Time and Singular Causation—A Computational Model

Causal queries about singular cases, which inquire whether specific events were causally connected, are prevalent in daily life and important in professional disciplines such as the law, medicine, or engineering. Because causal links cannot be directly observed, singular causation judgments require an assessment of whether a co-occurrence of two events c and e was causal or simply coincidental. How can this decision be made? Building on previous work by Cheng and Novick (2005) and Stephan and Waldmann (2018), we propose a computational model that combines information about the causal strengths of the potential causes with information about their temporal relations to derive answers to singular causation queries. The relative causal strengths of the potential cause factors are relevant because weak causes are more likely to fail to generate effects than strong causes. But even a strong cause factor does not necessarily need to be causal in a singular case because it could have been preempted by an alternative cause. We here show how information about causal strength and about two different temporal parameters, the potential causes' onset times and their causal latencies, can be formalized and integrated into a computational account of singular causation. Four experiments are presented in which we tested the validity of the model. The results showed that people integrate the different types of information as predicted by the new model.     

Is everyday causation deterministic or probabilistic?

One view of causation is deterministic: A causes B means that whenever A occurs, B occurs. An alternative view is that causation is probabilistic: the assertion means that given A, the probability of B is greater than some criterion, such as the probability of B given not-A. Evidence about the induction of causal relations cannot readily decide between these alternative accounts, and so we examined how people refute causal assertions. In four experiments most participants judged that a single counterexample of A and not-B refuted assertions of the form, A causes B. And, as a deterministic theory based on mental models predicted, participants were more likely to request multiple refutations for assertions of the form, A enables B. Similarly, refutations of the form not-A and B were more frequent for enabling than causal assertions. Causation in daily life seems to be a deterministic concept.     

Absence Causation and a Liberal Theory of Causal Explanation

For the framework of event causation—i.e. the framework according to which causation is a relation between events—absences or omissions pose a problem. Absences, it is generally agreed, are not events; so, under the framework of event causation, they cannot be causally related. But, as a matter of fact, absences are often taken to be causes or effects. The problem of absence causation is thus how to make sense of causation that apparently involves absences as causes or effects. In an influential paper, Helen Beebee offers a partial solution to the problem by giving an account of causation by absence (i.e. causation in which absences are supposed to be causes). I argue that Beebee's account can be extended to cover causation of absence (i.e. causation in which absences are supposed to be effects) as well. More importantly, I argue that the extended Beebeeian account calls for a major modification to David Lewis's theory of causal explanation, usually taken as standard. Compared to the standard theory, the result of this modification, which I shall call ‘the liberal theory of causal explanation’, has, among other things, the advantage of being able to accommodate causal explanations in which the explananda are not given in terms of events.     

A Deliberative Approach to Causation

Fundamental physics makes no clear use of causal notions; it uses laws that operate in relevant respects in both temporal directions and that relate whole systems across times. But by relating causation to evidence, we can explain how causation fits in to a physical picture of the world and explain its temporal asymmetry. This paper takes up a deliberative approach to causation, according to which causal relations correspond to the evidential relations we need when we decide on one thing in order to achieve another. Tamsin's taking her umbrella is a cause of her staying dry, for example, if and only if her deciding to take her umbrella for the sake of staying dry is adequate grounds for believing she'll stay dry. This correspondence explains why causation matters: knowledge of causal structure helps us make decisions that are evidence of outcomes we seek. The account also explains why we can control the future and not the past, and why causes come before their effects. When agents properly deliberate, their decisions can never count as evidence for any outcomes they may seek in the past. From this it follows that causal relations don't run backwards. This deliberative asymmetry is itself traced back to asymmetries of evidence and entropy, providing a new way of deriving causal asymmetry from temporally symmetric laws.     

Reversing the Counterfactual Analysis of Causation

The counterfactual analysis of causation has focused on one particular counterfactual conditional, taking as its starting‐point the suggestion that C causes E iff (～C □→ ～E). In this paper, some consequences are explored of reversing this counterfactual, and developing an account starting with the idea that C causes E iff (～E □→ ～C). This suggestion is discussed in relation to the problem of pre‐emption. It is found that the ‘reversed’ counterfactual analysis can handle even the most difficult cases of pre‐emption with only minimal complications. The paper closes with a discussion of the wider philosophical implications of developing a reversed counterfactual analysis, especially concerning the differentiation of causes from causal conditions, causation by absences, and the extent to which causes suffice for their effects.     

