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)

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.

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)

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.

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)

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)

This article compares causal and constitutive explanation. While scientific inquiry usually addresses both causal and constitutive questions, making the distinction is crucial for a detailed understanding of scientific questions and their interrelations. These explanations have different kinds of explananda and they track different sorts of dependencies. Constitutive explanations do not address events or behaviors, but causal capacities. While there are some interesting relations between building and causal manipulation, causation and constitution are not to be confused. Constitution (...) is a synchronous and asymmetric relation between relata that cannot be conceived as independent existences. However, despite their metaphysical differences, the same key ideas about explanation largely apply to both. Causal and constitutive explanations face similar challenges (such as the problems of relevance and explanatory regress) and both are in the business of mapping networks of counterfactual dependence—i.e. mechanisms—although the relevant counterfactuals are of a different sort. In the final section the issue of developmental explanation is discussed. It is argued that developmental explanations deserve their own place in taxonomy of explanations, although ultimately developmental dependencies can be analyzed as combinations of causal and constitutive dependencies. Hence, causal and constitutive explanation are distinct, but not always completely separate forms of explanation. (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)

It is argued that causal understanding originates in experiences of acting on objects. Such experiences have consistent features that can be used as clues to causal identification and judgment. These are singular clues, meaning that they can be detected in single instances. A catalog of 14 singular clues is proposed. The clues function as heuristics for generating causal judgments under uncertainty and are a pervasive source of bias in causal judgment. More sophisticated clues such as mechanism (...) clues and repeated interventions are derived from the 14. Research on the use of empirical information and conditional probabilities to identify causes has used scenarios in which several of the clues are present, and the use of empirical association information for causal judgment depends on the presence of singular clues. It is the singular clues and their origin that are basic to causal understanding, not multiple instance clues such as empirical association, contingency, and conditional probabilities. (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)

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)

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.

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)

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)

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)

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)

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)

Reasoning about underlying causal relations drives responsibility judgments: agents are held responsible for the outcomes they cause through their behaviors. Two main causal reasoning approaches exist: dependence theories emphasize statistical relations between causes and effects, while transference theories emphasize mechanical transmission of energy. Recently, pluralistic or hybrid models, combining both approaches, have emerged as promising psychological frameworks. In this paper, we focus on causal reasoning as involved in third-party judgements of responsibility and on related judgments of (...) intention and control. In particular, we used a novel visual paradigm to investigate the combined effects of two well-known causal manipulations, namely omission and pre-emption, on these evaluations. Our findings support the view that people apply a pluralistic causal reasoning when evaluating individual responsibility for negative outcomes. In particular, we observed diminished responsibility when dependence, transference, or both fail, compared to when these mechanisms are upheld. Responsibility judgement involves a cognitive hybrid of multiple aspects of causal reasoning. However, important differences exist at the interindividual level, with most people weighting transference more than dependence. (shrink)

When agents violate norms, they are typically judged to be more of a cause of resulting outcomes. In this paper, we suggest that norm violations also affect the causality attributed to other agents, a phenomenon we refer to as "causal superseding." We propose and test a counterfactual reasoning model of this phenomenon in four experiments. Experiments 1 and 2 provide an initial demonstration of the causal superseding effect and distinguish it from previously studied effects. Experiment 3 shows that (...) this causal superseding effect is dependent on a particular event structure, following a prediction of our counterfactual model. Experiment 4 demonstrates that causal superseding can occur with violations of non-moral norms. We propose a model of the superseding effect based on the idea of counterfactual sufficiency. (shrink)

We employ a frequency-dependent asymmetric and causality analysis to investigate the connectedness between gold and cryptocurrencies during the COVID-19 pandemic. Hence, the variational mode decomposition-based quantile regression is utilised. Findings from the study divulge that the variational mode functions at the lower quantiles are mostly significant and negative indicating that gold acts as a safe haven, a diversifier at most market conditions with insignificant coefficients, and a hedge at normal market conditions for most cryptocurrencies at various investment horizons. Particularly, hedging (...) benefits mostly occur in the short- and medium-term for Bitcoin and Ripple, as well as Bitcoin and Dogecoin in the long-term with gold. This implies that there is high persistence in the hedging properties of gold with Bitcoin, followed by Ripple. We notice more significant relationship between gold and some cryptocurrencies in the long-term of the COVID-19 pandemic relative to the medium-term emphasising the delayed responses of prices to information. Investors are recommended to be observant and mindful of investing in these markets due to the different dynamics. (shrink)