The chapter explores whether, or to what extent, recent work in experimental philosophy puts pressure on the idea that the concept of causation is ‘egalitarian’. Causal selection – where experimental subjects tend to rate the causal strength of (for example) a norm-violator more strongly than a non-norm-violator – is a well established phenomenon, and is in prima facie tension with an egalitarian conception of causation; it also, indirectly, puts prima facie pressure on the idea that causation is (...) a worldly phenomenon whose obtaining is independent of facts about norms. The chapter explores both the various psychological mechanisms and the broadly pragmatic approaches to explaining causal selection. It argues that the answer to the question whether or not the concept of causation is egalitarian is currently significantly empirically underdetermined, and suggests some avenues for further investigation. (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)

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)

Causal selection has to do with a distinction between mere background conditions and the "true" causes of some outcome of interest. Mainstream philosophical views claim that causal selection is "groundless" in the sense that it lacks any type of principled rationale. I argue against this position in the context of biochemistry where causal factors are selected in explanations of metabolic processes. These factors are selected on the basis of a principled rationale, which is best understood (...) in terms of the causal control that they provide over an outcome of interest. (shrink)

In The Biopsychosocial Model of Health and Disease, Derek Bolton and Grant Gillett argue that a defensible updated version of the biopsychosocial model requires a metaphysically adequate account of disease causation that can accommodate biological, psychological, and social factors. This present paper offers a philosophical critique of their account of biopsychosocial causation. I argue that their account relies on claims about the normativity and the semantic content of biological information that are metaphysically contentious. Moreover, I suggest that these claims are (...) unnecessary for a defence of biopsychosocial causation, as the roles of multiple and diverse factors in disease causation can be readily accommodated by a more widely accepted and less metaphysically contentious account of causation. I then raise the more general concern that they are misdiagnosing the problem with the traditional version of the biopsychosocial model. The challenge when developing an explanatorily valuable version of the biopsychosocial model, I argue, is not so much providing an adequate account of biopsychosocial causation, but providing an adequate account of causal selection. Finally, I consider how this problem may be solved to arrive at a more explanatorily valuable and clinically useful version of the biopsychosocial model. (shrink)

Binding specificity is a centrally important concept in molecular biology, yet it has received little philosophical attention. Here I aim to remedy this by analyzing binding specificity as a causal property. I focus on the concept’s role in drug design, where it is highly prized and hence directly studied. From a causal perspective, understanding why binding specificity is a valuable property of drugs contributes to an understanding of causal selection—of how and why scientists distinguish between causes, (...) not just causes from noncauses. In particular, the specificity of drugs is precisely what underwrites their value as experimental interventions on biological processes. (shrink)

Causal selection is the cognitive process through which one or more elements in a complex causal structure are singled out as actual causes of a certain effect. In this paper, we report on an experiment in which we investigated the role of moral and temporal factors in causal selection. Our results are as follows. First, when presented with a temporal chain in which two human agents perform the same action one after the other, subjects tend (...) to judge the later agent to be the actual cause. Second, the impact of temporal location on causal selection is almost canceled out if the later agent did not violate a norm while the former did. We argue that this is due to the impact that judgments of norm violation have on causal selection—even if the violated norm has nothing to do with the obtaining effect. Third, moral judgments about the effect influence causal selection even in the case in which agents could not have foreseen the effect and did not intend to bring it about. We discuss our findings in connection to recent theories of the role of moral judgment in causal reasoning, on the one hand, and to probabilistic models of temporal location, on the other. (shrink)

