Naturalistic theories of representation seek to specify the conditions that must be met for an entity to represent another entity. Although these approaches have been relatively successful in certain areas, such as communication theory or genetics, many doubt that they can be employed to naturalize complex cognitive representations. In this essay I identify some of the difficulties for developing a teleosemantic theory of cognitive representations and provide a strategy for accommodating them: to look into models of signaling in evolutionary game (...) theory. I show how these models can be used to formulate teleosemantics and expand it in new directions. (shrink)

Although the definition of ‘signal’ has been controversial for some time within the life sciences, current approaches seem to be converging toward a common analysis. This powerful framework can satisfactorily accommodate many cases of signaling and captures some of its main features. This paper argues, however, that there is a central feature of signals that so far has been largely overlooked: its special causal role. More precisely, I argue that a distinctive feature of signals is that they are minimal causes. (...) I explain this notion, suggest some strategies for identifying its instances and defend its relevance by means of conceptual and empirical considerations. (shrink)

The indeterminacy problem is one of the most prominent objections against naturalistic theories of content. In this essay I present this difficulty and argue that extant accounts are unable to solve it. Then, I develop a particular version of teleosemantics, which I call ’explanation-based teleosemantics’, and show how this outstanding problem can be addressed within the framework of a powerful naturalistic theory.

Recent research on bacteria and other microorganisms has provided interesting insights into the nature of life, cooperation, evolution, individuality or species. In this paper, I focus on the capacity of bacteria to produce molecules that are usually classified as ’signals’ and I defend two claims. First, I argue that certain interactions between bacteria should actually qualify as genuine forms of communication. Second, I use this case study to revise our general theories of signaling. Among other things, I argue that a (...) plausible requirement for a state to qualify as a signal is that it is a minimal cause. (shrink)

In the biological realm, a complete explanation of a trait seems to include an explanation in terms of function. It is natural to ask of some trait, "What is its function?" or "What purpose in the organism does the particular trait serve?" or "What is the goal of its activity?" There are several views concerning the appropriate definition of function for biological matters. Two popular views of function with respect to living things are Cummins' organizational account and the Griffiths/Godfrey-Smith modern (...) history account. Whereas Cummins argues that a trait functions so as to contribute to the general organization of some organism's present structure, Griffiths, and Godfrey-Smith argue that a trait functions because of its fitness with respect to the organism's recent evolutionary history. In this paper, I show how these accounts can be made compatible and compliment one another. Given that structure, organization, operational flexibility, function, and evolutionary history are all factors to be considered in an organism's makeup, we should expect that the traits of an organism function the way they do because such traits presently contribute to the overall organization of the organism (Cummins) as well as were selected for in the organism's species' recent ancestry (Griffiths/Godfrey-Smith). (shrink)

One important aspect of biological explanation is detailed causal modeling of particular phenomena in limited experimental background conditions. Recognising this allows one to appreciate that a sufficient condition for a reduction in biology is a molecular model of (1) only the demonstrated causal parameters of a biological model and (2) only within a replicable experimental background. These identities—which are ubiquitous in biology and form the basis of ruthless reductions (Bickle, Philosophy and neuroscience: a ruthlessly reductive account, 2003)—are criticised as merely (...) “local” (Sullivan, Synthese 167:511–539, 2009) or “fragmentary” (Schaffner, Synthese, 151(3):377–402, 2006). However, in an instructive case, a biological model is preserved in molecular terms, demonstrating a complex phenomenon that has been successfully reduced. (shrink)

The emphasis on the organization of entities and their activities and interactions has been labeled one of the most distinct contributions of mechanistic philosophy. In this paper I discuss the manner in which the organization of entities and their activities and interactions participates in bringing about phenomena. I present a well-known example from molecular biology—the functioning of the genetic switch in phage lambda—and discuss Marco J. Nathan’s notion of causation by concentration. Nathan introduces causation by concentration to account for the (...) irreducible causal role that the concentration ratio between two kinds of proteins possesses in the genetic switch mechanism in phage lambda. I discuss what the irreducibility of this causal role amounts to and provide a mechanistic interpretation of Nathan’s causation by concentration; that is, I explain this irreducible causal role as one organizational feature of this mechanism. The paper concludes that biological mechanisms need a causal pluralist framework [similar to Glennan’s account in, and but slightly modified] where organizational features such as the concentration ratio have a causally relevant role, yet all the causally productive relations occur at the level of entities or individuals. (shrink)

