Explanation

[EDIT: This book will be published open access. Check back around April 2024 to access the entire book.] One central aim of science is to provide explanations of natural phenomena. What role(s) does mathematics play in achieving this aim? How does mathematics contribute to the explanatory power of science? Rules to Infinity defends the thesis, common though perhaps inchoate among many members of the Vienna Circle, that mathematics contributes to the explanatory power of science by expressing conceptual rules, rules which (...) allow the transformation of empirical descriptions. Mathematics should not be thought of as describing, in any substantive sense, an abstract realm of eternal mathematical objects, as traditional platonists have thought. In Rules to Infinity, this view, which I call mathematical normativism, is updated with contemporary philosophical tools, and it is argued that normativism is compatible with mainstream semantic theory. This allows the normativist to accept that there are mathematical truths, while resisting the platonistic idea that there exist abstract mathematical objects that explain such truths. Furthermore, Rules to Infinity defends a particular account of the distinction between scientific explanations that are in some sense distinctively mathematical – those that explain natural phenomena in some uniquely mathematical way – and those that are only standardly mathematical, and it lays out desiderata for any account of this distinction. Normativism is compared with other prominent views in the philosophy of mathematics such as neo-Fregeanism, fictionalism, conventionalism, and structuralism. Rules to Infinity serves as an entry point into debates at the forefront of philosophy of science and mathematics, and it defends novel positions in these debates. (shrink)

I introduce an argument for Platonism based on intra-mathematical explanation: the explanation of one mathematical fact by another. The argument is important for two reasons. First, if the argument succeeds then it provides a basis for Platonism that does not proceed via standard indispensability considerations. Second, if the argument fails it can only do so for one of three reasons: either because there are no intra-mathematical explanations, or because not all explanations are backed by dependence relations, or because some form (...) of noneism-the view according to which non-existent entities possess properties and stand in relations-is true. The argument thus forces a choice between nominalism without noneism, intra-mathematical explanation and a backing conception of explanation. You can have any two, but not all three. (shrink)

Modern life sciences research is increasingly relying on artificial intelligence (AI) approaches to model biological systems, primarily centered around the use of machine learning (ML) models. Although ML is undeniably useful for identifying patterns in large, complex data sets, its widespread application in biological sciences represents a significant deviation from traditional methods of scientific inquiry. As such, the interplay between these models and scientific understanding in biology is a topic with important implications for the future of scientific research, yet it (...) is a subject that has received little attention. Here, we draw from an epistemological toolkit to contextualize recent applications of ML in biological sciences under modern philosophical theories of understanding, identifying general principles that can guide the design and application of ML systems to model biological phenomena and advance scientific knowledge. We propose that conceptions of scientific understanding as information compression, qualitative intelligibility, and dependency relation modelling provide a useful framework for interpreting ML-mediated understanding of biological systems. Through a detailed analysis of two key application areas of ML in modern biological research – protein structure prediction and single cell RNA-sequencing – we explore how these features have thus far enabled ML systems to advance scientific understanding of their target phenomena, how they may guide the development of future ML models, and the key obstacles that remain in preventing ML from achieving its potential as a tool for biological discovery. Consideration of the epistemological features of ML applications in biology will improve the prospects of these methods to solve important problems and advance scientific understanding of living systems. (shrink)

The ontic conception of explanation is predicated on the proposition that “explanation is a relation between real objects in the world” and hence, according to this approach, scientific explanation cannot take place absent such a premise. Despite the fact that critics have emphasized several drawbacks of the ontic conception, as for example its inability to address the so-called “abstract explanations”, the debate is not settled and the ontic view can claim to capture cases of explanation that are non-abstract, such as (...) causal relations between events. However, by eliminating the distinction between abstract and non-abstract explanations, it follows that ontic and epistemic proposals can no longer contend to capture different cases of explanation and either all are captured by the ontic view or all are captured by the epistemic view. On closer inspection, it turns out that the ontic view deals with events that fall outside the scientists’ scope of observation and that it does not accommodate common instances of explanation such as explanations from false propositions and hence it cannot establish itself as the dominant philosophical stance with respect to explanation. On the contrary, the epistemic conception does account for almost all episodes of explanation and can be described as a relation between representations, whereby the explanans transmit information to the explanandum and that this information can come, dependent on context, in the form of any of the available theories of explanation (law-like, unificatory, causal and non-causal). The range of application of the ontic view thus is severely restricted to trivial cases of explanation that come through direct observation of the events involved in an explanation and explanation is to be mostly conceived epistemically. (shrink)

