First published in 2001, Causality in Macroeconomics addresses the long-standing problems of causality while taking macroeconomics seriously. The practical concerns of the macroeconomist and abstract concerns of the philosopher inform each other. Grounded in pragmatic realism, the book rejects the popular idea that macroeconomics requires microfoundations, and argues that the macroeconomy is a set of structures that are best analyzed causally. Ideas originally due to Herbert Simon and the Cowles Commission are refined and generalized to non-linear systems, particularly (...) to the non-linear systems with cross-equation restrictions that are ubiquitous in modern macroeconomic models with rational expectations (with and without regime-switching). These ideas help to clarify philosophical as well as economic issues. The structural approach to causality is then used to evaluate more familiar approaches to causality due to Granger, LeRoy and Glymour, Spirtes, Scheines and Kelly, as well as vector autoregressions, the Lucas critique, and the exogeneity concepts of Engle, Hendry and Richard. (shrink)

This monograph looks at causal nets from a philosophical point of view. The author shows that one can build a general philosophical theory of causation on the basis of the causal nets framework that can be fruitfully used to shed new light on philosophical issues. Coverage includes both a theoretical as well as application-oriented approach to the subject. The author first counters David Hume’s challenge about whether causation is something ontologically real. The idea behind this is that good metaphysical concepts (...) should behave analogously to good theoretical concepts in scientific theories. In the process, the author offers support for the theory of causal nets as indeed being a correct theory of causation. Next, the book offers an application-oriented approach to the subject. The author shows that causal nets can investigate philosophical issues related to causation. He does this by means of two exemplary applications. The first consists of an evaluation of Jim Woodward’s interventionist theory of causation. The second offers a contribution to the new mechanist debate. Introductory chapters outline all the formal basics required. This helps make the book useful for those who are not familiar with causal nets, but interested in causation or in tools for the investigation of philosophical issues related to causation. (shrink)

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.

Donald J. Zeyl begins the historical section of the book by tracing divine causation throughout classical Greek philosophy. Some of the Pre-Socratics held to a single god as the source of rational order or change. These views suggested that the cosmos may be explained teleologically. Plato takes up that suggested promise in his Phaedo and finds it wanting. Instead, he looks to Forms as (formal) causes of natural processes. This direction of inquiry leads him to postulate, in the Republic, the (...) Form of the Good as the “unhypothetical (causal) first principle.” In Plato’s later writings, most notably in the Timaeus, Plato presents a full-blown teleological account of both the universe at large and the varieties of living things that inhabit the earth. The agent that brings about the conformity of the world to the Forms is the divine Demiurge. -/- Aristotle inherits from Plato the belief that processes in the natural world are to be understood teleologically. These processes are explained by the nature (or form) of the organism itself. Aristotle’s world has no beginning and thus has no place for an original efficient cause to get the world started. Aristotle’s “Unmoved Mover” plays no causal role in the processes of the natural world, all of which are exhaustively explained in terms of Aristotle’s well-known theory of the “four causes.” Nevertheless, the Unmoved Mover is a final cause. -/- After Aristotle, only the Stoics offered an account of divine causal agency. As pantheists, the Stoics identified the world with a divine rational principle they named the Logos. All events, natural and social, are completely determined by Reason, so the Stoics were strict determinists, both in their natural philosophy and in their social and ethical thought. (shrink)

Wesley Salmon is renowned for his seminal contributions to the philosophy of science. He has powerfully and permanently shaped discussion of such issues as lawlike and probabilistic explanation and the interrelation of explanatory notions to causal notions. This unique volume brings together twenty-six of his essays on subjects related to causality and explanation, written over the period 1971-1995. Six of the essays have never been published before and many others have only appeared in obscure venues. The volume includes a (...) section of accessible introductory pieces, as well as more advanced and technical pieces, and will make essential work in the philosophy of science readily available to both scholars and students. (shrink)