This paper addresses the methodological problem of analysing what it is to explain observed behaviours of engineered computing systems, focusing on the crucial role that abstraction and idealization play in explanations of both correct and incorrect BECS. First, it is argued that an understanding of explanatory requests about observed miscomputations crucially involves reference to the rich background afforded by hierarchies of functional specifications. Second, many explanations concerning incorrect BECS are found to abstract away from descriptions of physical components and processes (...) of computing systems that one finds below the logic circuit and gate layer of functional specification hierarchies. Third, model-based explanations of both correct and incorrect BECS that are provided in the framework of formal verification methods often involve idealizations. Moreover, a distinction between restrictive and permissive idealizations is introduced and their roles in BECS explanations are analysed. (shrink)

How regular do mechanisms need to be, in order to count as mechanisms? This paper addresses two arguments for dropping the requirement of regularity from the definition of a mechanism, one motivated by examples from the sciences and the other motivated by metaphysical considerations regarding causation. I defend a broadened regularity requirement on mechanisms that takes the form of a taxonomy of kinds of regularity that mechanisms may exhibit. This taxonomy allows precise explication of the degree and location of regular (...) operation within a mechanism, and highlights the role that various kinds of regularity play in scientific explanation. I defend this regularity requirement in terms of regularity’s role in individuating mechanisms against a background of other causal processes, and by prioritizing mechanisms’ ability to serve as a model of scientific explanation, rather than as a metaphysical account of causation. It is because mechanisms are regular, in the expanded sense described here, that they are capable of supporting the kinds of generalizations that figure prominently in scientific explanations. (shrink)

Even though the evidence‐based medicine movement (EBM) labels mechanisms a low quality form of evidence, consideration of the mechanisms on which medicine relies, and the distinct roles that mechanisms might play in clinical practice, offers a number of insights into EBM itself. In this paper, I examine the connections between EBM and mechanisms from several angles. I diagnose what went wrong in two examples where mechanistic reasoning failed to generate accurate predictions for how a dysfunctional mechanism would respond to intervention. (...) I then use these examples to explain why we should expect this kind of mechanistic reasoning to fail in systematic ways, by situating these failures in terms of evolved complexity of the causal system(s) in question. I argue that there is still a different role in which mechanisms continue to figure as evidence in EBM: namely, in guiding the application of population‐level recommendations to individual patients. Thus, even though the evidence‐based movement rejects one role in which mechanistic reasoning serves as evidence, there are other evidentiary roles for mechanistic reasoning. This renders plausible the claims of some critics of evidencebased medicine who point to the ineliminable role of clinical experience. Clearly specifying the ways in which mechanisms and mechanistic reasoning can be involved in clinical practice frames the discussion about EBM and clinical experience in more fruitful terms. (shrink)

Leuridan (2010) argued that mechanisms cannot provide a genuine alternative to laws of nature as a model of explanation in the sciences, and advocates Mitchell’s (1997) pragmatic account of laws. I first demonstrate that Leuridan gets the order of priority wrong between mechanisms, regularity, and laws, and then make some clarifying remarks about how laws and mechanisms relate to regularities. Mechanisms are not an explanatory alternative to regularities; they are an alternative to laws. The existence of stable regularities in nature (...) is necessary for either model of explanation: regularities are what laws describe and what mechanisms explain. (shrink)

Humean accounts of laws are often contrasted with governing accounts, and recent developments have added pragmatic versions of Humeanism. This paper offers Mitchell's pragmatist, perspectival account of laws as a third option. The differences between these accounts come down to the role of modality. Mitchell's bottom-up account allows for subtle gradations of modal content to be conveyed by laws. The perspectival character of laws is not an accident or something to be eventually eliminated - it is part of how this (...) modal content is conveyed. I conclude with a discussion of the metaphysical commitments in Humeanism as requiring a perspectiveless view of the manifold from outside, and how Mitchell's situated account is better able to account for the substantive notion of possibility involved in scientific laws. (shrink)

