Contemporary philosophical debates about causation are dominated by two approaches, which are often referred to as difference-making and causal process approaches to causation, respectively. I provide a characterization of the dialectic between these two approaches, on which that dialectic turns crucially on the question as to whether our common sense concept of causation involves a commitment to locality – i.e., to the claim that causal relations are always subject to spatial constraints. I then argue that we can extract (...) from existing work on perceptual judgement (specifically work that invokes the notion of a simple theory of perception) materials for an argument in favour of a positive answer to that question, and that this work can also help to bring out a distinctive kind of role that a commitment to locality plays in our reasoning about causal relationships. (shrink)

This article provides a conceptual account of causal understanding by connecting current psychological research on time and causality with philosophical debates on the causal asymmetry. I argue that causal relations are viewed as asymmetric because they are understood in temporal terms. I investigate evidence from causal learning and reasoning in both children and adults: causal perception, the temporal priority principle, and the use of temporal cues for causal inference. While this account does not (...) suffice for correct inferences of causal structure, I show it to serve as a preliminary understanding of causal concepts as asymmetric, that later incorporates other types of evidence. This approach supplies causal models with an asymmetric concept of causation that underlies hypotheses about causal structure, as I will illustrate from the framework of the knowledge-based causal induction model. I further argue for an integrating perspective, showing how the understanding of causes as preceding their effects underlies both psychological models and philosophical debates over time and the causal asymmetry, particularly regarding problem cases such as simultaneous causation or backwards causation, and the conceptual connection between causation and action. (shrink)

Karl Pearson is the leading figure of XX century statistics. He and his co-workers crafted the core of the theory, methods and language of frequentist or classical statistics – the prevalent inductive logic of contemporary science. However, before working in statistics, K. Pearson had other interests in life, namely, in this order, philosophy, physics, and biological heredity. Key concepts of his philosophical and epistemological system of anti-Spinozism (a form of transcendental idealism) are carried over to his subsequent works on the (...) logic of scientific discovery. This article’s main goal is to analyze K. Pearson early philosophical and theological ideas and to investigate how the same ideas came to influence contemporary science, either directly or indirectly – by the use of variant theories, methods and dialects of statistics, corresponding to variant statistical inference procedures and their specific belief calculi. (shrink)

Comments presented at the 35th International Seminar on the -- New Institutional Economics -- Empirical Methods for the Law; Syracuse, 2018.

This paper argues that the ubiquitous digital networks in which we are increasingly becoming immersed present a threat to our ability to exercise free will. Using process philosophy, and expanding upon understandings of causal autonomy, the paper outlines a thematic analysis of diary studies and interviews gathered in a project exploring the nature of digital experience. It concludes that without mindfulness in both the use and design of digital devices and services we run the risk of allowing such services (...) to direct our daily lives in ways over which we are increasingly losing control. (shrink)

An influential philosophical conception of our mind’s place in the world is as a site for the states and events that causally mediate the world we perceive and the world we affect. According to this conception, states and events in the world cause mental states and events in us through the process of perception. These mental states and events then go on to produce new states and events in the world through the process of action. Our role is as hosts (...) for these states and events that causally mediate the states and events on the input side and those on the output side. (shrink)

Causal understanding is a defining characteristic of human cognition. Like many animals, human children learn to control their bodily movements and act effectively in the environment. Like a smaller subset of animals, children intervene: they learn to change the environment in targeted ways. Unlike other animals, children grow into adults with the causal reasoning skills to develop abstract theories, invent sophisticated technologies and imagine alternate pasts, distant futures and fictional worlds. In this Review, we explore the development (...) of human-unique causal learning and reasoning from evolutionary and ontogenetic perspectives. We frame our discussion using an ‘interventionist’ approach. First, we situate causal understanding in relation to cognitive abilities shared with non-human animals. We argue that human causal understanding is distinguished by its depersonalized (objective) and decontextualized (general) representations. Using this framework, we next review empirical findings on early human causal learning and reasoning and consider the naturalistic contexts that support its development. Then we explore connections to related abilities. We conclude with suggestions for ongoing collaboration between developmental, cross-cultural, computational, neural and evolutionary approaches to causal understanding. (shrink)

We blame faulty brakes for a car crash, or rain for our bad mood. This “merely causal” blame is usually seen as uninteresting. I argue that it is crucial for understanding the interpersonal blame with which we target ourselves and each other. The two are often difficult to distinguish, in a way that plagues philosophical discussions of blame. And interpersonal blame is distinctive, I argue, partly in its causal focus: its attention to a person as cause. I (...) argue that this causal focus helps explain several central characteristics of interpersonal blame: its tendency to exaggerate a person’s causal role, its weakening through attention to personal history or thoughts about determinism, its characteristic ‘force’ or ‘sting’, and our sense that blame is often harmful or unfair. I conclude by drawing out one implication of blame's causal focus: in a certain range of cases, blame is partly under our voluntary control. (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)