In this article I examine several related views expressed by Robin Hendry concerning molecular structure, emergence and chemical bonding. There is a long-standing problem in the philosophy of chemistry arising from the fact that molecular structure cannot be strictly derived from quantum mechanics. Two or more compounds which share a molecular formula, but which differ with respect to their structures, have identical Hamiltonian operators within the quantum mechanical formalism. As a consequence, the properties of all such isomers yield precisely the (...) same calculated quantities such as their energies, dipole moments etc. The only means through which the difference between the isomers can be recovered is to build their structures into the quantum mechanical calculations, something that is carried out by the application of the Born-Oppenheimer approximation. Consequently, it has been argued by many authors that molecular structure is written in ‘by hand’ rather than derived. Robin Hendry is one such author, but he goes a great deal further by proposing that this situation implies the existence of emergence and downward causation. In the current article I argue that there are alternative explanations which render emergence and downward causation redundant. Such an alternative lies in the notion of quantum decoherence and the appeal to work in the foundations of physics, which posits that the various isomers exist as a superposition until their wavefunctions are collapsed either by observation or by interacting with their environment. Hendry also alludes to a debate among chemists as to whether chemical bonds are real or not, in the sense of directional connections between two or more nuclei in any given molecule. I reject this view and propose that the structural and energetic views of chemical bonding, that have been discussed by some philosophers of chemistry including Hendry, do not refer to any essential ontological differences. I agree that chemists view bonding in a more realistic fashion and may consider bonds to be in some senses real, while physicists may consider bonding in more abstract energetic terms. However, I do not believe that such differences in scientific practice and attitudes should be considered to offer a window as to the ontological status of bonding or whether bonding is real. Finally, I discuss the kinetic energy school of chemical bonding which would seem to challenge any notion of bonds as directional entities, since bonding is no longer regarded as being primarily due to the build-up of electron density between nuclei. (shrink)

It is well-known that the global structure of every space-time model for relativistic cosmology is observationally underdetermined. In order to alleviate the severity of this underdetermination, it has been proposed that we adopt the Cosmological Principle because the Principle restricts our attention to a distinguished class of space-time models (spatially homogeneous and isotropic models). I argue that, even assuming the Cosmological Principle, the topology of space remains observationally underdetermined. Nonetheless, I argue that we can muster reasons to prefer various topological (...) properties over others. In particular, I favor the adoption of multiply connected universe models on grounds of (i) simplicity, (ii) Machian considerations, and (iii) explanatory power. We are able to appeal to such grounds because multiply connected topologies open up the possibility of finite universe models (consistent with our best data), which in turn avoid thorny issues concerning the postulation of an actually infinite universe. (shrink)

The role of evolutionary theory at the origin of life is an extensively debated topic. The origin and early development of life is usually separated into a prebiotic phase and a protocellular phase, ultimately leading to the Last Universal Common Ancestor. Most likely, the Last Universal Common Ancestor was subject to Darwinian evolution, but the question remains to what extent Darwinian evolution applies to the prebiotic and protocellular phases. In this review, we reflect on the current status of evolutionary theory (...) in origins of life research by bringing together philosophy of science, evolutionary biology, and empirical research in the origins field. We explore the various ways in which evolutionary theory has been extended beyond biology; we look at how these extensions apply to the prebiotic development of (proto)metabolism; and we investigate how the terminology from evolutionary theory is currently being employed in state-of-the-art origins of life research. In doing so, we identify some of the current obstacles to an evolutionary account of the origins of life, as well as open up new avenues of research. (shrink)