In this field guide, I distinguish five separate senses with which the term ‘mechanism’ is used in contemporary philosophy of science. Many of these senses have overlapping areas of application but involve distinct philosophical claims and characterize the target mechanisms in relevantly different ways. This field guide will clarify the key features of each sense and introduce some main debates, distinguishing those that transpire within a given sense from those that are best understood as concerning distinct senses. The ‘new mechanisms’ (...) sense is at the center of most of these contemporary debates and will be treated at greater length; subsequent senses of mechanism will be primarily distinguished from this one. In part I of this paper, I distinguish two senses of the term ‘mechanism’, both of which are explicitly hierarchical and nested in character, such that any given mechanism is comprised of smaller sub-mechanisms, in turn comprised of yet smaller sub-sub-mechanisms and so on. While both of the senses discussed here are anti-reductive, they differ in their focus on scientific practice versus metaphysics, in the degree of regularity they attribute to mechanisms, and in terms of their relationships to the discussions of mechanisms in the history of philosophy and science. (shrink)

The dual process theory is a view that there are two information-processing systems in our mind. It has been popular in cognitive and social psychology for the last few decades, but this simplified formulation of the theory has problems. In this paper I shall review the recent developments made by the dual process theorists to meet those challenges and indicate the directions the theory could take. In particular I shall discuss possible defining properties or mechanisms of the two systems. I (...) argue that working memory and its neural correlates, but not cognitive decoupling, are the underlying mechanisms of the "reflective" system while the "intuitive" system may have rather external underlying mechanisms, i.e., natural selection. This renders both systems homeostatic property cluster kinds but they are based on different kinds of mechanisms. (shrink)

Partiendo de la distinción filosófica entre las leyes de la ciencia y las leyes de la naturaleza, en el presente artículo se defiende la indispensabilidad explicativa de las leyes de la ciencia en el campo de las ciencias cognitivas. Se sostiene que las leyes de la ciencia desempeñan un papel epistémico indispensable tanto en el análisis funcional como en la explicación mecanicista de las capacidades cognitivas. De esta manera, se ofrece una elucidación plausible del poder explicativo de las ciencias cognitivas (...) en términos del papel epistémico de las leyes de la ciencia, suspendiendo el juicio, de manera prudente, respecto del controvertido estatus metafísico de las leyes naturales. Se pone en evidencia que tanto quienes defienden como quienes rechazan el compromiso ontológico con leyes causales intencionales presuponen que esas leyes no contribuyen a la explicación funcionalista ni mecanicista de los fenómenos que describen. Sin embargo, en el presente trabajo se argumenta, primero, que el análisis funcional requiere la especificación de leyes científicas no causales y, segundo, que la representación científica precisa de las actividades y de la organización dinámica de un mecanismo se despliega mayoritariamente, en el contexto de un modelo mecanicista, mediante la especificación de leyes científicas. La conclusión es que las leyes científicas (aunque no necesariamente las leyes de la naturaleza) desempeñan un papel indispensable en la explicación en ciencias cognitivas. (shrink)

In this paper, I describe grounds for dissatisfaction with certain aspects of the sciences of animal cognition and argue that a turn toward mathematical modeling of animal cognition is warranted. I consider some objections to this call and argue that the implications of such a turn are not as drastic for ordinary, commonsense understanding of animal minds as they might seem.