Causal theories of mental content attempt to explain how thoughts can be about things. They attempt to explain how one can think about, for example, dogs. These theories begin with the idea that there are mental representations and that thoughts are meaningful in virtue of a causal connection between a mental representation and some part of the world that is represented. In other words, the point of departure for these theories is that thoughts of dogs are about dogs because dogs (...) cause the mental representations of dogs. (shrink)

The physical realm is causally closed, according to physicalists like me. But why is it causally closed, what metaphysically explains causal closure? I argue that reductive physicalists are committed to one explanation of causal closure to the exclusion of any independent explanation, and that as a result, they must give up on using a causal argument to attack mind–body dualism. Reductive physicalists should view dualism in much the way that we view the hypothesis that unicorns exist, or that the Kansas (...) City Royals won the 2003 World Series: false, but not objectionable in any distinctively causal way. My argument turns on connections between explanation, counterfactuals, and inductive confirmation. (shrink)

In this paper we develop an analysis of dispositions by means of causal Bayes nets. In particular, we analyze dispositions as cause-effect structures that increase the probability of the manifestation when the stimulus is brought about by intervention in certain circumstances. We then highlight several advantages of our analysis and how it can handle problems arising for classical analyses of dispositions such as masks, mimickers, and finks.

This book offers a discussion about how people think, talk, learn, and explain things in causal terms in terms of action and manipulation. Sloman also reviews the role of causality, causal models, and intervention in the basic human cognitive functions: decision making, reasoning, judgement, categorization, inductive inference, language, and learning.

Hitchcock demonstrated that the validity of causal exclusion arguments as well as the plausibility of several of their premises hinges on the specific theory of causation endorsed. In this paper I show that the validity of causal exclusion arguments—if represented within the theory of causal Bayes nets the way Gebharter suggests—actually requires much weaker premises than the ones which are typically assumed. In particular, neither completeness of the physical domain nor the no overdetermination assumption are required.

Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal (...) connections and statistical associations. Cited in more than 2,100 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. In this revised edition, Judea Pearl elucidates thorny issues, answers readers' questions, and offers a panoramic view of recent advances in this field of research. Causality will be of interest to students and professionals in a wide variety of fields. Dr Judea Pearl has received the 2011 Rumelhart Prize for his leading research in Artificial Intelligence and systems from The Cognitive Science Society. (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)

Causal decision theory (CDT) cares only about the effects of a contemplated act, not its causes. The article constructs a case in which CDT consequently recommends a bet that the agent is certain to lose, rather than a bet that she is certain to win. CDT is plainly giving wrong advice in this case. It therefore stands refuted. 1 The Argument2 The Argument in More Detail2.1 The betting mechanism2.2 Soft determinism2.3 The content of P 2.4 The argument again3 The Descriptive (...) Premise3.1 Causal decision theory3.2 Causal decision theory prefers A14 The Normative Premise5 Objections5.1 Table 1 and Table 2 are misleading5.2 The agency theory of causation5.3 The payment mechanism5.4 Newcomb’s problem5.5 Against the normative premise5.6 Drop soft determinism. (shrink)

Causal reductionism is the widespread assumption that there is no room for additional causes once we have accounted for all elementary mechanisms within a system. Due to its intuitive appeal, causal reductionism is prevalent in neuroscience: once all neurons have been caused to fire or not to fire, it seems that causally there is nothing left to be accounted for. Here, we argue that these reductionist intuitions are based on an implicit, unexamined notion of causation that conflates causation with prediction. (...) By means of a simple model organism, we demonstrate that causal reductionism cannot provide a complete and coherent account of ‘what caused what’. To that end, we outline an explicit, operational approach to analyzing causal structures. (shrink)