Waters’s (2007) actual difference making and Weber’s (2013, 2017) biological normality approaches to causal selection have received many criticisms, some of which miss their target. Disagreement about whether Waters’s and Weber’s views succeed in providing criteria that uniquely singles out the gene as explanatorily significant in biology has led philosophers to overlook a prior problem. Before one can address whether Waters’s and Weber’s views successfully account for the explanatory significance of genes, one must ask whether either view satisfactorily (...) meets the necessary conditions for causal selection in the first place. An adequate defense of causal selection must meet two desiderata. First, there must be an explanatory property that sets some causes apart from others. Second, the property identified must be one that is recognized by biologists as relevant to their domain(s) of inquiry. I argue that both fall short of meeting the second condition. I demonstrate this by showing how many of the biological technologies crucial to experimentation do not fit either view very well. I offer a more adequate proposal that accommodates non-actual and artificial causal variables. A consequence of my view is the following: When analyzing the causal selection practices of biologists, philosophers should consider the explanatory targets relevant to a research program – including ones whose explanans must appeal to biological technologies. I then explain how this proposal can inform the existing debate between Weber (2017) and Griffiths et al. (2015). (shrink)

Among the many causes of an event, how do we distinguish the important ones? Are there ways to distinguish among causes on principled grounds that integrate both practical aims and objective knowledge? Psychologist Tania Lombrozo has suggested that causal explanations “identify factors that are ‘exportable’ in the sense that they are likely to subserve future prediction and intervention” (Lombrozo 2010, 327). Hence portable causes are more important precisely because they provide objective information to prediction and intervention as practical aims. (...) However, I argue that this is only part of the epistemology of causal selection. Recent work on portable causes has implicitly assumed them to be portable within the same causal system at a later time. As a result, it has appeared that the objective content of causal selection includes only facts about the causal structure of that single system. In contrast, I present a case study from systems biology in which scientists are searching for causal factors that are portable across rather than within causal systems. By paying careful attention to how these biologists find portable causes, I show that the objective content of causal selection can extend beyond the immediate systems of interest. In particular, knowledge of the evolutionary history of gene networks is necessary for correctly identifying causal patterns in these networks that explain cellular behavior in a portable way. (shrink)

Disasters in sociotechnical systems are caused by many factors. For example, the tragic chemical disaster in Bhopal, India, was caused by a leaky valve and a maintenance error. Safety scientists and investigators call these proximate factors. But the tragedy was also caused by what experts call systemic factors, which include the facility’s design, the organization of its workforce, and the safety culture of the plant and surrounding community. Other disasters share a similarly complex causality, depending on a multitude of proximate (...) and systemic factors. Investigators and scientists distinguish between these different types of factors because they think each has distinctive causal features and also because they often think some factors are more significant causes of disasters than others. In this dissertation, I analyze these distinctions and the reasoning experts use when selecting important causes of disasters in cases like the Bhopal gas tragedy and the Challenger shuttle loss. Using James Woodward’s interventionist theory of causation, I explicate three causal concepts that can be used to distinguish among causal factors: amplifying/damping, causal inertia, and causal delay. I employ these concepts to elaborate and clarify the causal features safety scientists identify to draw distinctions among different types of causal factors, and their reasons for thinking some causes are more important than others for understanding disasters. My dissertation takes a pragmatic approach to causal selection. Although philosophers have emphasized John Stuart Mill’s remark that selecting individual causal factors is “capricious,” I base my approach on Mill’s deeper thinking about the logic of causal selection and the philosophical challenge it poses. I show that selections of causal factors in investigations of disasters and the surrounding discussions of safety are motivated primarily by the dual aim of preventing future disasters and making systems safer. Considering these purposes is essential to understand why investigators single out causes with certain features. Analyzing causal selection in terms of why certain types of causes with certain kinds of features are more useful than others for particular purposes clarifies vital reasoning about the important causes of disasters and enriches our understanding of causal knowledge. (shrink)

Causal selection has to do with the distinction we make between background conditions and “the” true cause or causes of some outcome of interest. A longstanding consensus in philosophy views causal selection as lacking any objective rationale and as guided, instead, by arbitrary, pragmatic, and non-scientific considerations. I argue against this position in the context of causal selection for disease traits. In this domain, causes are selected on the basis of the type of (...) class='Hi'>causal control they exhibit over a disease of interest. My analysis clarifies the principled rationale that guides this selection and how it involves both pragmatic and objective considerations, which have been overlooked in the extant literature. (shrink)