This paper studies the epistemic failures to reach understanding in relation to scientific explanations. We make a distinction between genuine understanding and its negative phenomena—lack of understanding and misunderstanding. We define explanatory understanding as inclusive as possible, as the epistemic success that depends on abilities, skills, and correct explanations. This success, we add, is often supplemented by specific positive phenomenology which plays a part in forming epistemic inclinations—tendencies to receive an insight from familiar types of explanations. We define lack of (...) understanding as the epistemic failure that results from a lack of an explanation or from an incorrect one. This can occur due to insufficient abilities and skills, or to fallacious explanatory information. Finally, we characterize misunderstanding by cases where one’s epistemic inclinations do not align with an otherwise correct explanation. We suggest that it leads to potential debates about the explanatory power of different explanatory strategies. We further illustrate this idea with a short meta-philosophical study on the current debates about distinctively mathematical explanations. (shrink)

This essay discusses Peter Langland-Hassan's approach to "explaining imagination" as it plays out in his recent book of that title. Langland-Hassan offers a theory of “attitude imagining” that avoids positing what he calls a “sui generis cognitive attitude.” This theory attempts to explain things like pretend play, hypothetical reasoning, and cognition of fiction; to explain them using only (what he calls) more “basic” mental states like beliefs and desires; and thus to explain them without positing a distinct cognitive attitude of (...) imagining, as many theorists do (including me). In other words, “attitude imagining,” for Langland-Hassan, is whatever explains those things (except for a distinct cognitive attitude of imagining itself). Despite the theoretical interest of this approach, I argue it is ontologically pennywise and pound foolish: for a slight savings in ontological complexity it dramatically reduces explanatory power. (shrink)

Epistemic pluralists in the philosophy of science often argue that different epistemic perspectives in science are equally warranted. Sandra Mitchell – with her Integrative Pluralism (IP) – has notably advocated for this kind of epistemic pluralism. A problem arises for Mitchell however because she also wants to be an epistemological pluralist. She claims that, not only are different epistemic perspectives in science equally warranted in different contexts, but different understandings of these epistemic perspectives in science are also equally warranted in (...) different contexts. The problem is that Mitchell argues that her understanding of epistemic perspectives in science (IP) is the correct one, and it is dilemmic to then claim that there is more than one such understanding. As solution, I suggest that we abandon epistemological pluralism and instead follow Feyerabend in being opportunistic pluralists. We can adopt pluralism as a short-term strategy in the pursuit of a long-term unitary goal. This unitary goal is what philosophers of understanding call objectual understanding, the kind of understanding that Integrative Pluralism tacitly aspires to anyway. (shrink)

Ross Cameron (2022) argues that metaphysical infinitists should reject the generally accepted idea that metaphysical determination relations back metaphysical explanations. Otherwise it won’t be possible for them to come up with successful explanations for the existence of dependent entities in non-wellfounded chains of dependence. I argue that his argument suffers from what he calls the finitist dogma, although indirectly so. However, there is a better way of motivating Cameron’s conclusion. Assuming Cameron’s principle of Essence, explanations for the existence of dependent (...) entities turn out to be circular if determination relations back explanations. This latter argument provides a stronger case as it puts the foundationalist under significant pressure, besides putting the infinitist under some pressure, to deny the idea that determination relations back explanations. (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)

The observational-theoretical distinction has played a central role in the philosophy of science from logical empiricism onwards. Developments within the discipline have shown that such a distinction hides two non-identical distinctions: observational vs. non-observational and theoretical vs. non-theoretical. Likewise, metatheoretical structuralism proposed a more sophisticated treatment of theoricity in terms of the operational dependence or independence of concepts from the theories in which they appear. Despite this remarkable sophistication, it is still generally accepted that the distinction between theoretical and non-theoretical (...) concepts coincides with the explanatory vs. non-explanatory and testing vs. non-testing distinctions. Ginnobili and Carman argued for the independence between theoricity and explanation. In this paper we will focus on testing and argue for its independence from both theoricity and explanation. To do so, we propose an account of theory testing based on the framework of metatheoretical structuralism and apply it to natural selection theory and cladistics. (shrink)