Among the factors necessary for the occurrence of some event, which of these are selectively highlighted in its explanation and labeled as causes — and which are explanatorily omitted, or relegated to the status of background conditions? Following J. S. Mill, most have thought that only a pragmatic answer to this question was possible. In this paper I suggest we understand this ‘causal selection problem’ in causal-explanatory terms, and propose that explanatory trade-offs between abstraction and stability can provide a principled (...) solution to it. After sketching that solution, it is applied to a few biological examples, including to a debate concerning the ‘causal democracy’ of organismal development, with an anti-democratic (though not a gene-centric) moral. (shrink)

According to orthodox causal decision theory, performing an action can give you information about factors outside of your control, but you should not take this information into account when deciding what to do. Causal decision theorists caution against an irrational policy of 'managing the news'. But, by providing information about factors outside of your control, performing an act can give you two, importantly different, kinds of good news. It can tell you that the world in which you find yourself is (...) good in ways you can't control, and it can also tell you that the act itself is in a position to make the world better. While the first kind of news does not speak in favor of performing an act, I believe that the second kind of news does. I present a revision of causal decision theory which advises you to manage the news about the good you stand to promote, while ignoring news about the good the world has provided for you. (shrink)

Recent attempts to resolve the Paradox of the Gatecrasher rest on a now familiar distinction between individual and bare statistical evidence. This paper investigates two such approaches, the causal approach to individual evidence and a recently influential (and award-winning) modal account that explicates individual evidence in terms of Nozick's notion of sensitivity. This paper offers counterexamples to both approaches, explicates a problem concerning necessary truths for the sensitivity account, and argues that either view is implausibly committed to the impossibility of (...) no-fault wrongful convictions. The paper finally concludes that the distinction between individual and bare statistical evidence cannot be maintained in terms of causation or sensitivity. We have to look elsewhere for a solution of the Paradox of the Gatecrasher. (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)

Evidential decision theory (EDT) says that the choiceworthiness of an option depends on its evidential connections to possible outcomes. Causal decision theory (CDT) holds that it depends on your beliefs about its causal connections. While Newcomb cases support CDT, Arif Ahmed has described examples that support EDT. A new account is needed to get all cases right. I argue that an option A’s choiceworthiness is determined by the probability that a good outcome ensues at possible A-worlds that match actuality in (...) the facts causally unaffected by your decision (the “unaffected facts”). Moreover, you should evaluate A on the assumption that A is compossible with the unaffected facts. This view entails that you should use EDT when evaluating A on the assumption that the unaffected facts determine your action, but use CDT when assessing A on the opposite assumption. A’s choiceworthiness equals a weighted average of these conditional assessments. The weights are determined by your beliefs about whether the unaffected fact determine your action. This account gets both Newcomb and Ahmed cases right. According to an influential view, whether you take the unaffected facts to determine your action can make a difference to whether you can regard yourself as free and the action as being under your control. While my account is neutral on this issue, it entails that whether you take the unaffected facts to determine your action is important in a different way: it matters to whether you should follow EDT or CDT. (shrink)

The recent literature on causality has seen the introduction of several distinctions within causality, which are thought to be important for understanding the widespread scientific practice of focusing causal explanations on a subset of the factors that are causally relevant for a phenomenon. Concepts used to draw such distinctions include, among others, stability, specificity, proportionality, or actual-difference making. In this contribution, I propose a new distinction that picks out an explanatorily salient class of causes in biological systems. Some (...) select causes in complex biological systems, I argue, have the property of enabling coherent causal control of these systems. Examples of such control variables include hormones and other signaling molecules, e.g., TOR (target of rapamycin), morphogens or the products of homeotic selector genes in embryonic pattern formation. I propose an analysis of this notion based on concepts borrowed from causal graph theory. (shrink)