Despite the promise to boost human potential and wellbeing, enhancement drugs face recurring ethical scrutiny. The present studies examined attitudes toward cognitive enhancement in order to learn more about these ethical concerns, who has them, and the circumstances in which they arise. Fairness-based concerns underlay opposition to competitive use—even though enhancement drugs were described as legal, accessible and affordable. Moral values also influenced how subsequent rewards were causally explained: Opposition to competitive use reduced the causal contribution of the enhanced (...) winner’s skill, particularly among fairness-minded individuals. In a follow-up study, we asked: Would the normalization of enhancement practices alleviate concerns about their unfairness? Indeed, proliferation of competitive cognitive enhancement eradicated fairness-based concerns, and boosted the perceived causal role of the winner’s skill. In contrast, purity-based concerns emerged in both recreational and competitive contexts, and were not assuaged by normalization. (shrink)

Causal judgments are widely known to be sensitive to violations of both prescriptive norms (e.g., immoral events) and statistical norms (e.g., improbable events). There is ongoing discussion as to whether both effects are best explained in a unified way through changes in the relevance of counterfactual possibilities, or whether these two effects arise from unrelated cognitive mechanisms. Recent work has shown that moral norm violations affect causal judgments of agents, but not inanimate artifacts used by those agents. These (...) results have been interpreted as showing that prescriptive norm violations only affect causal reasoning about intentional agents, but not the use of inanimate artifacts, thereby providing evidence that the effect of prescriptive norm violations arises from mechanisms specific to reasoning about intentional agents, and thus casting doubt on a unified counterfactual analysis of causal reasoning. Four experiments explore this recent finding and provide clear support for a unified counterfactual analysis. Experiment 1 demonstrates that these newly observed patterns in causal judgments are closely mirrored by judgments of counterfactual relevance. Experiment 2 shows that the relationship between causal and counterfactual judgments is moderated by causal structure, as uniquely predicted by counterfactual accounts. Experiment 3 directly manipulates the relevance of counterfactual alternatives and finds that causal judgments of intentional agents and inanimate artifacts are similarly affected. Finally, Experiment 4 shows that prescriptive norm violations (in which artifacts malfunction) affect causal judgments of inanimate artifacts in much the same way that prescriptive norm violations (in which agents act immorally) affect causal judgments of intentional agents. (shrink)

Despite the voluminous literature on biological functions produced over the last 40 years, few philosophers have studied the concept of function as it is used in neuroscience. Recently, Craver (forthcoming; also see Craver 2001) defended the causal role theory against the selected effects theory as the most appropriate theory of function for neuroscience. The following argues that though neuroscientists do study causal role functions, the scope of that theory is not as universal as claimed. Despite the strong prima (...) facie superiority of the causal role theory, the selected effects theory (when properly developed) can handle many cases from neuroscience with equal facility. It argues this by presenting a new theory of function that generalizes the notion of a ‘selection process’ to include processes such as neural selection, antibody selection, and some forms of learning—that is, to include structures that have been differentially retained as well as those that have been differentially reproduced. This view, called the generalized selected effects theory of function, will be defended from criticism and distinguished from similar views in the literature. (shrink)

In their book What Darwin Got Wrong, Jerry Fodor and Massimo Piattelli-Palmarini construct an a priori philosophical argument and an empirical biological argument. The biological argument aims to show that natural selection is much less important in the evolutionary process than many biologists maintain. The a priori argument begins with the claim that there cannot be selection for one but not the other of two traits that are perfectly correlated in a population; it concludes that there cannot be (...) an evolutionary theory of adaptation. This article focuses mainly on the a priori argument. (shrink)