Social support,coping, and depressive symptoms in cardiac illness among Hispanic and non-Hispanic White cardiac patients

In Multi-Trait Multi-Method (MTMM) studies of causal attributions for laboratory events, there is little evidence of convergent and discriminant validity for attribution measures. We report the first MTMM study to investigate the validity of two methods of eliciting causal beliefs for an illness, specifically, myocardial infarction. Adult respondents (N?=?107) listed causes of MI, then completed questionnaire rating scales for causal beliefs for MI. Measures were compared using both Campbell and Fiske's approach to MTMM analyses, and a Confirmatory Factor Analysis approach. Neither single item measures causal beliefs, nor scales of causal beliefs derived using exploratory factor analysis provided much evidence of convergent and discriminant validity. Confirmatory factor analysis showed that a model containing only causal belief factors provided a moderately good fit to the data. Adding a questionnaire method factor significantly improved the fit of the model, as well as substantially changing the pattern of factor loadings: loadings of questionnaire items on causal belief factors were markedly reduced. These results highlight major problems with the measurement of causal beliefs, and in particular question the validity of factor analysis of questionnaire measures of causal beliefs. They also suggest that at least some of the MI causal belief factors reported in the literature are artefacts of common questionnaire method variance.     

Causal Relata: Tokens, Types, or Variables?

The literature on causation distinguishes between causal claims relating properties or types and causal claims relating individuals or tokens. Many authors maintain that corresponding to these two kinds of causal claims are two different kinds of causal relations. Whether to regard causal relations among variables as yet another variety of causation is also controversial. This essay maintains that causal relations obtain among tokens and that type causal claims are generalizations concerning causal relations among these tokens.     

Epistemic normativity in Kant's “Second Analogy”

In the “Second Analogy,” Kant argues that, unless mental contents involve the concept of causation, they cannot represent an objective temporal sequence. According to Kant, deploying the concept of causation renders a certain temporal ordering of representations necessary, thus enabling objective representational purport. One exegetical question that remains controversial is this: how, and in what sense, does deploying the concept of cause render a certain ordering of representations necessary? I argue that this necessitation is a matter of epistemic normativity: with certain causal presuppositions in place, the individual is obliged to make a judgment with certain temporal contents, on pain of irrationality. To make this normatively obligatory judgment, the subject must place her perceptual representations in a certain order. This interpretation fits Kant's text, his argumentative aims, and his broader views about causal inference, better than rival interpretations can. This result has important consequences for the ongoing debate over the role of normativity in Kant's philosophy of mind.     

Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment

Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge—an interconnected causal network, where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms—causal islands—such that events in different mechanisms are not thought to be related even when they belong to the same causal chain. To distinguish these possibilities, we tested whether people make transitive judgments about causal chains by inferring, given A causes B and B causes C, that A causes C. Specifically, causal chains schematized as one chunk or mechanism in semantic memory (e.g., exercising, becoming thirsty, drinking water) led to transitive causal judgments. On the other hand, chains schematized as multiple chunks (e.g., having sex, becoming pregnant, becoming nauseous) led to intransitive judgments despite strong intermediate links ((Experiments 1–3). Normative accounts of causal intransitivity could not explain these intransitive judgments (Experiments 4 and 5).     

Causal Compatibilism – What Chance?

Orthodox physicalism has a problem with mental causation. If physics is complete and mental events are not identical to physical events (as multiple-realisation arguments imply) it seems as though there is no causal work for the mental to do. This paper examines some recent attempts to overcome this problem by analysing causation in terms of counterfactuals or conditional probabilities. It is argued that these solutions cannot simultaneously capture the force of the completeness of physics and make room for mental causation.     

AGAINST LEWIS's NEW THEORY OF CAUSATION: A STORY WITH THREE MORALS

Abstract: A recent paper by David Lewis, “Causation as Influence”, provides a new theory of causation. This paper presents an argument against the theory, using a series of counterexamples that are, I think, of independent interest to philosophers of causation. I argue that (a) the relation asserted by a claim of the form “C was a cause of E” is distinct from the relation of causal influence, (b) the former relation depends very much, contra Lewis, on the individuation conditions for the event E, and (c) Lewis's account is unsatisfactory as an analysis of either kind of relation. The counterexamples presented in this paper provide, I suggest, some insight into the reasons for the failure of counterfactual accounts of causal relations.     