The chapter discusses the issue of how we may achieve knowledge of essence. It offers a critical survey of the main theories of knowledge of essence that have been proposed within contemporary debates, particularly by Lowe, Hale, Oderberg, Elder, and Kment.

I argue that ML models used in science function as highly idealized toy models. If we treat ML models as a type of highly idealized toy model, then we can deploy standard representational and epistemic strategies from the toy model literature to explain why ML models can still provide epistemic success despite their lack of similarity to their targets.

Most psychological research aims to uncover generalizations about the mind that hold across subjects. Philosophical discussions of scientific explanation have focused on such generalizations, but in doing so, have often overlooked an important phenomenon: variation. Variation is ubiquitous in psychology and many other domains, and an important target of explanation in its own right. Here I characterize explananda that concern individual differences and formulate an account of what it takes to explain them. I argue that the notion of actual difference (...) making, the only causal concept in the literature that explicitly addresses variation, cannot be used to ground such an account. Instead, I propose a view on which explaining individual differences involves identifying causes that could be intervened on to reduce the variability in the population. This account provides criteria of success for explaining variation and deepens our understanding of causal explanation. (shrink)

Social phenomena—quite like mental states in the philosophy of mind—are often regarded as potential troublemakers from the start, particularly if they are approached with certain explanatory commitments, such as naturalism or social individualism, already in place. In this paper, we argue that such explanatory constraints should be at least initially bracketed if we are to arrive at an adequate non-biased description of social phenomena. Legitimate explanatory projects, or so we maintain, such as those of making the social world fit within (...) the natural world with the help of, e.g., collective intentionality, social individualism, and the like, should neither exclude nor influence the prior description of social phenomena. Just as we need a description of the mental that is not biased, for example, by (anti)physicalist constraints, we need a description of the social that is not biased, for example, by (anti)individualist or (anti)naturalist commitments. Descriptive social ontology, as we shall conceive of it, is not incompatible with the adoption of explanatory frameworks in social ontology; rather, the descriptive task, according to our conception, ought to be recognized as prior to the explanatory project in the order of inquiry. If social phenomena are, for example, to be reduced to nonsocial (e.g., psychological or physical) phenomena, we need first to understand clearly what the social candidates for the reduction in question are. While such descriptive or naive approaches have been influential in general metaphysics (see Fine 2017), they have so far not been prominent in analytic social ontology (though things are different outside of analytic philosophy, see esp. Reinach (1913). In what follows, we shall outline the contours of a descriptive approach by arguing, first, that description and explanation need to be distinguished as two distinct ways of engaging with social phenomena. Secondly, we defend the claim that the descriptive project ought to be regarded as prior to the explanatory project in the order of inquiry. We begin, in Section 2, by considering two different ways of engaging with mental phenomena: a descriptive approach taken by descriptive psychology and an explanatory approach utilized in analytic philosophy of mind. We take these two ways of approaching the study of the mind to be analogous to the distinction we want to draw in social ontology between a descriptive and an explanatory approach to the study of social phenomena. We consider next, in Section 3, how our approach compares to neighboring perspectives that are familiar to us from general metaphysics and philosophy more broadly, such as Aristotle’s emphasis on “saving the appearances”, Strawson’s distinction between descriptive and revisionary metaphysics, as well as Fine’s contrast between na¨ive and foundational metaphysics. In Section 4, we apply the proposed descriptive/explanatory distinction to the domain of social ontology and argue that descriptive social ontology ought to take precedence in the order of inquiry over explanatory social ontology. Finally, in Section 5, we consider and respond to several objections to which our account might seem to be susceptible. (shrink)

I argue that notions of relative fundamentality need to be invoked if there is to be something substantive at stake in the debate between proponents of Harvey Brown's dynamical approach to relativity and defenders of a more traditional interpretation of spacetime. I will review some problems that stand in the way of the advocate of the dynamical approach making good on their claim that dynamical symmetries are more fundamental than spacetime symmetries.