Recent discussions in the philosophy of biology have brought into question some fundamental assumptions regarding evolutionary processes, natural selection in particular. Some authors argue that natural selection is nothing but a population-level, statistical consequence of lower-level events (Matthen and Ariew [2002]; Walsh et al. [2002]). On this view, natural selection itself does not involve forces. Other authors reject this purely statistical, population-level account for an individual-level, causal account of natural selection (Bouchard and Rosenberg [2004]). I (...) argue that each of these positions is right in one way, but wrong in another; natural selection indeed takes place at the level of populations, but it is a causal process nonetheless. (shrink)

Recent arguments concerning the nature of causation in evolutionary theory, now often known as the debate between the 'causalist' and 'statisticalist' positions, have involved answers to a variety of independent questions – definitions of key evolutionary concepts like natural selection, fitness, and genetic drift; causation in multi-level systems; or the nature of evolutionary explanations, among others. This Element offers a way to disentangle one set of these questions surrounding the causal structure of natural selection. Doing so allows (...) us to clearly reconstruct the approach that some of these major competing interpretations of evolutionary theory have to this causal structure, highlighting particular features of philosophical interest within each. Further, those features concern problems not exclusive to the philosophy of biology. Connections between them and, in two case studies, contemporary metaphysics and philosophy of physics demonstrate the potential value of broader collaboration in the understanding of evolution. (shrink)

In the recent philosophical literature, two questions have arisen concerning the status of natural selection: (1) Is it a population-level phenomenon, or is it an organism-level phenomenon? (2) Is it a causal process, or is it a purely statistical summary of lower-level processes? In an earlier work (Millstein, Br J Philos Sci, 57(4):627–653, 2006), I argue that natural selection should be understood as a population-level causal process, rather than a purely statistical population-level summation of lower-level processes (...) or as an organism-level causal process. In a 2009 essay entitled “Productivity, relevance, and natural selection,” Stuart Glennan argues in reply that natural selection is produced by causal pro- cesses operating at the level of individual organisms, but he maintains that there is no causal productivity at the population level. However, there are, he claims, many population-level properties that are causally relevant to the dynamics of evolution- ary processes. Glennan’s claims rely on a causal pluralism that holds that there are two types of causes: causal production and causal relevance. Without calling into question Glennan’s causal pluralism or his claims concerning the causal relevance of natural selection, I argue that natural selection does in fact exhibit causal production at the population level. It is true that natural selection does not fit with accounts of mechanisms that involve decomposition of wholes into parts, such as Glennan’s own. However, it does fit with causal production accounts that do not require decomposition, such as Salmon’s Mark Transmission account, given the extent to which populations act as interacting “objects” in the process of natural selection. (shrink)

It is an ongoing controversy whether natural selection is a cause of population change, or a mere statistical description of how individual births and deaths accumulate. In this paper I restate the problem in terms of the reference class problem, and propose how the structure of stable equilibrium can provide a solution in continuity with biological practice. Insofar natural selection can be understood as a tendency towards equilibrium, key statisticalist criticisms are avoided. Further, in a modification of the (...) Newtonian-force analogy, it can be suggested that a better metaphor for natural selection is that of an emergent force, similar in nature to entropic forces: with magnitude and direction, but lacking a spatiotemporal origin or point of application. (shrink)

Whenever the use of non-experimental data for discovering causal relations or predicting the outcomes of experiments or interventions is contemplated, two difficulties are routinely faced. One is the problem of latent variables, or confounders: factors influencing two or more measured variables may not themselves have been measured or recorded. The other is the problem of sample selection bias: values of the variables or features under study may themselves influence whether a unit is included in the data sample.