The problem of the man who met death in Damascus appeared in the infancy of the theory of rational choice known as causal decision theory. A straightforward, unadorned version of causal decision theory is presented here and applied, along with Brian Skyrms’ deliberation dynamics, to Death in Damascus and similar problems. Decision instability is a fascinating topic, but not a source of difficulty for causal decision theory. Andy Egan’s purported counterexample to causal decision theory, Murder Lesion, is considered; a simple (...) response shows how Murder Lesion and similar examples fail to be counterexamples, and clarifies the use of the unadorned theory in problems of decision instability. I compare unadorned causal decision theory to previous treatments by Frank Arntzenius and by Jim Joyce, and recommend a well-founded heuristic that all three accounts can endorse. Whatever course deliberation takes, causal decision theory is consistently a good guide to rational action. (shrink)

Causal accounts of scientific explanation are currently broadly accepted (though not universally so). My first task in this paper is to show that, even for a causal approach to explanation, significant features of explanatory practice are not determined by settling how causal facts bear on the phenomenon to be explained. I then develop a broadly causal approach to explanation that accounts for the additional features that I argue an explanation should have. This approach to explanation makes sense of several aspects (...) of actual explanatory practice, including the widespread use of equilibrium explanations, the formulation of distinct explanations for a single event, and the tight relationship between explanations of events and explanations of causal regularities. (shrink)

This paper sketches a causal account of scientific explanation designed to sustain the judgment that high-level, detail-sparse explanations—particularly those offered in biology—can be at least as explanatorily valuable as lower-level counterparts. The motivating idea is that complete explanations maximize causal economy: they cite those aspects of an event’s causal run-up that offer the biggest-bang-for-your-buck, by costing less (in virtue of being abstract) and delivering more (in virtue making the event stable or robust).

Event-causal libertarians maintain that an agent’s freely bringing about a choice is reducible to states and events involving him bringing about the choice. Agent-causal libertarians demur, arguing that free will requires that the agent be irreducibly causally involved. Derk Pereboom and Meghan Griffith have defended agent-causal libertarianism on this score, arguing that since on event-causal libertarianism an agent’s contribution to his choice is exhausted by the causal role of states and events involving him, and since these states and events leave (...) it open which decision he will make, he does not settle which decision occurs, and thus “disappears.” My aim is to explain why this argument fails. In particular, I demonstrate that event-causal libertarians can dismantle the argument by enriching the reductive base in their analysis of free will to include a state that plays the functional role of the self-determining agent and with which the agent is identified. (shrink)

The Causal Exclusion Problem is raised in many domains, including in the metaphysics of macroscopic objects. If there is a complete explanation of macroscopic effects in terms of the microscopic entities that compose macroscopic objects, then the efficacy of the macroscopic will be threatened with exclusion. I argue that we can avoid the problem if we accept that macroscopic objects are ontically vague. Then, it is indeterminate which collection of microscopic entities compose them, and so information about microscopic entities is (...) insufficient to provide a complete explanation of certain properties of macroscopic objects. After outlining this solution, I consider several objections. (shrink)

In what follows, I shall presuppose the ecumenical core of the causal powers metaphysics. The argument of this paper concerns what may appear at first to be a wholly unrelated matter, the metaphysics of free will. However, an adequate account of freedom requires, in my judgment, a notion of a distinctive variety of causal power, one which tradition dubs ‘agent-causal power’. I will first develop this notion and clarify its relationship to other notions. I will then respond to a number (...) of objections either to the possibility of a power so explicated or to its sufficiency for grounding an adequate account of human freedom. (shrink)

The essay presents a novel counterexample to Causal Decision Theory (CDT). Its interest is that it generates a case in which CDT violates the very principles that motivated it in the first place. The essay argues that the objection applies to all extant formulations of CDT and that the only way out for that theory is a modification of it that entails incompatibilism. The essay invites the reader to find this consequence of CDT a reason to reject it.