The paper considers three questions. First, what is the connection between economics and agency? It is argued that causation and explanation in economics fundamentally depend on agency. So a philosophical understanding of economic explanation must be sensitive to an understanding of agency. Second, what is the connection between agency and causation? A causal view of agency-involving explanation is defended against a number of arguments from the resurgent noncausalist tradition in the literature on agency and action-explanation. If agency (...) is fundamental to economic explanation, it is argued, then so is causation. Third, what is the connection between causal explanation and the natural sciences? It is argued that, though the explanations given in economics and other social sciences are causal explanations, they are different in kind from the causal explanations of the natural sciences. On the one hand, then, the causal explanations of the social sciences are irreducible to those found in the natural sciences. On the other hand, the causal relations described by the social sciences are not completely autonomous; they do not float free of, or operate independently from, the causal relations charted by the natural sciences. (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)

This chapter begins with a discussion of the significance of studies of aspects of tool use in understanding causal cognition. It argues that tool use studies reveal the most basic type or causal understanding being put to use, in a way that studies that focus on learning statistical relationships between cause and effect or studies of perceptual causation do not. An overview of the subsequent chapters is also presented.

In this chapter, we outline the range of argument forms involving causation that can be found in everyday discourse. We also survey empirical work concerned with the generation and evaluation of such arguments. This survey makes clear that there is presently no unified body of research concerned with causal argument. We highlight the benefits of a unified treatment both for those interested in causal cognition and those interested in argumentation, and identify the key challenges that must be met (...) for a full understanding of causal argumentation. (shrink)

What are the roles of scientific causal knowledge in relation to the evidential requirements of policy making? In this chapter, I review the existing approaches in philosophy of science to the policy relevance of causal knowledge. I assess the specific concerns and questions on which these philosophical accounts have focused and show how they only offer a partial perspective of the relation between causal knowledge and policy making. Most existing views are top-down approaches: they start from philosophical (...) concerns about causation and evidence, and then make general claims about (potential) policy implications, but leave the notion of “policy” unanalyzed. As an alternative, I put forward some ideas toward a bottom-up approach: one that understands policy making as a dynamic process with several stages, and that starts from concrete policy problems, to then examine how causal notions and methods can contribute in various ways to the specifics of the process of policy making. (shrink)

A promising development in the philosophy of causation analyzes actual causation using structural equation models, i.e., “causal models”. This paper carefully considers what it means for an interpreted model to be accurate of its target situation. These considerations show, first, that our existing understanding of accuracy is inadequate. Further, and more controversially, they show that any causal model analysis is committed to a kind of relativism – a view whereby causation is a three-part relation holding between a (...) cause, an effect, and something else. In particular, insofar as a causal model analysis construes causation mind-and-language independently, it must treat causation as relative to a specification of background possibilities – i.e., a ‘modal profile.’ Or, so I argue. (shrink)

This paper discusses von Wright's theory of causation from Explanation and Understanding and Causality and Determinism in contemporary context. I argue that there are two important common points that von Wright's view shares with the version of manipulability currently supported by Woodward: the analysis of causal relations in a system modelled on controlled experiments, and the explanation of manipulability through counterfactuals - with focus on the counterfactual account of unmanipulable causes. These points also mark von Wright's departure from (...) previous action-based theories of causation. Owing to these two features, I argue that, upon classifying different versions of manipulability theories, von Wright's view should be placed closer to the interventionist approach than to the agency theory, where it currently stands. Furthermore, given its relevance in contemporary context, which this paper aims to establish, I claim that von Wright's theory can be employed to solve present problems connected to manipulability approaches to causation. (shrink)

ABSTRACT There is a disagreement over how to understand Nietzsche's view of science. According to what I call the Negative View, Nietzsche thinks science should be reconceived or superseded by another discourse, such as art, because it is nihilistic. By contrast, what I call the Positive View holds that Nietzsche does not think science is nihilistic, so he denies that it should be reinterpreted or overcome. Interestingly, defenders of each position can appeal to Nietzsche's understanding of naturalism to support (...) their interpretation. I argue that Nietzsche embraces a social constructivist conception of causality that renders his naturalism incompatible with the views of naturalism attributed to him by the two dominant readings. (shrink)

Bertrand Russell once pointed out that modern science doesn’t deal with causal laws and that assuming otherwise is not only wrong but such thinking is erroneously thought to do no harm. However, looking into the scientific practice of simulation or experimentation reveals a general causal comprehension of physical processes. In this paper I trace causal experiences to the existence of innate causal capacity by which we organize sensory information. This capacity, I argue, is something we have (...) got in virtue of natural selection as can be seen from experiments with intelligent animals like crows and chimpanzees. So understanding the empirical world is impossible without the use of causal categories. The reason why Russell believed that modern science does not refer to causal laws is, I think, because he argued that the laws of mathematical physics give us a non-causal description of reality. In contrast to such a claim I hold that theoretical laws are prescriptive rules of description rather than descriptions themselves. (shrink)

Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal knowledge (...) is necessary for the project, both as a source for handling complexity and as an output for meeting the project’s goals. Consequently, I argue that data-driven claims about causality are fundamentally flawed and causal knowledge should be considered a necessary aspect of Big Data science. In addition, I present the consequences of this result on other data-driven claims, concerning the role of theoretical considerations. I argue that the importance of causal knowledge and other kinds of theoretical engagement in EXPOsOMICS undermine theory-free accounts and suggest alternative ways of framing science based on Big Data. (shrink)

For many philosophers, the relation of medicine to health is exemplary for understanding the relation of human power to nature in general. Drawing on Heidegger and Aquinas, this paper examines the relation of art to nature as it emerges in the second book of Aristotle’s Physics, and it does so by articulating the duality of efficient causality. The art of medicine operates as a dispositive cause rather than as a perfective cause; it removes obstacles to the achievement of health, (...) but it does not impose health. Medicine, on this conception, aids the efficient causality of the natural body rather than substituting for it. The loss of dispositive causality makes efficient causality an imposition of force that bypasses the natural power to achieve natural goods. The paper concludes, with Plato, by arguing that dispositive causality offers a way to understand not only medicine but also governing, teaching, and parenting. (shrink)

Spinoza's causal axiom is at the foundation of the Ethics. I motivate, develop and defend a new interpretation that I call the ‘causally restricted interpretation’. This interpretation solves several longstanding puzzles and helps us better understand Spinoza's arguments for some of his most famous doctrines, including his parallelism doctrine and his theory of sense perception. It also undermines a widespread view about the relationship between the three fundamental, undefined notions in Spinoza's metaphysics: causation, conception and inherence.

The thesis explores and suggests a solution to a problem that I identify in John McDowell’s and Lynne Rudder Baker’s approaches to mental and intention-dependent (ID) causation in the physical world. I begin (chapter 1) with a brief discussion of McDowell’s non-reductive and anti-scientistic account of mind and world, which I believe offers, through its vision of the unbounded conceptual and the world as within the space of reasons, to liberate and renew philosophy. However, I find an inconsistency in McDowell’s (...) criticism of Davidson’s anomalous monism (chapter 2), stemming from a tension between McDowell’s naïve common sense view of mental causation and an understanding of ordinary physical causation which I think McDowell ought to embrace, which portrays it as both objective, in the sense of being recognition- independent, and as belonging within the space of reasons. The question of the relation between these two concepts of causation is an aspect of the more general question of the relation between the space of reasons and the realm of law. In chapter 3 I begin examining the possibility that Baker’s account of material and property constitution could form the basis of a bridge between the two spaces, and find it generally promising. However, I find that her defence of her version of non-reductive monism against Kim’s causal arguments also runs into problems, which I attribute to the fact that she holds a view of causation as secondary to causal explanation. 2 3 In chapter 4 I develop an account of what I call manifest physical causation – of objective causal relations in the world of Sellars’s manifest image. Based upon McDowell’s transcendental empiricism, which takes the existence of the ordinary perceived world as a condition of the possibility of our possession of conceptual capacities, I contend that it is this picture of reality, rather than that of fundamental physics, that should be the starting point of our theorizing. Causation in the manifest image, I argue, covers the behaviour of the familiar physical world as well as that of its well-understood extensions into the special sciences and engineering. Manifest physical causation, on my account, is productive, acts through mechanisms which are almost entirely mechanical, electromagnetic, and/ or chemical, and is causally closed. In my view, normative, semantic, contentful property-instances are not part of the manifest physical causal nexus. In my final chapter I suggest a modification of Baker’s constitution account, which I call Constituted Causation, whereby higher-level – mental and other ID – causal relations are constituted, in favourable circumstances, by lower-level ones. ID causal relations belong in their own causal nexus but are connected to the manifest physical world through constitution, a relation of unity without identity. Causation and constitution are, respectively, intra- and inter-level relations, and they are non-overlapping. The constituted network of rational and normative relations bears, I believe, striking parallels with McDowell’s view of reality. According to Baker’s view of constitution, the essential properties of constituted entities subsume those of their constituters; extending this to my account enables us to say that the real cause and explanation of someone’s action is that they consciously performed it 4 rather than that certain manifest causal processes occurred at the lower level. (shrink)