This paper presents a novel argument against one theoretically attractive form of panpsychism. I argue that “idealist panpsychism” is false since it cannot account for spacetime’s structure. Idealist panpsychists posit that fundamental reality is purely experiential. Moreover, they posit that the consciousness at the fundamental level metaphysically grounds and explains both the facts of physics and the facts of human consciousness. I argue that if idealist panpsychism is true, human consciousness and the consciousness at the fundamental level will have the (...) same metrical structure. However, as I demonstrate, human consciousness does not exhibit the same metrical structure as spacetime. Consequently, the idealist panpsychist faces an explanatory gap between the fundamental consciousness she posits and spacetime. Idealist panpsychism is incompatible with the existence of such an explanatory gap. Thus, idealist panpsychists must close this explanatory gap (which I argue they lack the resources to do), or idealist panpsychism is false. (shrink)

The concept of causality is central to the assessment of numerous related metaphysical and epistemic positions, in Hegel and elsewhere. The present essay tries 1) to understand Hegel’s critique of the merely categorically understood concept of causality; 2) to uncover the theoretical structure that must accompany the categorical concept of causality in order to avoid the problems mentioned above; and 3) to argue that such a theory of causality has a fundamental function for Hegel’s conception of objectivity.

Cancer biology features the ascription of normal functions to parts of cancers. At least some ascriptions of function in cancer biology track local normality of parts within the global abnormality of the aberration to which those parts belong. That is, cancer biologists identify as functions activities that, in some sense, parts of cancers are supposed to perform, despite cancers themselves having no purpose. The present paper provides a theory to accommodate these normal function ascriptions—I call it the Modeling Account of (...) Normal Function (MA). MA comprises two claims. First, normal functions are activities whose performance by the function-bearing part contributes to the self-maintenance of the whole system and, thereby, results in the continued presence of that part. Second, MA holds that models of system-level activities that are (partly) constitutive of self-maintenance are improved by including a representation of the relevant function-bearing part and by making reference to the activity/activities that part performs which contribute(s) to those system-level activities. I contrast MA with two other accounts that seek to explicate the ascription of normal functions in biology, namely, the organizational account and the selected effects account. Both struggle to extend to cancer biology. However, I offer ecumenical readings which allow them to recover some ascriptions of normal function to parts of cancers. So, though I contend that MA excels in this respect, the purpose of this paper is served if it provides materials for bridging the gap between cancer biology, philosophy of cancer, and the literature on function. (shrink)

La tesis principal de este trabajo es que los modelos estadísticos facilitan explicaciones acerca de los errores que pueden cometer nuestros procedimientos de inferencia de datos a fenómenos, en el contexto de la estadística clásica o frecuentista. La explicación del error es una operación que, a su vez, ayuda a evitarlo en donde es evitable e intolerable; tolerarlo donde es inevitable y tolerable; y suspender el juicio donde es inevitable e intolerable. Todas estas operaciones son elementos de una práctica generadora (...) de evidencia confiable. Se ilustra esta tesis con el modelo lineal en econometría, el estimador de mínimos cuadrados ordinarios, el estimador y modelo de variables instrumentales y con los conceptos relacionados con las pruebas de hipótesis. Se pone especial énfasis en las propiedades de insesgadez, consistencia y precisión como caracterizaciones del tipo de error que se puede cometer usándo un estimador. Se sostiene que los modelos explican identificando patrones de dependencia contrafáctica entre características del mecanismo estocástico representadas por el modelo y características de los procedimientos inferenciales. (shrink)