In this paper I reconstruct and evaluate the validity of two versions of causal exclusion arguments within the theory of causal Bayes nets. I argue that supervenience relations formally behave like causal relations. If this is correct, then it turns out that both versions of the exclusion argument are valid when assuming the causal Markov condition and the causal minimality condition. I also investigate some consequences for the recent discussion of causal exclusion arguments in the light of an interventionist theory (...) of causation such as Woodward's (2003) and discuss a possible objection to my causal Bayes net reconstruction. (shrink)

The argument from causal closure of the physical is usually considered the most powerful argument in favor of the ontological doctrine of physicalism. Many authors, most notably Papineau, assume that CCP implies that physicalism is supported by physics. I demonstrate, however, that physical science has no bias in the ontological debate between proponents of physicalism and dualism. I show that the arguments offered for CCP are effective only against the accounts of mental causation based on the action of the mental (...) forces of a Newtonian nature, i.e. those which manifest themselves by causing accelerations. However, it is conceivable and possible that mental causation is manifested through the redistribution of energy, momentum and other conserved quantities in the system, brought about by altering the state probability distribution within the living system and leading to anomalous correlations of neural processes. After arguing that a probabilistic, interactionist model of mental causation is conceivable, which renders the argument from causal closure of the physical ineffective, I point to some basic features that such a model must have in order to be intelligible. At the same time, I indicate the way that conclusive testing of CCP can be done within the theoretical framework of physics. (shrink)

The argument from causal closure of the physical is usually considered the most powerful argument in favor of the ontological doctrine of physicalism. Many authors, most notably Papineau, assume that CCP implies that physicalism is supported by physics. I demonstrate, however, that physical science has no bias in the ontological debate between proponents of physicalism and dualism. I show that the arguments offered for CCP are effective only against the accounts of mental causation based on the action of the mental (...) forces of a Newtonian nature, i.e. those which manifest themselves by causing accelerations. However, it is conceivable and possible that mental causation is manifested through the redistribution of energy, momentum and other conserved quantities in the system, brought about by altering the state probability distribution within the living system and leading to anomalous correlations of neural processes. After arguing that a probabilistic, interactionist model of mental causation is conceivable, which renders the argument from causal closure of the physical ineffective, I point to some basic features that such a model must have in order to be intelligible. At the same time, I indicate the way that conclusive testing of CCP can be done within the theoretical framework of physics. (shrink)

Causal modelling provides a powerful set of tools for identifying causal structure from observed correlations. It is well known that such techniques fail for quantum systems, unless one introduces 'spooky' hidden mechanisms. Whether one can produce a genuinely quantum framework in order to discover causal structure remains an open question. Here we introduce a new framework for quantum causal modelling that allows for the discovery of causal structure. We define quantum analogues for core features of classical causal modelling techniques, including (...) the causal Markov condition and faithfulness. Based on the process matrix formalism, this framework naturally extends to generalised structures with indefinite causal order. (shrink)

Until recently, many philosophers took Causal Decision Theory to be more successful than its rival, Evidential Decision Theory. Things have changed, however, with a renewed concern that cases involving an extreme form of decision instability are counterexamples to CDT :392–403, 1984; Egan in Philos Rev 116:93–114, 2007). Most prominent among those cases of extreme decision instability is the Psychopath Button, due to Andy Egan; in that case, CDT recommends a seemingly absurd act that almost certainly results in your death. This (...) renewed attention to decision instability has spurned an array of modifications to and rejections of CDT. I argue, however, that the Psychopath Button and its ilk are no counterexamples to CDT. That is, given the causalist’s commitments in Newcomb Problems, they already have the tools to justify CDT’s verdict in Egan-style cases of extreme decision instability. I first argue that there is no reason to think the Psychopath Button is a counterexample to CDT; in particular, many philosophers have placed too much weight on pre-theoretic intuition in Egan-cases, and apart from pre-theoretic intuition, arguments against CDT in cases of extreme decision instability are flawed. My second claim is that the causalist can provide good reasons for following CDT in cases of extreme decision instability. I present a new case, the Two Button Defense, that highlights precisely why the causalist can reasonably follow CDT in even the Psychopath Button. CDT therefore stands as a viable decision theory, without need for modification, restriction, or rejection. (shrink)