How are causal judgements such as 'The ice on the road caused the traffic accident' connected with counterfactual judgements such as 'If there had not been any ice on the road, the traffic accident would not have happened'? This volume throws new light on this question by uniting, for the first time, psychological and philosophical approaches to causation and counterfactuals. Traditionally, philosophers have primarily been interested in connections between causal and counterfactual claims on the level of meaning or (...) truth-conditions. More recently, however, they have also increasingly turned their attention to psychological connections between causal and counterfactual understanding or reasoning. At the same time, there has been a surge in interest in empirical work on causal and counterfactual cognition amongst developmental, cognitive, and social psychologists--much of it inspired by work in philosophy. In this volume, twelve original contributions from leading philosophers and psychologists explore in detail what bearing empirical findings might have on philosophical concerns about counterfactuals and causation, and how, in turn, work in philosophy might help clarify the issues at stake in empirical work on the cognitive underpinnings of, and relationships between, causal and counterfactual thought. (shrink)

Diagnoses in medicine are often taken to serve as explanations of patients’ symptoms and signs. This article examines how they do so. I begin by arguing that although some instances of diagnostic explanation can be formulated as covering law arguments, they are explanatory neither in virtue of their argumentative structures nor in virtue of general regularities between diagnoses and clinical presentations. I then consider the theory that medical diagnoses explain symptoms and signs by identifying their actual causes in particular cases. (...) While I take this to be largely correct, I argue that for a diagnosis to function as a satisfactory causal explanation of a patient’s symptoms and signs, it also needs to be supplemented by understanding the mechanisms by which the identified cause produces the symptoms and signs. This mechanistic understanding comes not from the diagnosis itself, but rather from the theoretical framework within which the physician operates. (shrink)

Numerous studies of the beliefs of people with anorexia nervosa (AN) suggest that a subset of such individuals may experience delusions. We first describe what makes a belief delusional and conclude that such characteristics can be appropriately applied to some beliefs of people with AN. Next, we outline how delusional beliefs may relate to the broader psychopathological process in AN, including: (1) they may be epiphenomenal; (2) they may be an initial partial cause of AN; (3) they may be caused (...) by aspects of AN; or (4) they may be sustaining causes, possibly involved in reciprocal causal relations with aspects of AN. We argue that there is good reason to believe that delusional beliefs of people with AN are not merely epiphenomenal, but rather that they’re causally connected to AN. Because of this, empirical studies can be designed to test for the presence of causal relations. We describe how these studies should be designed. The results of such studies have important implications for understanding the experience of individuals with AN and for the treatment of AN. We outline these implications. (shrink)

In this paper, I show how semantic factors constrain the understanding of the computational phenomena to be explained so that they help build better mechanistic models. In particular, understanding what cognitive systems may refer to is important in building better models of cognitive processes. For that purpose, a recent study of some phenomena in rats that are capable of ‘entertaining’ future paths (Pfeiffer and Foster 2013) is analyzed. The case shows that the mechanistic account of physical computation may (...) be complemented with semantic considerations, and in many cases, it actually should. (shrink)

Michael Strevens offers an account of causal explanation according to which explanatory practice is shaped by counterbalanced commitments to representing causal influence and abstracting away from overly specific details. In this paper, I challenge a key feature of that account. I argue that what Strevens calls explanatory frameworks figure prominently in explanatory practice because they actually improve explanations. This suggestion is simple but has far-reaching implications. It affects the status of explanations that cite multiply realizable properties; changes the (...) explanatory role of causal factors with small effect; and undermines Strevens’ titular explanatory virtue, depth. This results in greater coherence with explanatory practice and accords with the emphasis that Strevens places on explanatory patterns. Ultimately, my suggestion preserves a tight connection between explanation and the creation of understanding by taking into account explanations’ role in communication. (shrink)

This paper responds to critical commentaries on my book, Perceiving Reality (OUP, 2012), by Laura Guerrero, Matthew MacKenzie, and Anand Vaidya. Guerrero focuses on the metaphysics of causation, and its role in the broader question of whether the ‘two truths’ framework of Buddhist philosophy can be reconciled with the claim that science provides the best account of our experienced world. MacKenzie pursues two related questions: (i) Is reflexive awareness (svasaṃvedana) identical with the subjective pole of a dual-aspect cognition or are (...) there alternative, perhaps better, ways of understanding this self-intimating character of mental states? (ii) Is perception constitutively intentional or is it representational? Vaidya argues that, in so far as Husserlian phenomenology and Buddhism differ in terms of their fundamental ontological commit- ments, they must be incompatible, thus rendering any cross-cultural philosophical project that seeks their rapprochement tenuous. One of my aims in Perceiving Reality is to show how accounts of perception informed by metaphysical realism can be problematic on both metaphysical and epistemological grounds, especially when relying on conceptions of consciousness that ignore its properly phenomenological features. (shrink)