Este trabalho tem como principal objetivo apresentar uma abordagem lógico-formal capaz de apreender alguns aspectos do raciocínio abdutivo – o raciocínio responsável pela criação de hipóteses explicativas para fatos surpreendentes -, mediante tanto as noções filosófico-conceituais da canônica abdução peirceana quanto as de explicação científica. No caso desta última, procurarei evidenciar, inicialmente, pontos de contraste entre as concepções de explicação científica de Aristóteles e de Carl Hempel, a fim de elucidar, de modo mais satisfatório, em que medida, de fato, teorias (...) e hipóteses “explicam” algo. Apresentarei, também, um modo de tratar hipóteses explicativas contraditórias, por meio do operador de consistência ○ – próprio da lógica paraconsistente mbC -, o qual amplia o poder expressivo da linguagem-objeto subjacente ao sistema lógico, bem como apresentarei uma abordagem formal alternativa do raciocínio abdutivo pensado como dinâmica de mudança de crenças, especificamente por intermédio da lógica de revisão de crenças AGM. (shrink)

This chapter responds to Michael Tamir and Elay Shech’s chapter “Understanding from Deep Learning Models in Context.”.

In his recent book, John Norton has created a theory of inference to the best explanation, within the context of his "material theory of induction". I apply it to the problem of scientific explanations that are false: if we want the theories in our explanations to be true, then why do historians and scientists often say that false theories explained phenomena? I also defend Norton's theory against some possible objections.

I explore the process of changes in the observability of entities and objects in science and how such changes impact two key issues in the scientific realism debate: the claim that predictively successful elements of past science are retained in current scientific theories, and the inductive defense of a specific version of inference to the best explanation with respect to unobservables. I provide a case-study of the discovery of radium by Marie Curie in order to show that the observability of (...) some entities can change and that such changes are relevant for arguments seeking to establish the reliability of success-to-truth inferences with respect to unobservables. (shrink)

Thinking about metaphysical problems in terms of grounding has its uses, but those uses are limited. This paper argues against attempts to see issues of grounding as having a central and organising role in metaphysical inquiry. After arguing that grounding does some useful work, this paper will argue that grounding is neither the central tool for understanding explanation in metaphysics, nor defines the subject matter of metaphysics. Instead, grounding tracks only some of the metaphysical explanations we should be looking for, (...) and is only one among many of the topics metaphysics aims to address. (shrink)

This paper explores a novel notion of self-explanation that combines ideas from two sources: the tripartite account of explanation, according to which a proposition can help explain another either in the capacity of a reason why the latter obtains or in the capacity of an explanatory link, and the notion of an empty-base explanation, which generalizes the ideas of explanation by zero-grounding and explanation by status. After having introduced these ideas and the novel notion of self-explanation, I argue that the (...) latter has the potential to resist extant arguments against the possibility of self-explanation. In the remainder of the paper, I discuss candidates for such self-explanatory propositions and suggest possible applications for Humeanism about laws of nature, the debate on the grounds of ground, the rationalist tradition, and philosophical theology. (shrink)