Economists reason causally. Like many other scientists, they aim at formulating justified causal claims about their object of study. This thesis contributes to our understanding of how causal reasoning proceeds in economics. By using the research on the causes of unemployment as a case study, three questions are adressed. What are the meanings of causal claims? How can a causal claim be adequately supported by evidence? How are causal beliefs affected by incoming facts? In the (...) process of answering these semantic, epistemic and dynamical questions, the richness of causal reasoning in economics is brought to the foreground. In the part on semantics, it is argued that the meaning of causal generalizations in policy-oriented economics is best captured by using the concept of ‘inferential relation’ rather than the one of ‘referential relation’. This part contributes to develop an inferentialist semantics by distinguishing among types of inferential relations. In the part on epistemology, it is argued that justification in sciences like economics often relies, and ought to rely, on evidential variety―i.e. the combination of evidence from multiple sources. An interpretation of independence among evidential sources is offered: two evidential sources are fully independent if and only if the reasons why they would be unreliable do not overlap. It is then shown that the variety-of-evidence thesis does not hold under extreme circumstances. The part on dynamics focuses on deviant-case study. A storyline is provided for what deviant-case study aims at and how it proceeds in what is characterized as an ‘eclectic science’. (shrink)

Hull et al. make a direct connection between selection and replication. My view is that selection, at its causal crux, is not inherently connected to replication. I make plain the causal crux of selection, distinguishing it from replication. I discuss implications of my results for Hull et al.'s critique of Darden and Cain (1989).

It is observed that in ordinary everyday causal explanations often just one causal factor is mentioned. One causal factor carries the explanatory burden, even if there are several causal factors that are responsible for the event to be explained. This paper deals with the question of how to account for this explanatory selection. I argue for a pragmatic stance towards explanation, that we must attend to the question–answer situation as a whole and the context of (...) the explanation. The context of an explanation includes the inquirer's and the explainer's beliefs and presuppositions relevant for the explanation-seeking question, and these are encoded in a reference class. Furthermore I argue that the explanation-giving answer contains an implicit counterfactual claim, the explanation-giving counterfactual. The solution to the problem of explanatory selection is to be found in the presuppositions encoded by the reference class and the eg-counterfactual. In short we select as explanatory that factor which, together with the presupposition encoded in the reference class we believe will make the eg-counterfactual true. (shrink)

The integrodifferential equations satisfied by the statistical frequency functions for physical systems undergoing stochastic transitions are derived by application of a causality principle and selection rules to the Markov chain equations. The result equations can be viewed as generalizations of the diffusion equation, but, unlike the latter, they have a direct bearing onactive transport problems in biophysics andcondensation aggregation problems of astrophysics and phase transition theory. Simple specific examples of the effects of severe selection rules, such as the (...) relaxational Boltzmann transport equation and the diffusion equation, are also given. Finally, partial differential equations for the probability amplitudes of quantum mechanics are derived, usingunitarity instead of causality, and a selection rule is applied directly to obtain ageneralization of the Dirac equation in which infinite transitions between states arenot allowed. (shrink)

The theory of evolution is supported by the theory of genetics, which provides a single causal mechanism to explain the activities of replicators and interactors. A common misrepresentation of the theory of evolution, however, is that interaction (involving interactors), and transmission (involving replicators), are distinct causal processes. Sandra Mitchell (1987) is misled by this. I discuss why only a single causal mechanism is working in evolution and why it is sufficient. Further, I argue that Mitchell's mistaken view (...) of the causal mechanism in evolution prevents her from resolving the conflict between Dawkins and Brandon. I conclude that the unit-of-selection question remains very much alive. (shrink)

We develop an account of laboratory models, which have been central to the group selection controversy. We compare arguments for group selection in nature with Darwin's arguments for natural selection to argue that laboratory models provide important grounds for causal claims about selection. Biologists get information about causes and cause-effect relationships in the laboratory because of the special role their own causal agency plays there. They can also get information about patterns of effects and (...) antecedent conditions in nature. But to argue that some cause is actually responsible in nature, they require an inference from knowledge of causes in the laboratory context and of effects in the natural context. This process, cause detection, forms the core of an analogical argument for group selection. We discuss the differing roles of mathematical and laboratory models in constructing selective explanations at the group level and apply our discussion to the units of selection controversy to distinguish between the related problems of cause determination and evaluation of evidence. Because laboratory models are at the intersection of the two problems, their study is crucial for framing a coherent theory of explanation for evolutionary biology. (shrink)