If Charles Darwin’s work opened up the possibility of a true natural history, the signicance of time in evolutionary processes was left unresolved. This ambiguity has led to various interpretations of what evolutionary history is, some seeing it as the pure unfolding of processes, others as a ow marked by contingency and unpredictability. These interpretations re ect underlying differences in the perception of causality: mechanical and uniform on the one hand, transformative and multifaceted on the other. This tension affects not (...) only our understanding of the Darwinian text, but also our contemporary conception of evolutionary theory. Although many challenges in evolutionary biology are linked to time (the historicity of evolution, path-dependent processes, biological rhythms, the contingency of certain evolutionary events etc.), the importance attributed to time in biology remains unspeci ed. The aim of this chapter is to study the contradictions regarding the conception of history and causality in Darwin’s writings and to analyse how they have permeated the different interpretations of evolutionary theory from the turn of the twentieth century to the present day. This analysis of the tensions within the different interpretations of Darwinism in history will lead me to address both the conception of biological time(s) and the approach to causality in contemporary evolutionary biology. I will conclude this chapter by proposing some clarications about the signicance of time in contemporary evolutionary biology. (shrink)

The aim of this article is to develop an understanding-based argument for an explicitly political specification of the concept of race. It is argued that a specification of race in terms of hierarchical social positions is best equipped to guide causal reasoning about racial inequality in the public sphere. Furthermore, the article provides evidence that biological and cultural specifications of race mislead public reasoning by encouraging confusions between correlates and causes of racial inequality. The article concludes with a (...) more general case for incorporating empirical evidence about public reasoning into philosophical debates about competing specifications of the concept of race. (shrink)

Understanding causation in social-ecological systems (SES) is indispensable for promoting sustainable outcomes. However, the study of such causal relations is challenging because they are often complex and intertwined, and their analysis involves diverse disciplines. Although there is agreement that no single research approach (RA) can comprehensively explain SES phenomena, there is a lack of ability to deal with this diversity. Underlying this diversity and the challenge of dealing with it are different causal reasonings that are rarely explicit. (...) Awareness of hidden assumptions is essential for understanding how the causal reasoning of an RA is constituted, and for promoting the integration, translation, or juxtaposition of different RAs. We identify the following elements as particularly relevant for understanding causal reasoning: methods, frameworks and theories, accounts of causation, analytical focus, and causal notions. We begin with the idea that one of these elements typically figures as an entry point to an RA. This entry point is particularly important because it generates a path dependence that orients causal reasoning. In a subsequent step, when an approach is applied, causal reasoning concretizes as a result of a particular constellation of the remaining elements. We come to these insights by studying the application of four different RAs to the same social-ecological case (the collapse of Baltic cod stocks in the 1980s). On the basis of our findings we developed a guide for the analysis of causal reasoning by raising awareness of the assumptions, key elements, and the relations between these key elements for a given RA. The guide can be used to elicit the causal reasoning of RAs, facilitate interdisciplinary collaboration, and support disclosure of ethical/political dimensions that underlie management/governance interventions that are formulated on the basis of causal findings of research studies. (shrink)

Cognitive neuroscience is an interdisciplinary enterprise aimed at explaining cognition and behavior. It appears to be succeeding. What accounts for this apparent explanatory success? According to one prominent philosophical thesis, cognitive neuroscience explains by discovering and describing mechanisms. This "mechanist thesis" is open to at least two interpretations: a strong metaphysical thesis that Carl Craver and David Kaplan defend, and a weaker methodological thesis that William Bechtel defends. I argue that the metaphysical thesis is false and that the methodological thesis (...) is too weak to account for the explanatory promise of cognitive neuroscience. My argument draws support from a representative example of research in this field, namely, the neuroscience of decision-making. The example shows that cognitive neuroscience explains in a variety of ways and that the discovery of mechanisms functions primarily as a way of marshaling evidence in support of the models of cognition that are its principle unit of explanatory significance. -/- The inadequacy of the mechanist program is symptomatic of an implausible but prominent view of scientific understanding. On this view, scientific understanding consists in an accurate and complete description of certain "objective" explanatory relations, that is, relations that hold independently of facts about human psychology. I trace this view to Carl Hempel's logical empiricist reconceptualization of scientific understanding, which then gets extended in Wesley Salmon's causal-mechanistic approach. I argue that the twin objectivist ideals of accuracy and completeness are neither ends we actually value nor ends we ought to value where scientific understanding is concerned. -/- The case against objectivism motivates psychologism about understanding, the view that understanding depends on human psychology. I propose and defend a normative psychologistic framework for investigating the nature of understanding in the mind sciences along three empirically-informed dimensions: 1) What are the ends of understanding? 2) What is the nature of the cognitive strategy that we deploy to achieve those ends; and 3) Under what conditions is our deployment of this strategy effective toward achieving those ends? To articulate and defend this view, I build on the work of Elliot Sober to develop a taxonomy of psychologisms about understanding. Epistemological psychologism, a species of naturalism, is the view that justifying claims about understanding requires appealing to what scientists actually do when they seek understanding. Metaphysical psychologism is the view that the truth-makers for claims about understanding include facts about human psychology. I defend both views against objections. (shrink)