Causal theories of perception typically have problems in explaining deviant causal chains. They also have difficulty with other unusual putative cases of perception involving prosthetic aids, defective perception, scientifically extended cases of perception, and so on. But I show how a more adequate reflexive causal theory, in which objects or properties X cause a perceiver to acquire X-related dispositions toward that very same item X, can provide a plausible and principled perceptual explanation of all of these kinds of cases. A (...) critical discussion of David Lewis's perceptual descriptivist views is also provided, including a defense of the logical possibility of systematic misperception or perceptual error for a perceiver, in spite of its empirical improbability. (shrink)

We start this paper by arguing that causality should, in analogy with force in Newtonian physics, be understood as a theoretical concept that is not explicated by a single definition, but by the axioms of a theory. Such an understanding of causality implicitly underlies the well-known theory of causal nets and has been explicitly promoted by Glymour. In this paper we investigate the explanatory warrant and empirical content of TCN. We sketch how the assumption of directed cause–effect relations (...) can be philosophically justified by an inference to the best explanation. We then ask whether the explanations provided by TCN are merely post-facto or have independently testable empirical content. To answer this question we develop a fine-grained axiomatization of TCN, including a distinction of different kinds of faithfulness. A number of theorems show that although the core axioms of TCN are empirically empty, extended versions of TCN have successively increasing empirical content. (shrink)

One familiar affirmative answer to this question holds that these facts suffice to entail that Descartes' picture of the human mind must be mistaken. On Descartes' view, our mind or soul (the only essential part of ourselves) has no spatial location. Yet it directly interacts with but one physical object, the brain of that body with which it is, 'as it were, intermingled,' so as to 'form one unit.' The radical disparity posited between a nonspatial mind, whose intentional and conscious (...) properties are had by no physical object, and a spatial body, all of whose properties are had by no mind, has prompted some to conclude that, pace Descartes, causal interaction between the two is impossible. Jaegwon Kim has recently given a new twist to this old line of thought.(1) In the present essay, I will use Kim's argument as a springboard for motivating my own favored picture of the metaphysics of mind and body and then discussing how an often vilified account of freedom of the will may be realized within it. (shrink)

The Spanish Jesuit Francisco Suarez was an eminent philosopher and theologian whose _Disputationes Metaphysicae_ was first published in Spain in 1597 and was widely studied throughout Europe during the seventeenth century. The _Disputationes Metaphysicae_ had a great influence on the development of early modern philosophy and on such well-known figures as Descartes and Leibniz. This is the first time that Disputations 17, 18, and 19 have been translated into English. The _Metaphysical Disputations_ provide an excellent philosophical introduction to the medieval (...) Aristotelian discussion of efficient causality. The work constitutes a synthesis of monumental proportions: problematic issues are lucidly delineated and the various arguments are laid out in depth. Disputations 17, 18, and 19 deal explicitly with such issues as the nature of causality, the types of efficient causes, the prerequisites for causal action, causal contingency, human free choice, and chance. (shrink)

This article argues that the causal loops that occur in some time-travel scenarios and in certain solutions of the theory of relativity are no more mysterious than the infinitely descending causal chains familiar from Newtonian mechanics.

We develop a new version of the causal theory of spacetime. Whereas traditional versions of the theory seek to identify spatiotemporal relations with causal relations, the version we develop takes causal relations to be the grounds for spatiotemporal relations. Causation is thus distinct from, and more basic than, spacetime. We argue that this non-identity theory, suitably developed, avoids the challenges facing the traditional identity theory.