Temporal necessity; Hard facts/soft facts

Conclusion In conclusion, then, the notion of temporal necessity is certainly queer and perhaps a misnomer. It really has little to do with temporality per se and everything to do with counterfactual openness or closedness. We have seen that the future is as unalterable as the past, but that this purely logical truth is not antithetical to freedom or contingency. Moreover, we have found certain past facts are counterfactually open in that were future events or actualities to be other than they will be, these past facts would have been different as a consequence. God's beliefs about the future are such past facts. Moreover, the effects of actions which God would have taken had He believed differently are also such past facts. Oddly enough, then, virtually any past fact is potentially counterfactually open, and the only necessity that remains is purely de facto. We, of course, do not in general know which events of the past depend counterfactually on present actions, and those cases we do know about seem rather trivial. Our intuitions of the necessity, unalterability, and unpreventability of the past as opposed to the future stem from the impossibility of backward causation, which is precluded by the dynamic nature of time and becoming. But the counterfactual dependence of God's beliefs on future events or actualities is not a case of backward causation: rather future-tense propositions are true in virtue of what will happen, given a view of truth as correspondence, and God simply has the essential property of knowing all and only true propositions. With regard to the future, virtually all facts are counterfactually open, and therefore future-tense propositions are not temporally necessary. Propositions thus move from being temporally contingent to being temporally necessary when all the opportunities to affect things counterfactually have slipped by. Hence, the mere fact that an event is past is no indication that it is counterfactually closed. This is especially evident in the case of God's foreknowledge. If we say that God foreknows that I shall do x and therefore I cannot refrain from doing x, lest I change God's past foreknowledge, we are being deceived by a modality which has nothing to do with my power or freedom. All that is impossible is the conjunction of God's foreknowledge that p and of ~ p; but this modality in sensu composito has no bearing on my ability to act such that ~ p would be true and God would have foreknown differently. Temporal necessity, then, turns out to be only obliquely temporal and modally weak, certainly no threat to freedom or divine foreknowledge.     

Causal concepts and temporal ordering

Though common sense says that causes must temporally precede their effects, the hugely influential interventionist account of causation makes no reference to temporal precedence. Does common sense lead us astray? In this paper, I evaluate the power of the commonsense assumption from within the interventionist approach to causal modeling. I first argue that if causes temporally precede their effects, then one need not consider the outcomes of interventions in order to infer causal relevance, and that one can instead use temporal and probabilistic information to infer exactly when X is causally relevant to Y in each of the senses captured by Woodward’s interventionist treatment. Then, I consider the upshot of these findings for causal decision theory, and argue that the commonsense assumption is especially powerful when an agent seeks to determine whether so-called “dominance reasoning” is applicable.

     

The mental representation of causal conditional reasoning: mental models or causal models

In this paper, two experiments are reported investigating the nature of the cognitive representations underlying causal conditional reasoning performance. The predictions of causal and logical interpretations of the conditional diverge sharply when inferences involving pairs of conditionals—such as if P₁then Q and if P₂then Q—are considered. From a causal perspective, the causal direction of these conditionals is critical: are the P_icauses of Q; or symptoms caused byQ. The rich variety of inference patterns can naturally be modelled by Bayesian networks. A pair of causal conditionals where Q is an effect corresponds to a “collider” structure where the two causes (P_i) converge on a common effect. In contrast, a pair of causal conditionals where Q is a cause corresponds to a network where two effects (P_i) diverge from a common cause. Very different predictions are made by fully explicit or initial mental models interpretations. These predictions were tested in two experiments, each of which yielded data most consistent with causal model theory, rather than with mental models.     

The logic of causal methods in social science

Two kinds of causal inference rules which are widely used by social scientists are investigated. Two conceptions of causation also widely used are explicated — the INUS and probabilistic conceptions of causation. It is shown that the causal inference rules which link correlation, a kind of partial correlation, and a conception of causation areinvalid. It is concluded anew methodology is required for causal inference.     

Contiguity and the causal theory of memory

In Memory: A Philosophical Study, Bernecker argues for an account of contiguity. This Contiguity View is meant to solve relearning and prompting, wayward causation problems plaguing the causal theory of memory. I argue that Bernecker’s Contiguity View fails in this task. Contiguity is too weak to prevent relearning and too strong to allow prompting. These failures illustrate a problem inherent in accounts of memory causation. Relearning and prompting are both causal relations, wayward only with respect to our interest in specifying remembering’s requirements. Solving them requires saying more about remembering, not causation. I conclude by sketching such an account.     

