning meaning to a certain expression. Indeed, there are dependencies of this kind which are meaning-irrelevant. Secondly, I will claim that asymmetric dependence relations are not able even to support for the robustness of meaning. For there are cases in which according to the structure of these relations we would have to conclude that meaning is altered although robustness would require to have it unchanged. (shrink)

Quantal penetration through a (stationary) one-dimensional potential barrier is considered as a time evolution of an initially prepared wave packet. The large-time asymptotics of the process is concerned. Locality of the potential imposes certain analytical properties of the interaction amplitudes in the energy representation. The results are presented in terms of development of the phase-space (Wigner's) quasi-distribution. The phase-space evolution kernel is constructed, and it is shown that in the presence of a positive potential no part of the distribution is (...) transported faster than the free particle. For the case of a small initial momentum uncertainty, the deformation of the coordinate density is considered, including a possible advance of its maximum, which would not mean any noncausal signal transport. (shrink)

Despite recent efforts to improve on counterfactual theories of causation, failures to explain how effects depend on their causes are still manifest in a variety of cases. In particular, theories that do a decent job explaining cases of causal preemption have problems accounting for cases of causal intransitivity. Moreover, the increasing complexity of the counterfactual accounts makes it difficult to see why the concept of causation would be such a central part of our cognition. In this paper, I (...) propose an account of our causal thinking that not only explains the hitherto puzzling variety of causal judgments, but also makes it intelligible why we would employ such an elusive concept. (shrink)

One can find in the literature two sets of views concerning the relationship between understanding and explanation: that one understands only if 1) one has knowledge of causes and 2) that knowledge is provided by an explanation. Taken together, these tenets characterize what I call the narrow knowledge account of understanding. While the first tenet has recently come under severe attack, the second has been more resistant to change. I argue that we have good reasons to reject it on the (...) basis of theoretical models that provide how-possibly explanations. These models, while they do not explain in the strict sense, afford understanding. In response, I propose an alternative epistemology of understanding, broad KAU, that takes cases of theoretical modelling into account. (shrink)

This paper makes explicit and takes issue with the bizarre view, which is unfortunately prevalent among social scientists, that causal relations are features of models only. There are some good reasons to represent causal factors with independent variables. But the association between causes and independent variables is only a desideratum in model construction. It is not a criterion for judging which things are causes and which are effects.

Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual dependence or on physical connections. This paper argues that both approaches to causation are psychologically real, with different modes of explanation promoting judgments more or less consistent with each approach. Two sets of experiments isolate (...) the contributions of counterfactual dependence and physical connections in causal ascriptions involving events with people, artifacts, or biological traits, and manipulate whether the events are construed teleologically or mechanistically. The findings suggest that when events are construed teleologically, causal ascriptions are sensitive to counterfactual dependence and relatively insensitive to the presence of physical connections, but when events are construed mechanistically, causal ascriptions are sensitive to both counterfactual dependence and physical connections. The conclusion introduces an account of causation, an "exportable dependence theory," that provides a way to understand the contributions of physical connections and teleology in terms of the functions of causal ascriptions. (shrink)

We construct a new measure of voting power that yields reasonable measurements even if the individual votes are not cast independently. Our measure hinges on probabilities of counterfactuals, such as the probability that the outcome of a collective decision would have been yes, had a voter voted yes rather than no as she did in the real world. The probabilities of such counterfactuals are calculated on the basis of causal information, following the approach by Balke and Pearl. Opinion leaders (...) whose votes have causal influence on other voters' votes can have significantly more voting power under our measure. But the new measure of voting power is also sensitive to the voting rule. We show that our measure can be regarded as an average treatment effect, we provide examples in which it yields intuitively plausible results and we prove that it reduces to Banzhaf voting power in the limiting case of independent and equiprobable votes. (shrink)

Detecting and correcting execution errors is crucial for safe and efficient goal-directed behavior. Despite intensive investigations on error processing, the cognitive foundations of this process remain unclear. Based on the presumed relation between executive attention and error processing, we implemented a seven-day EA intervention by adopting the Posner cueing paradigm to test the potential causal link from EA to error processing in healthy adults. The experimental group was trained on the Posner cueing paradigm, with a ratio of invalid cue (...) trials to valid cue trials of 5:1 and a corresponding ratio of 1:1 in the active control group. We found that the EA intervention improved EA across intervention sessions. Critically, after the EA intervention, the HEA group showed that post-error accuracy was restored to the same level as the post-correct accuracy. However, post-error slowing and the flanker effect were not modulated by the EA intervention. Furthermore, we observed that the changes in the accuracy of VC trials positively predicted the changes in PEA and that the two groups were classified according to the changes in PEA with a 61.3% accuracy. Based on these results, we propose that EA causally drives error processing. And the capabilities of the “actively catch” more attention resources and the automatic mismatch processing developed after EA intervention is transferable to error processing, thereby directly resulting in the gains in post-error adjustments. Our work informs the potential cognitive mechanisms underlying this causal link. (shrink)