In the recent literature on causal and non-causal scientific explanations, there is an intuitive assumption according to which an explanation is non-causal by virtue of being abstract. In this context, to be ‘abstract’ means that the explanans in question leaves out many or almost all causal microphysical details of the target system. After motivating this assumption, we argue that the abstractness assumption, in placing the abstract and the causal character of an explanation in tension, is misguided in ways that are (...) independent of which view of causation or causal explanation one takes to be most accurate. On major accounts of causation, as well as on major accounts of causal explanation, the abstractness of an explanation is not sufficient for it being non-causal. That is, explanations are not non-causal by dint of being abstract. (shrink)

This paper discusses the important paper by Paul Thagard on the pathway version of mechanistic explanation that is currently used in chemical explanation. The author claims that this method of explanation has a respectable pedigree and can be traced back to the Chemical Revolution in the arguments used by the Lavoisier School in their theoretical duels with Richard Kirwan, the proponent of a revised phlogistonian theory. Kirwan believed that complex chemical reactions could be explained by recourse to affinity tables that (...) catalogued the attraction that various simple bodies possessed towards each other. To explain was in effect to make a delayed prediction, it is not enough just to show how a phenomenon fits into the discernible patterns of the world. Lavoisier, Fourcroy and their colleagues used pathway reasoning, although disguising this fact by suggesting that affinities varied when subjected to n-body situations. (shrink)

Cognitive science is unusual in that cognitive scientists have dramatic disagreements about the extension of their object of study, cognition. This paper defends a novel analysis of the scientific concept of cognition: that cognition is the sensitive management of an agent’s behavior. This analysis is “modular,” so that its extension varies depending on how one interprets certain of its constituent terms. I argue that these variations correspond to extant disagreements between cognitive scientists. This correspondence is evidence that the proposed analysis (...) models the contemporary understanding of cognition among scientists, without artificially resolving questions that are currently considered open. (shrink)

One might have thought that if something has two or more distinct realizations, then that thing is multiply realized. Nevertheless, some philosophers have claimed that two or more distinct realizations do not amount to multiple realization, unless those distinct realizations amount to multiple “ways” of realizing the thing. Corey Maley, Gualtiero Piccinini, Thomas Polger, and Lawrence Shapiro are among these philosophers. Unfortunately, they do not explain why multiple realization requires multiple “ways” of realizing. More significantly, their efforts to articulate multiple (...) “ways” of realizing turn out to be problematic. (shrink)

We contend that diagrams are tools not only for communication but also for supporting the reasoning of biologists. In the mechanistic research that is characteristic of biology, diagrams delineate the phenomenon to be explained, display explanatory relations, and show the organized parts and operations of the mechanism proposed as responsible for the phenomenon. Both phenomenon diagrams and explanatory relations diagrams, employing graphs or other formats, facilitate applying visual processing to the detection of relevant patterns. Mechanism diagrams guide reasoning about how (...) the parts and operations work together to produce the phenomenon and what experiments need to be done to improve on the existing account. We examine how these functions are served by diagrams in circadian rhythm research. (shrink)

The use of unrealistic assumptions in Economics is usually defended not only for pragmatic reasons, but also because of the intrinsic difficulties in determining the degree of realism of assumptions. Additionally, the criterion used for evaluating economic models is associated with their ability to provide accurate predictions. This mode of thought involves –at least implicitly– a commitment to the existence of unvarying invariant factors or regularities. Contrary to this, the present paper presents a critique to the use of invariant knowledge (...) in economics. One reason for this analysis lies in the fact that economic phenomena are not compatible with the logic of invariance, but with the logic of "possibility trees" or "open-ended results". The other reason is that the use of invariant knowledge may entail both external validity problems and negative exposures to a "black swan". Alternatively, an approach where models are understood as possible scenarios is proposed. It is argued that the realism of assumptions is crucial here, since it helps to ascertain the degree of resemblance between the different models and the target system. (shrink)