In this paper we will look at research by the philosopher of the mind João Fernandes Teixeira in "Uma nota sobre Sartre e Damásio ou as emoções entre a Fenomenologia e a Neurobiologia". From this we will analyze the theory of emotions of Jean-Paul Sartre in "Sketch for a Theory of Emotions" and of the neurobiologist António Damásio " Looking for Spinoza: Joy, Sorrow and the feeling Brain ". We will briefly discuss the theory of emotions of Jesse Prinz and (...) neuroscientist Robert Lent. Finally, we will propose that the synthesis for the quest to identify the meaning of emotions, as Sartre wanted, should involve combining different causal approaches to emotional phenomena to better understand the. (shrink)

Intuitions play an important role in the debate on the causal status of high‐level properties. For instance, Kim has claimed that his “exclusion argument” relies on “a perfectly intuitive … understanding of the causal relation.” We report the results of three experiments examining whether laypeople really have the relevant intuitions. We find little support for Kim's view and the principles on which it relies. Instead, we find that laypeople are willing to count both a multiply realized property (...) and its realizers as causes, and regard the systematic overdetermination implied by this view as unproblematic. (shrink)

There is a long tradition of logic, from Aristotle to Gödel, of understanding a proof from the concepts of necessity and causality. Gödel's attempts to define provability in terms of necessity led him to the distinction of formal and absolute (abstract) provability. Turing's definition of mechanical procedure by means of a Turing machine (TM) and Gödel's definition of a formal system as a mechanical procedure for producing formulas prompt us to understand formal provability as a mechanical causality. We propose (...) a formalism which makes explicit the mechanical causal nature of a TM's work. We claim that Gödel's axiomatised ontotheology and his ontological proof give a clue for the understanding of the concept of absolute provability and the pattern of the corresponding absolute completeness proof, respectively. (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)

In the last couple of years, a few seemingly independent debates on scientific explanation have emerged, with several key questions that take different forms in different areas. For example, the questions what makes an explanation distinctly mathematical and are there any non-causal explanations in sciences (i.e., explanations that don’t cite causes in the explanans) sometimes take a form of the question of what makes mathematical models explanatory, especially whether highly idealized models in science can be explanatory and in virtue (...) of what they are explanatory. These questions raise further issues about counterfactuals, modality, and explanatory asymmetries: i.e., do mathematical and non-causal explanations support counterfactuals, and how ought we to understand explanatory asymmetries in non-causal explanations? Even though these are very common issues in the philosophy of physics and mathematics, they can be found in different guises in the philosophy of biology where there is the statistical interpretation of the Modern Synthesis theory of evolution, according to which the post-Darwinian theory of natural selection explains evolutionary change by citing statistical properties of populations and not the causes of changes. These questions also arise in philosophy of ecology or neuroscience in regard to the nature of topological explanations. The question here is can the mathematical (or more precisely topological) properties in network models in biology, ecology, neuroscience, and computer science be explanatory of physical phenomena, or are they just different ways to represent causal structures. The aim of this special issue is to unify all these debates around several overlapping questions. These questions are: are there genuinely or distinctively mathematical and non-causal explanations?; are all distinctively mathematical explanations also non-causal; in virtue of what they are explanatory; does the instantiation, implementation, or in general, applicability of mathematical structures to a variety of phenomena and systems play any explanatory role? This special issue provides a platform for unifying the debates around several key issues and thus opens up avenues for better understanding of mathematical and non-causal explanations in general, but also, it will enable even better understanding of key issues within each of the debates. (shrink)

Recent studies indicate that indicative conditionals like "If people wear masks, the spread of Covid-19 will be diminished" require a probabilistic dependency between their antecedents and consequents to be acceptable (Skovgaard-Olsen et al., 2016). But it is easy to make the slip from this claim to the thesis that indicative conditionals are acceptable only if this probabilistic dependency results from a causal relation between antecedent and consequent. According to Pearl (2009), understanding a causal relation involves multiple, hierarchically (...) organized conceptual dimensions: prediction, intervention, and counterfactual dependence. In a series of experiments, we test the hypothesis that these conceptual dimensions are differentially encoded in indicative and counterfactual conditionals. If this hypothesis holds, then there are limits as to how much of a causal relation is captured by indicative conditionals alone. Our results show that the acceptance of indicative and counterfactual conditionals can become dissociated. Furthermore, it is found that the acceptance of both is needed for accepting a causal relation between two co-occurring events. The implications that these findings have for the hypothesis above, and for recent debates at the intersection of the psychology of reasoning and causal judgment, are critically discussed. Our findings are consistent with viewing indicative conditionals as answering predictive queries requiring evidential relevance (even in the absence of direct causal relations). Counterfactual conditionals in contrast target causal relevance, specifically. Finally, we discuss the implications our results have for the yet unsolved question of how reasoners succeed in constructing causal models from verbal descriptions. (shrink)