To evaluate Hume's thesis that causal claims are always empirical, I consider three kinds of causal statement: ?e1 caused e2 ?, ?e1 promoted e2 ?, and ?e1 would promote e2 ?. Restricting my attention to cases in which ?e1 occurred? and ?e2 occurred? are both empirical, I argue that Hume was right about the first two, but wrong about the third. Standard causal models of natural selection that have this third form are a priori mathematical truths. (...) Some are obvious, others less so. Empirical work on natural selection takes the form of defending causal claims of the first two types. I provide biological examples that illustrate differences among these three kinds of causal claim. (shrink)

I discuss two subjects in Samir Okasha’s excellent book, Evolution and the Levels of Selection. In consonance with Okasha’s critique of the conventionalist view of the units of selection problem, I argue that conventionalists have not attended to what realists mean by group, individual, and genic selection. In connection with Okasha’s discussion of the Price equation and contextual analysis, I discuss whether the existence of these two quantitative frameworks is a challenge to realism.

This article argues that at least very many judgments of homology rest on prior attributions of selected‐effect (SE) function, and that many of the “parts” of biological systems that are rightly classified as homologous are constituted by (are so classified in virtue of) their consequence etiologies. We claim that SE functions are often used in the prior identification of the parts deemed to be homologous and are often used to differentiate more restricted homologous kinds within less restricted ones. In doing (...) so, we discuss recent criticism of this view that has been offered (especially that offered by Paul Griffiths). *Received July 2007; revised November 2008. †To contact the authors, please write to: Department of Philosophy, 201 West Duke Building, Box 90743, Durham, NC 27708; e‐mail: [email protected] or [email protected]. (shrink)

Genic selectionism holds that all selection can be understood as operating on particular genes. Critics (and conventional biological wisdom) insist that this misrepresents the actual causal structure of selective phenomena at higher levels of biological organization, but cannot convincingly defend this intuition. I argue that the real failing of genic selectionism is pragmatic – it prevents us from adopting the most efficient corpus of causal laws for predicting and intervening in the course of affairs – and I (...) offer a Pragmatic account of causation itself which ultimately bears out the claim that genic selectionism misrepresents the causal structure of selective contexts. (shrink)

The statistical evidence for the detrimental effect of exposure to low levels of lead on the cognitive capacities of children has been debated for several decades. In this paper I describe how two techniques from artificial intelligence and statistics help make the statistical evidence for the accepted epidemiological conclusion seem decisive. The first is a variable-selection routine in TETRAD III for finding causes, and the second a Bayesian estimation of the parameter reflecting the causal influence of Actual Lead (...) Exposure, a latent variable, on the measured IQ score of middle class suburban children. (shrink)

Proceedings of the Pittsburgh Workshop in History and Philosophy of Biology, Center for Philosophy of Science, University of Pittsburgh, March 23-24 2001 Session 3: Natural Selection as a Causal Theory.

Kin selection and multilevel selection are alternative approaches for studying the evolution of social behaviour, the relation between which has long been a source of controversy. Many recent theorists regard the two approaches as ultimately equivalent, on the grounds that gene frequency change can be correctly expressed using either. However, this shows only that the two are formally equivalent, not that they offer equally good causal representations of the evolutionary process. This article articulates the notion of an (...) ‘adequate causal representation’ using causal graphs, and then seeks to identify circumstances under which kin and multilevel selection do and do not satisfy the test of causal adequacy. 1 Introduction2 The KS and MLS Approaches2.1 The MLS decomposition2.2 The KS decomposition3 Equivalence and Causality4 Two Problem Cases4.1 The non-social trait case4.2 Genotypic selection with meiotic drive5 Casual Adequacy: A Graphical Approach5.1 The basic idea5.2 Graphs with individual and group variables5.3 Cases where KS is causally adequate5.4 Cases where MLS is causally adequate6 Discussion6.1 Relation to previous work. (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)