Bayes nets are formal representations of causal systems that many psychologists have claimed as plausible mental representations. One purported advantage of Bayes nets is that they may provide a theory of counterfactual conditionals, such as If Calvin had been at the party, Miriam would have left early. This article compares two proposed Bayes net theories as models of people's understanding of counterfactuals. Experiments 1-3 show that neither theory makes correct predictions about backtracking counterfactuals (in which the event of the if-clause (...) occurs after the event of the then-clause), and Experiment 4 shows the same is true of forward counterfactuals. An amended version of one of the approaches, however, can provide a more accurate account of these data. (shrink)

Causal descriptivism and its relative nominal descriptivism are critically examined. It is argued that they do not manage to undermine the principal conclusions of the new theory of reference.

"Correlation is not causation" is one of the mantras of the sciences—a cautionary warning especially to fields like epidemiology and pharmacology where the seduction of compelling correlations naturally leads to causal hypotheses. The standard view from the epistemology of causation is that to tell whether one correlated variable is causing the other, one needs to intervene on the system—the best sort of intervention being a trial that is both randomized and controlled. In this paper, we argue that some purely correlational (...) data contains information that allows us to draw causal inferences: statistical noise. Methods for extracting causal knowledge from noise provide us with an alternative to randomized controlled trials that allows us to reach causal conclusions from purely correlational data. (shrink)

A neuroscience-based approach has recently been proposed for the relation between the mind and the brain. The proposal is that events at the sub-neuronal, neuronal, and neuronal network levels take place simultaneously to perform a computation that can be described at a high level as a mental state, with content about the world. It is argued that as the processes at the different levels of explanation take place at the same time, they are linked by a non-causal supervenient relationship: (...) class='Hi'>causality can best be described in brains as operating within but not between levels. This mind-brain theory allows mental events to be different in kind from the mechanistic events that underlie them; but does not lead one to argue that mental events cause brain events, or vice versa: they are different levels of explanation of the operation of the computational system. Here, some implications are developed. It is proposed that causality, at least as it applies to the brain, should satisfy three conditions. First, interventionist tests for causality must be satisfied. Second, the causally related events should be at the same level of explanation. Third, a temporal order condition must be satisfied, with a suitable time scale in the order of 10 ms (to exclude application to quantum physics; and a cause cannot follow an effect). Next, although it may be useful for different purposes to describe causality involving the mind and brain at the mental level, or at the brain level, it is argued that the brain level may sometimes be more accurate, for sometimes causal accounts at the mental level may arise from confabulation by the mentalee, whereas understanding exactly what computations have occurred in the brain that result in a choice or action will provide the correct causal account for why a choice or action was made. Next, it is argued that possible cases of “downward causation” can be accounted for by a within-levels-of-explanation account of causality. This computational neuroscience approach provides an opportunity to proceed beyond Cartesian dualism and physical reductionism in considering the relations between the mind and the brain. (shrink)

The principle of 'information causality' can be used to derive an upper bound---known as the 'Tsirelson bound'---on the strength of quantum mechanical correlations, and has been conjectured to be a foundational principle of nature. In this paper, however, I argue that the principle has not to date been sufficiently motivated to play this role; the motivations that have so far been given are either unsatisfactorily vague or else amount to little more than an appeal to intuition. I then consider (...) how one might begin to successfully motivate the principle. I argue that a compelling way of so doing is to understand it as a generalisation of Einstein's principle of the mutually independent existence---the 'being-thus'---of spatially distant things, interpreted as a special methodological principle. More specifically: I describe an argument, due to Demopoulos, to the effect that the quantum-mechanical no-signalling condition can be viewed as a generalisation, appropriate to an irreducibly statistical theory such as quantum mechanics, of the Einsteinian principle. And I then argue that a compelling way to motivate information causality is to in turn consider it as a further generalisation of the Einsteinian principle that is appropriate to a theory of communication. I nevertheless describe important obstacles that must yet be overcome if the project of establishing information causality as a foundational principle of nature is to succeed. (shrink)