Rival causal and interpretive approaches to explaining social phenomena have important ethical differences. While human actions can be explained as a result of causal mechanisms, as a meaningful choice based on reasons, or as some combination of the two, it is morally important that social scientists respect others by recognizing them as persons. Interpretive explanations directly respect their subjects in this way, while purely causal explanations do not. Yet although causal explanations are not themselves expressions of (...) respect, they can be used in respectful ways if they are incorporated into subjects’ self-directed projects. This can occur when subjects correctly understand and freely adopt researchers’ goals through a process of informed consent. It can also occur when researchers correctly understand and adopt their subject’s goals, using their research to empower those they study. (shrink)

Jacques Monod (1971) argued that certain molecular processes rely critically on the property of chemical arbitrariness, which he claimed allows those processes to “transcend the laws of chemistry”. It seems natural, as some philosophers have done, to interpret this in modal terms: a biological relationship is chemically arbitrary if it is possible, within the constraints of chemical “law”, for that relationship to have been otherwise than it is. But while modality is certainly important for understanding chemical arbitrariness, understanding (...) its biological role also requires an account of the concrete causal-functional features that distinguish arbitrary from non-arbitrary phenomena. In this paper I elaborate on this under-emphasised aspect by offering a general account of these features: arbitrary relations are instantiated by mechanisms that involve molecular adapters, which causally couple two properties or processes which would otherwise be uncorrelated. Additionally, adapters work by acting as intermediate rather than cooperating causes. (shrink)

When does a model explain? When does it promote understanding? A dominant approach to scientific explanation is the interventionist view. According to this view, when X explains Y, intervening on X can produce, prevent or alter Y in some predictable way. In this paper, I argue for two claims. First, I reject a position that many interventionist theorists endorse. This position is that to explain some phenomenon by providing a model is also to understand that phenomenon. While endorsing the (...) interventionist view, I argue that explaining and understanding are distinct scientific achievements. Second, I defend a novel theory of scientific understanding. According to this view, when some model M promotes understanding, M makes available a distinctive mental state. This state is of the same psychological kind as when we grasp events in a narrative as bearing on some ultimate conclusion. To conclude, I show that, given this view, mechanistic explanations often provide a powerful source of understanding that many causal-historical models lack. This paper will be of interest to both philosophers of science and epistemologists engaged in the topics of explanation and understanding. (shrink)

As physical entities that translate symbols into physical actions, computers offer insights into the nature of meaning and agency. • Physical symbol systems, generically known as agents, link abstractions to material actions. The meaning of a symbol is defined as the physical actions an agent takes when the symbol is encountered. • An agent has autonomy when it has the power to select actions based on internal decision processes. Autonomy offers a partial escape from constraints imposed by direct physical influences (...) such as gravity and the transfer of momentum. Swimming upstream is an example. • Symbols are names that can designate other entities. It appears difficult to explain the use of names and symbols in terms of more primitive functionality. The ability to use names and symbols, i.e., symbol grounding, may be a fundamental cognitive building block. • The standard understanding of causality—wiggling X results in Y wiggling—applies to both physical causes (e.g., one billiard ball hitting another) and symbolic causes (e.g., a traffic light changing color). Because symbols are abstract, they cannot produce direct physical effects. For a symbol to be a cause requires that the affected entity determine its own response. This is called autonomous causality. • This analysis of meaning and autonomy offers new perspectives on free will. (shrink)

Can the persistence of a human being's soul at death and prior to the bodily resurrection be sufficient to guarantee that the resurrected human being is numerically identical to the human being who died? According to Thomas Aquinas, it can. Yet, given that Aquinas holds that the human being is identical to the composite of soul and body and ceases to exist at death, it's difficult to see how he can maintain this view. In this paper, I address Aquinas's response (...) to this objection . After making a crucial clarification concerning the nature of the non-repeatability principle on which the objection relies, I argue that the contemporary notion of immanent causal relations provides us with a way of understanding Aquinas's defence that renders it both highly interesting and philosophically plausible. (shrink)

Kant’s view that freedom is a “kind of causality” seems to conflict with his claim that the categories of the understanding – including causality – can only be applied objectively to sensible phaenomena, never to supersensible noumena, as freedom is only possible for the latter. I argue that only Kant’s theory of symbolic presentation, according to which the category of cause is applied merely analogically to freedom, can dispel this threatening inconsistency. Unlike it is commonly thought, one cannot here (...) use the category of cause in its unschematised form to think freedom as causality, for its mere logical significance does not suffice for the practical reality of freedom. Symbolic cognition in turn is not unschematised but indirect schematized presentation. Ultimately I will show that symbolic cognition is a necessary condition of moral agency – but not of morality itself – for without it we could not cognize and hence self-consciously use our freedom to act from the moral law. (shrink)