Causal reasoning and game-theoretic reasoning are fundamental topics in artificial intelligence, among many other disciplines: this paper is concerned with their intersection. Despite their importance, a formal framework that supports both these forms of reasoning has, until now, been lacking. We offer a solution in the form of (structural) causal games, which can be seen as extending Pearl's causal hierarchy to the game-theoretic domain, or as extending Koller and Milch's multi-agent influence diagrams to the causal domain. (...) We then consider three key questions: i) How can the (causal) dependencies in games - either between variables, or between strategies - be modelled in a uniform, principled manner? ii) How may causal queries be computed in causal games, and what assumptions does this require? iii) How do causal games compare to existing formalisms? To address question i), we introduce mechanised games, which encode dependencies between agents' decision rules and the distributions governing the game. In response to question ii), we present definitions of predictions, interventions, and counterfactuals, and discuss the assumptions required for each. Regarding question iii), we describe correspondences between causal games and other formalisms, and explain how causal games can be used to answer queries that other causal or game-theoretic models do not support. Finally, we highlight possible applications of causal games, aided by an extensive open-source Python library. (shrink)

This work explains how different theories of causation confront causal overdetermination. Chapters clarify the problem of overdetermination and explore its fundamental aspects. It is argued that a theory of causation can account for our intuitions in overdetermination cases only by accepting that the adequacy of our claims about causation depends on the context in which they are evaluated.The author proposes arguments for causal contextualism and provides insight which is valuable for resolution of the problem. -/- These chapters enable (...) readers to quickly absorb different perspectives on overdetermination and important theories of causation, therefore it is a work that will have a broad appeal. (shrink)

Engineering failure investigations seek to reconstruct the actual causes of major engineering failures. The investigators need to establish the existence of certain past events and the actual causal relationships that these events bear to the failures in question. In this paper, I examine one method for reconstructing the actual causes of failure events, which I call "feature dependence". The basic idea of feature dependence is that some features of an event are informative about the features of its causes; therefore, (...) the investigators can use the features of a known failure event to reconstruct details of its causes. I make explicit the structure of feature dependence and the evidential basis of its key premises, and show how feature dependence works in the investigation of the American Airlines Flight 191 accident. (shrink)

Ontological dependence is a relation—or, more accurately, a family of relations—between entities or beings. For there are various ways in which one being may be said to depend upon one or more other beings, in a sense of “depend” that is distinctly metaphysical in character and that may be contrasted, thus, with various causal senses of this word. More specifically, a being may be said to depend, in such a sense, upon one or more other beings for its existence (...) or for its identity. Some varieties of ontological dependence may be analyzed in modal terms—that is, in terms of distinctly metaphysical notions of possibility and necessity—while others seem to demand an analysis in terms of the notion of essence. The latter varieties of ontological dependence may accordingly be called species of essential dependence. Notions of ontological dependence are frequently called upon by metaphysicians in their proposed analyses of other metaphysically important notions, such as the notion of substance. (shrink)

Causation is extrinsic. What an event causes depends not just on its own nature and the laws, but on the environment in which it occurs. Had an event occurred under different conditions, it may have had different effects. Yet we often want to say that causation, in at least some respect, is not extrinsic. Events exert an influence on the world themselves, independently of what other events do or do not occur in their surroundings. This paper develops an account of (...) such influence and argues that it provides a solution to the causal exclusion problem. By locating that solution largely within the metaphysics of causation, we can solve the exclusion problem without taking on a commitment to a theory of mind. (shrink)

In the foundations of Fechner's psychophysics, the concept of “functional relation” plays a highly relevant role in three different respects: (1) in respect to the principles of measurement, (2) in respect to the mind-body problem, and (3) in respect to the concept of a law of nature. In all three cases, it is important to explain the difference between a functional dependency of a variable upon another and a causal relationship between two (or more) variables. In all three respects, (...) Ernst Mach developed Fechner's ideas further and tried to extend the lessons he had learned from using the concept of a functional relation in psychophysics to the whole of science. For all three cases, I explain why they are still relevant for psychophysics and philosophy today. (shrink)

We study the identifiability and estimation of functional causal models under selection bias, with a focus on the situation where the selection depends solely on the effect variable, which is known as outcome-dependent selection. We address two questions of identifiability: the identifiability of the causal direction between two variables in the presence of selection bias, and, given the causal direction, the identifiability of the model with outcome-dependent selection. Regarding the first, we show that in the framework of (...) post-nonlinear causal models, once outcome-dependent selection is properly modeled, the causal direction between two variables is generically identifiable; regarding the second, we identify some mild conditions under which an additive noise causal model with outcome-dependent selection is to a large extent identifiable. We also propose two methods for estimating an additive noise model from data that are generated with outcome-dependent selection. (shrink)

The paper examines definitions of ‘cause’ in the epidemiological literature. Those definitions all describe causes as factors that make a difference to the distribution of disease or to individual health status. In the philosophical jargon, causes in epidemiology are difference-makers. Two claims are defended. First, it is argued that those definitions underpin an epistemology and a methodology that hinge upon the notion of variation, contra the dominant Humean paradigm according to which we infer causality from regularity. Second, despite the fact (...) that causes be defined in terms of ‘difference-making’, this cannot fixes the causal metaphysics. Causality in epidemiology ought to be interpreted according to the epistemic theory. In this approach relations are deemed causal depending on the evidence and on the available methods. Indeed, evidence to establish causal claims requires difference-making considerations; furthermore, those definitions of cause reflect the ‘variational’ epistemology and methodology of epidemiology. (shrink)