Arguments for the autonomy of psychology or other higher-level sciences have often taken the form of denying the possibility of reduction. The form of reduction most proponents and critics of the autonomy of psychology have in mind is theory reduction. Mechanistic explanations provide a different perspective. Mechanistic explanations are reductionist insofar as they appeal to lower-level entities—the component parts of a mechanism and their operations— to explain a phenomenon. However, unlike theory reductions, mechanistic explanations also recognize the fundamental role of (...) organization in enabling mechanisms to engage their environments as units (as well as the role of yet higher-level structures in constraining such engagement). Especially when organization is non-linear, it can enable mechanisms to generate phenomena that are quite surprising given the operations of the components taken in isolation. Such organization must be discovered—it cannot simply be derived from knowledge of lower-level parts and their operations. Moreover, the organized environments in which mechanisms operate must also be discovered. It is typically the higher-level disciplines that have the tools for discovering the organization within and between mechanisms. Although these inquiries are constrained by the knowledge of the parts and operations constituting the mechanism, they make their own autonomous contribution to understanding how a mechanism actually behaves. Thus, mechanistic explanations provide a strong sense of autonomy for higher levels of organization and the inquiries addressing them even while recognizing the distinctive contributions of reductionistic research investigating the operations of the lower level components. (shrink)

Explanations in behavioural neuroscience are often said to be mechanistic in the sense that they explain an organism’s behaviour by describing the activities and organisation of the organism’s parts that are “constitutively relevant” to organism behaviour. Much has been said about the constitutive relevance of working parts (in debates about the so-called “mutual manipulability criterion”), but relatively little has been said about the constitutive relevance of the organising relations between working parts. Some New Mechanists seem to endorse a simple causal-linking (...) account: organising relations are constitutively relevant to organism behaviour if and only if (and because) they are causal relations that link the working parts that are constitutively relevant to organism behaviour. In this paper, I argue that the causal-linking account is inadequate because it neglects the constitutive relevance of anatomical relations that organise the working parts of a behaving organism. I demonstrate this by considering a case study where the anatomical organisation of the barn owl (Tyto alba) is constitutively relevant to their mechanism for sound localization. The anatomical organisation of this mechanism is best understood as the back-and-forth flow of task information across 7 “levels of anatomy” (a notion that I distinguish from levels of mechanism). A further implication, I conclude, is that at least some of the interlevel structure of neuroscientific explanation is accounted for by levels of anatomy, not levels of mechanism. (shrink)

Multiple realizability (MR) is traditionally conceived of as the feature of computational systems, and has been used to argue for irreducibility of higher-level theories. I will show that there are several ways a computational system may be seen to display MR. These ways correspond to (at least) five ways one can conceive of the function of the physical computational system. However, they do not match common intuitions about MR. I show that MR is deeply interest-related, and for this reason, difficult (...) to pin down exactly. I claim that MR is of little importance for defending computationalism, and argue that it should rather appeal to organizational invariance or substrate neutrality of computation, which are much more intuitive but cannot support strong antireductionist arguments. (shrink)

These preprints were automatically compiled into a PDF from the collection of papers deposited in PhilSci-Archive in conjunction with the PSA 2018.

Natural selection is a general process that operates in different populations. To characterise natural selection as a mechanism within the framework of the new mechanistic philosophy, it is required to identify a pertinent phenomenon for which natural selection is responsible. Firstly, every case identified by evolutionary biologists as instances of natural selection must align with this mechanistic characterisation. Secondly, natural selection should genuinely be responsible for the attributed phenomenon. While philosophers often posit producing adaptation as the quintessential phenomenon, Pérez-González and (...) Luque challenge this perspective, contending that not all instances of natural selection are cases where natural selection produces adaptation. This paper further supports Pérez-González and Luque’s objection and demonstrates that natural selection is also not responsible for the increased frequency of traits with a greater expected number of offspring. Furthermore, the paper argues that even if there is a phenomenon that allows for the mechanistic characterisation of natural selection to encompass all instances, it is improbable that natural selection assumes responsibility for it. Consequently, characterising natural selection as a mechanism emerges as an implausible stance. (shrink)

In his chapter in this volume, Christopher Pincock develops an argument for scientific realism based on scientific understanding, and he argues that Giere’s (2006) and my (2017, 2020) commitment to the context-dependence of scientific understanding or knowledge renders our views unable to account for an essential step in how scientists come to know. Meanwhile, in my chapter in this volume, I motivate a view that I call "causal pattern realism." In this response to Pincock's chapter, I will sketch a revised (...) version of Pincock’s argument for realism that is consistent with causal pattern realism. Then I will respond to Pincock’s concern that the context-dependence of understanding on my view would interfere with the scientific community’s ability to extrapolate from specific experimental and observational contexts as needed to develop knowledge. My goal is not to convince anyone to be a causal pattern realist but rather to create the space for such a view, taking into account the concerns motivating Pincock. (shrink)