Agent Causation and the Phenomenology of Agency

Several philosophers claim that the phenomenology of one's own agency conflicts with standard causal theories of action, couched in terms of causation by mental events or states. Others say that the phenomenology is prima facie incompatible with such a theory, even if in the end, a reconciliation can be worked out. Here, it is argued that the type of action theory in question is consistent with what can plausibly be said to be presented to us in our experience of our agency. Several routes to a claim that there is nevertheless a prima facie incompatibility are examined, and all are found wanting. The phenomenology of agency, it is argued, is no threat to a standard causal theory of action.     

Cause and essence

Essence and causation are fundamental in metaphysics, but little is said about their relations. Some essential properties are of course causal, as it is essential to footprints to have been caused by feet. But I am interested less in causation's role in essence than the reverse: the bearing a thing's essence has on its causal powers. That essencemight make a causal contribution is hinted already by the counterfactual element in causation; and the hint is confirmed by the explanation essence offers of something otherwise mysterious, namely, how events exactly alike in every ordinary respect, like the bolt'ssuddenly snapping and its snapping per se, manage to disagree in what they cause. Some prior difference must exist between these events to make their causal powers unlike. Paradoxically, though, it can only be in point of a property, suddenness, which both events possess in common. Only by postulating a difference in themanner — essential or accidental — of the property's possession is the paradox resolved. Next we need an account of causation in which essence plays an explicit determinative role. That account, based on the idea that causes should becommensurate with their effects, is thatx causesy only if nothing essentially poorer would have done, and nothing essentially richer was needed.Something like the present approach to causation was proposed in the last two chapters of my dissertation (1986, Things, University of California, Berkeley). In Yablo (1987) the essentialist half of the story is laid out in some detail, and the connection with causation briefly indicated; this paper takes the cause/essence connection as its main object. I am grateful to Louise Antony, Paul Boghossian, Sin Yee Chan, Donald Davidson, John Drennan, Graeme Forbes, Sally Haslanger, Jaegwon Kim, Louis Loeb, Vann McGee, Sarah Patterson, Gideon Rosen, Larry Sklar, William Taschek, Ken Walton, and Crispin Wright for discussion and advice. Research for this paper was supported by the National Endowment for the Humanities and the Social Sciences and Humanities Research Council of Canada.     

How Could There Be True Causal Claims Without There Being Special Causal Facts in the World?

Some philosophers of physics recently expressed their skepticism about causation (Norton 2003b, 2007). However, this is not new. The view that causation does not refer to any ontological category perhaps can be attributed to Hume, Kant and Russell. On the other hand, some philosophers (Wesley Salmon and Phil Dowe) view causation as a physical process and some others (Cartwright) view causation as making claims about capacities possessed by objects. The issue about the ontological status of causal claims involves issues concerning the ontological status of capacity, modality and dispositional claims. In this paper, my goal is to show that without engaging metaphysical debates about the ontological status of causal claims, it can be shown that we can objectively assign truth values to these statements. I argue that for causal claims to be objective we don't need to postulate the existence of special facts (specific to causal claims) in addition to ordinary physical facts described by physical theories. This, I think, is enough to justify the usefulness of this concept in certain branches (may be all) of science. Once this is achieved, there is no need to engage in unnecessary metaphysical debates. So, even if advanced physical theories don't mention this notion, causal reasoning can still be important in understanding the world not in the sense that science discovers special ontological category called causation but in the sense that we come to know certain facts about the world.     

Transitivity and the ontology of causation

It is argued that it is very hard to analyse causation in such a way that prevents everything from causing everything else. This is particularly true if we assume that the causal relation is transitive, for it all too often happens that causal chains that we wish to keep separate pass through common intermediate events. It is also argued that treating causes as aspects of events, rather than the events themselves, will not solve this problem. This is because aspects have to be highly disjunctive, and disjunctive conditions tend to undermine causal connections, a fact that is most clearly seen when causation is analysed in terms of INUS conditions. It is concluded that reductive analyses of causation do not work, and that transitivity can only be guaranteed in cases where the elements of the causal chain constitute an independently understood causal process.