There is longstanding interpretive dispute between commentators over Spinoza’s commitment to necessitarianism, the doctrine that all things are metaphysically necessary and none are contingent. Those who affirm Spinoza’s commitment to the doctrine adhere to the necessitarian interpretation whereas those who deny it adhere to what I call the semi-necessitarian interpretation. As things stand, the disagreement between commentators appears to have reached an impasse. Notwithstanding, there seems to be no disagreement among commentators on the question of necessitarianism’s philosophical plausibility as a (...) metaphysical view: the doctrine is wildly untenable. This consensus view is more relevant to the interpretive debate than few have recognized, since leading semi-necessitarian commentators take the doctrine’s alleged absurdity to be one of the most compelling reasons (if not the most compelling reason) to prefer their reading over the necessitarian interpretation: for, as a matter of methodological principle, great philosophers like Spinoza should not be ascribed ridiculous views in the absence of better evidence. -/- This dissertation seeks to defend Spinoza’s commitment to necessitarianism on both the interpretive and philosophical fronts. I argue not only that the necessitarian interpretation of Spinoza is more plausible than the semi-necessitarian interpretation on textual grounds, but that Spinoza’s necessitarianism is a serviceable philosophical view whose tenability has been almost entirely overlooked and perfunctorily rejected. The principal basis upon which I build this defense is Spinoza’s rich and fascinating view of essences—what I simply refer to as his essentialism. Spinoza’s essentialism forms the bedrock of his metaphysics and is significant not least because it underlies and informs doctrines like his necessitarianism. Spinoza’s essentialism supplies resources to answer not just interpretive problems associated with necessitarianism, but philosophical challenges to the plausibility of the doctrine. My defense of Spinoza’s necessitarianism on philosophical grounds also offers a novel way of getting past much of the current interpretive impasse among commentators by effectively undercutting the methodological motivation for the semi-necessitarian reading. In addition to my defense on the interpretive front, then, my defense on the philosophical front provides supplementary reason to a fortiori favor the necessitarian reading of Spinoza. (shrink)

A commissioned 3-volume (800 pages) in-depth introduction to the philosophy of science, peer-reviewed by 11 specialists. (In Hebrew).

I argue that Émilie Du Châtelet breaks with Christian Wolff regarding the scope and epistemological content of the principle of sufficient reason, despite his influence on her basic ontology and their agreement that the principle of sufficient reason has foundational importance. These differences have decisive consequences for the ways in which Du Châtelet and Wolff conceive of science.

This article considers two important traditions concerning the chemical elements. The first is the meaning of the term “element” including the distinctions between element as basic substance, as simple substance and as combined simple substance. In addition to briefly tracing the historical development of these distinctions, I make comments on the recent attempts to clarify the fundamental notion of element as basic substance for which I believe the term “element” is best reserved. This discussion has focused on the writings of (...) Fritz Paneth which are here analyzed from a new perspective. The other tradition concerns the reduction of chemistry to quantum mechanics and an understanding of chemical elements through their microscopic components such as protons, neutrons and electrons. I claim that the use of electronic configurations has still not yet settled the question of the placement of several elements and discuss an alternative criterion based on maximizing triads of elements. I also point out another possible limitation to the reductive approach, namely the failure, up to now, to obtain a derivation of the Madelung rule. Mention is made of some recent similarity studies which could be used to clarify the nature of ‘elements’. Although it has been suggested that the notion of element as basic substance should be considered in terms of fundamental particles like protons and electrons, I resist this move and conclude that the quantum mechanical tradition has not had much impact on the question of what is an element which remains an essentially philosophical issue. (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)

Distinctively mathematical explanations (DMEs) explain natural phenomena primarily by appeal to mathematical facts. One important question is whether there can be an ontic account of DME. An ontic account of DME would treat the explananda and explanantia of DMEs as ontic structures and the explanatory relation between them as an ontic relation (e.g., Pincock 2015, Povich 2021). Here I present a conventionalist account of DME, defend it against objections, and argue that it should be considered ontic. Notably, if indeed it (...) is ontic, the conventionalist account seems to avoid a convincing objection to other ontic accounts (Kuorikoski 2021). (shrink)

Ground is all the rage in contemporary metaphysics. But what is its nature? Some metaphysicians defend what we could call, following Skiles and Trogdon (2021), the inheritance view: it is because constitutive forms of metaphysical explanation are such-and-such that we should believe that ground is so-and-so. However, many putative instances of inheritance are not primarily motivated by scientific considerations. This limitation is harmless if one thinks that ground and science are best kept apart. Contrary to this view, we believe that (...) ground is a highly serviceable tool for investigating metaphysical areas of science. In this paper, we defend a naturalistic version of the inheritance view which takes constitutive scientific explanation as a better guide to ground. After illustrating the approach and its merits, we discuss some implications of the emerging scientific conception for the theory of ground at large. (shrink)