The type-level abstraction is a formal way to represent molecular structures in biological practice. Graphical representations of molecular structures of biological objects are also used to identify functional processes of things. This paper will reveal that category theory is a formal mathematical language not only to visualize molecular structures of biological objects as type-level abstraction formally but also to understand how to infer biological functions from the molecular structures of biological objects. Category theory is a toolkit to understand biological knowledge (...) at the type-level formally, not individual token-level, as well as typical heuristic strategies in molecular biology. (shrink)

In a recent paper, Erasmus et al. (2021) defend the idea that the ambiguity of the term “explanation” in explainable AI (XAI) can be solved by adopting any of four different extant accounts of explanation in the philosophy of science: the Deductive Nomological, Inductive Statistical, Causal Mechanical, and New Mechanist models. In this chapter, I show that the authors’ claim that these accounts can be applied to deep neural networks as they would to any natural phenomenon is mistaken. I also (...) provide a more general argument as to why the notion of explainability as it is currently used in the XAI literature bears little resemblance to the traditional concept of scientific explanation. It would be more fruitful to use the label “understandable AI” to avoid the confusion that surrounds the goal and purposes of XAI. In the second half of the chapter, I argue for a pragmatic conception of understanding that is better suited to play the central role attributed to explanation in XAI. Following De Regt (2017) and Kuorikoski and Ylikoski (2015), the conditions of satisfaction for understanding an ML system are fleshed out in terms of an agent’s success in using the system. (shrink)

Scientists cannot devise theories, construct models, propose explanations, make predictions, or even carry out observations, without first classifying their subject matter. The goal of scientific taxonomy is to come up with classification schemes that conform to nature's own. Another way of putting this is that science aims to devise categories that correspond to 'natural kinds.' The interest in ascertaining the real kinds of things in nature is as old as philosophy itself, but it takes on a different guise when one (...) adopts a naturalist stance in philosophy, that is when one looks closely at scientific practice and takes it as a guide for identifying natural kinds and investigating their general features. This Element surveys existing philosophical accounts of natural kinds, defends a naturalist alternative, and applies it to case studies in a diverse set of sciences. This title is also available as Open Access on Cambridge Core. (shrink)

According to new mechanists, mechanisms explain how specific biological phenomena are produced. New mechanists have had little to say about how mechanisms relate to the organism in which they reside. A key feature of organisms, emphasized by the autonomy tradition, is that organisms maintain themselves. To do this, they rely on mechanisms. But mechanisms must be controlled so that they produce the phenomena for which they are responsible when and in the manner needed by the organism. To account for how (...) they are controlled, we characterize mechanisms as sets of constraints on the flow of free energy. Some constraints are flexible and can be acted on by other mechanisms, control mechanisms, that utilize information procured from the organism and its environment to alter the flexible constraints in other mechanisms so that they produce phenomena appropriate to the circumstances. We further show that control mechanisms in living organisms are organized heterarchically—control is carried out primarily by local controllers that integrate information they acquire as well as that which they procure from other control mechanisms. The result is not a hierarchy of control but an integrated network of control mechanisms that has been crafted over the course of evolution. (shrink)

We lay groundwork for applying ethnographic methods in philosophy of science. We frame our analysis in terms of two tasks: to identify the benefits of an ethnographic approach in philosophy of science and to structure an ethnographic approach for philosophical investigation best adapted to provide information relevant to philosophical interests and epistemic values. To this end, we advocate for a purpose-guided form of cognitive ethnography that mediates between the explanatory and normative interests of philosophy of science, while maintaining openness and (...) independence when framing such an investigation to achieve robust unbiased results. (shrink)