I highlight a metaphysical concern that stands in the way of more widespread adoption of causal modeling techniques such as causal Bayes nets. Researchers in some fields may resist adoption due to concerns that they don't 'really' understand what they are saying about a system when they apply such techniques. Students in these fields are repeated exhorted to be cautious about application of statistical techniques to their data without a clear understanding of the conditions required for those (...) techniques to yield genuine insight into the data. They are acutely aware that anyone can chuck some data into a software package and get what looks like an answer, even though these tests may not be well-defined for the data on which they can apparently be run. This is thus a healthy skepticism for uptake of causal modeling methods, which points directly to the need for a metaphysical understanding of causation in order to successfully use the modeling methods. Without a clear understanding of what the methods are committing to, including what it means to say that there exists a causal relationship, researchers have limited ability to identify potentially bad output, or to independently verify results. (shrink)

It has been stated that the notion of cause and effect is one object of study that sciences and engineering revolve around. Lately, in software engineering, diagrammatic causal inference methods (e.g., Pearl’s model) have gained popularity (e.g., analyzing causes and effects of change in software requirement development). This paper concerns diagrammatical (graphic) models of causal relationships. Specifically, we experiment with using the conceptual language of thinging machines (TMs) as a tool in this context. This would benefit works on (...) causal relationships in requirements engineering, enhance our understanding of the TM modeling, and contribute to the study of the philosophical notion of causality. To specify the causality in a system’s description is to constrain the system’s behavior and thus exclude some possible chronologies of events. The notion of causality has been studied based on tools to express causal questions in diagrammatic and algebraic forms. Causal models deploy diagrammatic models, structural equations, and counterfactual and interventional logic. Diagrammatic models serve as a language for representing what we know about the world. The research methodology in the paper focuses on converting causal graphs into TM models and contrasts the two types of representation. The results show that the TM depiction of causality is more complete and therefore can provide a foundation for causal graphs. (shrink)

As physicalisms of various kinds have faced difficulties in recent years, the time has come to explore possible alternatives, one of which is yinyang ontology. A yinyang theorist is expected to provide a plausible account of causation to replace the traditional notion of causation. The present paper is critical of the Humean tradition, which understands the relata of causal relations in terms of passive materiality so that humans use referential terms to describe causal relations constructively. But an alternative (...) notion of reference is available according to which causal relata are active processors of the information with which they interact. On this latter view, humans use referential language to describe the structure in which the relata interrelate themselves so that the structure can be understood hermeneutically. Reference on this view is naturalized. In this article I advance two arguments for this thesis, one concerning the informationality of states and the other related to the essentiality of properties. (shrink)

The search for understanding is a major aim of science. Traditionally, understanding has been undervalued in the philosophy of science because of its psychological underpinnings; nowadays, however, it is widely recognized that epistemology cannot be divorced from psychology as sharp as traditional epistemology required. This eliminates the main obstacle to give scientific understanding due attention in philosophy of science. My aim in this paper is to describe an account of scientific understanding as an emergent feature of (...) our mastering of different (causal) explanatory frameworks that takes place through the mastering of scientific practices. Different practices lead to different kinds of representations. Such representations are often heterogeneous. The integration of such representations constitute understanding. (shrink)

"Explanation and Understanding" (1971) by Georg Henrik von Wright is a modern classic in analytic hermeneutics, and in the philosophy of the social sciences and humanities in general. In this work, von Wright argues against naturalism, or methodological monism, i.e. the idea that both the natural sciences and the social sciences follow broadly the same general scientific approach and aim to achieve causal explanations. Against this view, von Wright contends that the social sciences are qualitatively different from the (...) natural sciences: according to his view, the natural sciences aim at causal explanations, whereas the purpose of the social sciences is to understand their subjects. In support of this conviction, von Wright also puts forward a version of the so-called logical connection argument. -/- Von Wright views scientific explanation along the lines of the traditional covering law model. He suggests that the social sciences, in contrast, utilize what he calls “practical syllogism” in understanding human actions. In addition, von Wright presents in this work an original picture on causation: a version of the manipulability theory of causation. -/- In the four decades following von Wright’s classic work, the overall picture in in the philosophy of science has changed significantly, and much progress has been made in various fronts. The aim of the contribution is to revisit the central ideas of "Explanation and Understanding" and evaluate them from this perspective. The covering law model of explanation and the regularity theory of causation behind it have since then fallen into disfavor, and virtually no one believes that causal explanations even in the natural sciences comply with the covering law model. No wonder then that covering law explanations are not found in the social sciences either. Ironically, the most popular theory of causal explanation in the philosophy of science nowadays is the interventionist theory, which is a descendant of the manipulability theory of von Wright and others. However, this theory can be applied with no special difficulties in both the natural sciences and the social sciences. -/- Von Wright’s logical connection argument and his ideas concerning practical syllogisms are also critically assessed. It is argued that in closer scrutiny, they do not pose serious problems for the view that the social sciences too provide causal explanations. In sum, von Wright’s arguments against naturalism do not appear, in today’s perspective, particularly convincing. (shrink)