Causal discovery becomes especially challenging when the possibility of latent confounding and/or selection bias is not assumed away. For this task, ancestral graph models are particularly useful in that they can represent the presence of latent confounding and selection effect, without explicitly invoking unobserved variables. Based on the machinery of ancestral graphs, there is a provably sound causal discovery algorithm, known as the FCI algorithm, that allows the possibility of latent confounders and selection bias. However, (...) the orientation rules used in the algorithm are not complete. In this paper, we provide additional orientation rules, augmented by which the FCI algorithm is shown to be complete, in the sense that it can, under standard assumptions, discover all aspects of the causal structure that are uniquely determined by facts of probabilistic dependence and independence. The result is useful for developing any causal discovery and reasoning system based on ancestral graph models. (shrink)

Research in evolutionary biology and philosophy of biology and cognition strongly suggests that human organisms modify their environment through active processes of niche construction. Recently, proponents of the free-energy principle and variational active inference have argued that their approach can deepen our understanding of the reciprocal causal relationship between organisms and their niche on various scales. This paper examines the feasibility and scope of variational formalisations and conceptualisations of the organism-niche nexus with a particular focus on the extended active (...) inference account. I will draw a conceptual distinction between selective niche construction, developmental niche construction, and organism-niche coordination dynamics and argue that these notions capture different causal patterns, each of which with a distinct scope. Against this background, I will analyse and discuss the extended active inference account and its strategy to integrate variational active inference with work on extended cognition. The proponents of extended active inference assume that their account can provide an explanation of selective niche construction, developmental niche construction, and organism-niche coordination dynamics. However, my key claim will be that this account has the potential to elucidate the workings of organism-niche coordination dynamics, but does not adequately capture the causal patterns of selective niche construction and developmental niche construction. (shrink)

The evolution of the human mind through natural selection mandates that our conscious experiences are causally potent in order to leave a tangible impact upon the surrounding physical world. Any attempt to construct a functional theory of the conscious mind within the framework of classical physics, however, inevitably leads to causally impotent conscious experiences in direct contradiction to evolution theory. Here, we derive several rigorous theorems that identify the origin of the latter impasse in the mathematical properties of ordinary (...) differential equations employed in combination with the alleged functional production of the mind by the brain. Then, we demonstrate that a mind--brain theory consistent with causally potent conscious experiences is provided by modern quantum physics, in which the unobservable conscious mind is reductively identified with the quantum state of the brain and the observable brain is constructed by the physical measurement of quantum brain observables. The resulting quantum stochastic dynamics obtained from sequential quantum measurements of the brain is governed by stochastic differential equations, which permit genuine free will exercised through sequential conscious choices of future courses of action. Thus, quantum reductionism provides a solid theoretical foundation for the causal potency of consciousness, free will and cultural transmission. (shrink)

Sober 2011 argues that, contrary to Hume, some causal statements can be known a priori to be true—notably, some ‘would promote’ statements figuring in causal models of natural selection. We find Sober's argument unconvincing. We regard the Humean thesis as denying that causal explanations contain any a priori knowable statements specifying certain features of events to be causally relevant. We argue that not every ‘would promote’ statement is genuinely causal, and we suggest that Sober has (...) not shown that his examples of ‘would promote’ statements manage to achieve a priori status without sacrificing their causal character. (shrink)

Cognitive Science, Volume 46, Issue 2, February 2022.

Causal selection and priority are at the heart of discussions of the causal parity thesis, which says that all causes of a given effect are on a par, and that any justified priority assigned to a given cause results from causal explanatory interests. In theories of causation that provide necessary and sufficient conditions for the truth of causal claims, status as cause is an either/or issue: either a given cause satisfies the conditions or it does (...) not. Consequently, assessments of causal parity and priority require more resources, which can either be additional or part of the causal analysis itself. While adding resources in terms of a theory of causal explanation has been standard, here we develop a unified conceptual analysis that includes a range of different precise causal concepts that allows for assessments of causal priority in terms of different kinds of causal relevance. (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)