A crucial question for a process view of life is how to identify a process and how to follow it through time. The genidentity view can contribute decisively to this project. It says that the identity through time of an entity X is given by a well-identified series of continuous states of affairs. Genidentity helps address the problem of diachronic identity in the living world. This chapter describes the centrality of the concept of genidentity for David Hull and proposes an (...) extension of Hull’s view to the ubiquitous phenomenon of symbiosis. Finally, using immunology as a key example, it shows that the genidentity view suggests that the main interest of a process approach is epistemological rather than ontological and that its principal claim is one of priority, namely that processes precede and define things, and not vice versa. (shrink)

This chapter argues that scientific and philosophical progress in our understanding of the living world requires that we abandon a metaphysics of things in favour of one centred on processes. We identify three main empirical motivations for adopting a process ontology in biology: metabolic turnover, life cycles, and ecological interdependence. We show how taking a processual stance in the philosophy of biology enables us to ground existing critiques of essentialism, reductionism, and mechanicism, all of which have traditionally been associated with (...) substance ontology. We illustrate the consequences of embracing an ontology of processes in biology by considering some of its implications for physiology, genetics, evolution, and medicine. And we attempt to locate the subsequent chapters of the book in relation to the position we defend. (shrink)

The terms “perspectivism” and “perspectivalism” have been the focus of an intense philosophical discussion with important repercussions for the debate about the role of mechanisms in scientific explanations. However, leading exponents of the new mechanistic philosophy have conceded more than was necessary to the radically subjectivistic perspectivalism, and fell into the opposite error, by retaining not negligible residues of objectivistic views about mechanisms. In order to remove this vacillation between the subjective-cultural and the objective-natural sides of mechanisms, we shall raise (...) the question about theory-ladenness over again and interpret it in its connection with the technical–experimental nature of scientific knowledge, as affirming the perspectival character of scientific knowledge: It is because of the character at once theory-laden and practice-laden, i.e. technique-laden, of our putting questions to nature that empirical reality must be investigated from particular perspectives: nature can be known scientifically only from a potentially infinite number of perspectives or theoretical points of view, concretely exemplified by mechanisms or experimental ‘machines’ that allow specific access to specific aspects of sensible reality. (shrink)

Computational perspectivalism has been recently proposed as an alternative to mainstream accounts of physical computation, and especially to the teleologically-based mechanistic view. It takes physical computation to be partly dependent on explanatory perspectives and eschews appeal to teleology in helping individuate computational systems. I assess several varieties of computational perspectivalism, showing that they either collapse into existing non-perspectival views or end up with unsatisfactory or implausible accounts of physical computation. Computational perspectivalism fails, therefore, to be a compelling alternative to perspective-independent (...) theories of computation in physical systems. I conclude that a teleologically-based, non-perspectival mechanistic account of physical computation is to be preferred. 1Introduction 2The Mechanistic View of Computation 2.1Teleological functions and meeting the desiderata 3Varieties of Perspectivalism 4Computational Perspectivalism 4.1Computational perspectivalism and pancomputationalism 4.2Computational perspectivalism and miscomputation 5The Varieties of Computational Perspectivalism Assessed 5.1Innocuous computational perspectivalism 5.2Non-innocuous computational perspectivalism 5.2.1Computational instrumentalism 5.2.2Ontic perspectivalism 6Concluding Remarks. (shrink)

Any successful account of the metaphysics of mechanistic causation must satisfy at least five key desiderata. In this article, I lay out these five desiderata and explain why existing accounts of the metaphysics of mechanistic causation fail to satisfy them. I then present an alternative account that does satisfy the five desiderata. According to this alternative account, we must resort to a type of ontological entity that is new to metaphysics, but not to science: constraints. In this article, I explain (...) how a constraints-based metaphysics fits best with the emerging consensus on the nature of mechanistic explanation. 1Introduction2Renormalizability2.1The first two desiderata: Intrinsicness and productivity2.2The third desideratum: Scientific validity or non-mysteriousness2.3The fourth desideratum: Directionality2.4The fifth desideratum: Perspectival nature of mechanisms3Constraints and Causation3.1Multi-perspectival realism and causal structure3.2Causal structure as laws3.3Causal structures in analytical mechanics: Constraints3.4A metaphysics inspired by analytical mechanics: Constraints as ontologically primitive modal structures4Constraints and Mechanistic Causal Powers 4.1Inter- versus intra-perspectival categories4.2Mechanistic causal powers are grounded by constraints4.3Intrinsicness and constraints4.4Constraints and productiveness4.5Constraints and directionality5Conclusion. (shrink)