In recent decades, economists have developed methods for measuring the country-wide level of inequality of opportunity. The most popular method, called the ex-ante method, uses data on the distribution of outcomes stratified by groups of individuals with the same circumstances, in order to estimate the part of outcome inequality that is due to these circumstances. I argue that these methods are potentially biased, both upwards and downwards, and that the unknown size of this bias could be large. To argue that (...) the methods are biased, I show that they ought to measure causal or counterfactual quantities, while the methods are only capable of identifying correlational information. To argue that the bias is potentially large, I illustrate how the causal complexity of the real world leads to numerous non-causal correlations between circumstances and outcomes and respond to objections claiming that such correlations are nonetheless indicators of unfair disadvantage, that is, inequality of opportunity. (shrink)

Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative way. That is, mechanistic models are conceived of as representing how certain entities and activities are spatially and temporally organized so that they bring about the behavior of the mechanism in question. Although this adequately characterizes how mechanisms are represented in biology textbooks, contemporary biological research practice (...) shows the need for quantitative, probabilistic models of mechanisms, too. In this paper we argue that the formal framework of causal graph theory is well-suited to provide us with models of biological mechanisms that incorporate quantitative and probabilistic information. On the ba-sis of an example from contemporary biological practice, namely feedback regulation of fatty acid biosynthesis in Brassica napus, we show that causal graph theoretical models can account for feedback as well as for the multi-level character of mechanisms. However, we do not claim that causal graph theoretical representations of mechanisms are advantageous in all respects and should replace common qualitative models. Rather, we endorse the more balanced view that causal graph theoretical models of mechanisms are useful for some purposes, while being insufficient for others. (shrink)

It has often been noted that there is some tension between engaging in decision-making and believing that one’s choices might be predetermined. The possibility that our choices are predetermined forces us to consider, in our decisions, act-state pairs which are inconsistent, and hence to which we cannot assign sensible utilities. But the reasoning which justifies two-boxing in Newcomb’s problem also justifies associating a non-zero causal probability with these inconsistent act-state pairs. Put together these undefined utilities and non-zero probabilities entail that (...) expected utilities are undefined whenever it is a possibility that our choices are predetermined. There are three ways to solve the problem, but all of them suffer serious costs: always assume that, contrary to our evidence, the outcome of our present decision-making is not predetermined; give up the reasoning that justifies unconditional two-boxing in Newcomb’s problem; or allow epistemically impossible outcomes to contribute to expected utility, leading to the wrong results in a series of cases introduced by Ahmed :665–685, 2014a, Evidence, decision and causality, Cambridge University Press, Cambridge, 2014b). However they choose to respond, causal decision theorists cannot remain silent: the intuitive tension between decision-making and the possibility of predetermination can be made precise, and resolving it will require giving up something. Causal decision theorists have a predetermination problem. (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)

How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in multiple agent contexts. We draw on the structural model account of actual causation (e.g., Halpern & Pearl, 2005) and its extension to responsibility judgments (Chockler & Halpern, 2004). We review the main (...) theoretical and empirical issues that arise from this literature and propose a novel model of intuitive judgments of responsibility. This model is a function of both pivotality (whether an agent made a difference to the outcome) and criticality (how important the agent is perceived to be for the outcome, before any actions are taken). The model explains empirical results from previous studies and is supported by a new experiment that manipulates both pivotality and criticality. We also discuss possible extensions of this model to deal with a broader range of causal situations. Overall, our approach emphasizes the close interrelations between causality, counterfactuals, and responsibility attributions. (shrink)

This paper expounds that besides the well-known spatio-temporal problem there is a causal problem of entanglement: even when one neglects spatio-temporal constraints, the peculiar statistics of EPR/B experiment is inconsistent with usual principles of causal explanation as stated by the theory of causal Bayes nets. The conflict amounts to a dilemma that either there are uncaused correlations or there are caused independences . I argue that the central ideas of causal explanations can be saved if one accepts the latter horn (...) and explains the unfaithful independences by a stable fine-tuning of the causal parameters. (shrink)