Sober and Huemer have independently argued that simplicity has no place in evaluating philosophical views. In particular, they have argued that the best rationales for scientists to appeal to simplicity in judging between rival theories fail to carry over to philosophers judging between rival philosophical accounts. This paper disagrees with Sober and Huemer. It argues that two rationales for scientific appeals to simplicity equally well underwrite appeals to simplicity when philosophers evaluate rival rational reconstructions of some social normative practice. These (...) two rationales are shown to apply to two philosophical appeals to simplicity: in Quine’s argument against analyticity and in an argument against pluralism in accounts of scientific explanation. Some factors are identified that influence how much weight simplicity should carry in these and other philosophical cases. Simplicity’s legitimate role in evaluating rival rational reconstructions suggests that simplicity will also turn out to be justly relevant to ontological investigations. (shrink)

Big data biology—bioinformatics, computational biology, systems biology (including ‘omics’), and synthetic biology—raises a number of issues for the philosophy of science. This article deals with several such: Is data-intensive biology a new kind of science, presumably post-reductionistic? To what extent is big data biology data-driven? Can data ‘speak for themselves?’ I discuss these issues by way of a reflection on Carl Woese’s worry that “a society that permits biology to become an engineering discipline, that allows that science to slip into (...) the role of changing the living world without trying to understand it, is a danger to itself.” And I argue that scientific perspectivism, a philosophical stance represented prominently by Giere, Van Fraassen, and Wimsatt, according to which science cannot as a matter of principle transcend our human perspective, provides the best resources currently at our disposal to tackle many of the philosophical issues implied in the modeling of complex, multilevel/multiscale phenomena. (shrink)

Many debates in philosophy focus on whether folk or scientific psychological notions pick out cognitive natural kinds. Examples include memory, emotions and concepts. A potentially interesting type of kind is: kinds of mental representations (as opposed, for example, to kinds of psychological faculties). In this chapter we outline a proposal for a theory of representational kinds in cognitive science. We argue that the explanatory role of representational kinds in scientific theories, in conjunction with a mainstream approach to explanation in cognitive (...) science, suggest that representational kinds are multi-level. This is to say that representational kinds’ properties cluster at different levels of explanation and allow for intra- and inter-level projections. (shrink)

Philosophical analyses of causation have been centred on the question of what causation is. More precisely speaking, philosophers tend to address four different issues: metaphysical (what is causation out there?), epistemological (how can a causal claim be established and assessed?), conceptual (what does the word ‘cause’ mean?), and methodological (what methods ought one to use in order to establish and assess causal claims?). This chapter argues that the practical issue of causation (what is a causal claim for in practice?) is (...) highly relevant to the metaphysical, epistemological, conceptual, and methodological issues of causation. Any philosophical enquiry into causation without an examination of this practical issue is incomplete. In other words, a promising approach to causation ought to take all of the metaphysical, epistemological, conceptual, methodological, and practical issues into account. (shrink)

Are causal explanations (e.g., “she switched careers because of the COVID pandemic”) treated differently from the corresponding claims that one factor caused another (e.g., “the COVID pandemic caused her to switch careers”)? We examined whether explanatory and causal claims diverge in their responsiveness to two different types of information: covariation strength and mechanism information. We report five experiments with 1,730 participants total, showing that compared to judgments of causal strength, explanatory judgments tend to bemoresensitive to mechanism andlesssensitive to covariation – (...) even though explanatory judgments respond to both types of information. We also report exploratory comparisons to judgments of understanding, and discuss implications of our findings for theories of explanation, understanding, and causal attribution. These findings shed light on the potentially unique role of explanation in cognition. (shrink)