There has been a push in recent years to provide better explanations for how AIs make their decisions. Most of this push has come from the ethical concerns that go hand in hand with AIs making decisions that affect humans. Outside of the strictly ethical concerns that have prompted the study of explainable AIs (XAIs), there has been research interest in the mere possibility of creating XAIs in various domains. In general, the more accurate we make our models the harder (...) they are to explain. Go playing AIs like AlphaGo and KataGo provide fantastic examples of this phenomenon. In this paper, I discuss a non-exhaustive list of the leading theories of explanation and what each of these theories would say about the explainability of AI-played moves of Go. Finally, I consider the possibility of ever explaining AI-played Go moves in a way that meets the four principles of XAI. I conclude, somewhat pessimistically, that Go is not as imminently explainable as other domains. As such, the probability of having an XAI for Go that meets the four principles is low. (shrink)

Recent years have seen growing interest in modifying interventionist accounts of causal explanation in order to characterise noncausal explanation. However, one surprising element of such accounts is that they have typically jettisoned the core feature of interventionism: interventions. Indeed, the prevailing opinion within the philosophy of science literature suggests that interventions exclusively demarcate causal relationships. This position is so prevalent that, until now, no one has even thought to name it. We call it “intervention puritanism” (I-puritanism, for short). In this (...) paper, we mount the first sustained defence of the idea that there are distinctively noncausal explanations which can be characterized in terms of possible interventions; a position we call “intervention liberalism” (I-liberalism, for short). While many have followed James Woodward (2003) in committing to I-puritanism, we trace support for I-liberalism back to the work of Jaegwon Kim (1974). Furthermore, we analyse two recent sources of scepticism regarding I-liberalism: debate surrounding mechanistic constitution; and attempts to provide a monistic account of explanation. We show that neither literature provides compelling reasons for adopting I-puritanism. Finally, we present a novel taxonomy of available positions upon the role of possible interventions in explanation: weak causal imperialism; strong causal imperialism; monist intervention puritanism; pluralist intervention puritanism; monist intervention liberalism; and finally, the specific position defended in this paper, pluralist intervention liberalism. (shrink)

It does not seem particularly daring to say that one objective of science education is to enable students to understand different phenomena in the world in their mutual relationship. This is roughly equivalent to promoting knowledge of scientific explanations, which involve resorting to regular relationships between certain phenomena and which, certainly, is different from knowledge of this or that type of event taken in isolation. In this text, we will draw attention to two opposing tendencies that, however, tend towards the (...) common result of hindering the achievement of such an objective. On the one hand, we find characterizations of scientific explanation that assimilate it to argumentation and, therefore, lose sight of what specifically makes explanations explanatory; that is, they ask too little of a scientific explanation. On the other hand, those that consider paradigmatic cases of scientific explanation −such as those achieved by subsuming phenomena such as tides to Newton's laws− do not really constitute explanations but merely descriptions; it is about asking too much of an explanation here. We will therefore point out that a greater attention to the elaborations provided by the philosophy of science about the notion of explanation is crucial to better serve educational purposes. (shrink)

We develop and apply a multi-dimensional conception of explanatory depth towards a comparative analysis of inflationary and bouncing paradigms in primordial cosmology. Our analysis builds on earlier work due to Azhar and Loeb (2021) that establishes initial condition fine-tuning as a dimension of explanatory depth relevant to debates in contemporary cosmology. We propose dynamical fine-tuning and autonomy as two further dimensions of depth in the context of problems with instability and trans-Planckian modes that afflict bouncing and inflationary approaches respectively. In (...) the context of the latter issue, we argue that the recently formulated trans-Planckian censorship conjecture leads to a trade-off for inflationary models between dynamical fine-tuning and autonomy. We conclude with the suggestion that explanatory preference with regard to the different dimensions of depth is best understood in terms of differing attitudes towards heuristics for future model building. (shrink)

Park (2017, 2018, 2019) argues that Bas van Fraassen uses inference to the best explanation to defend his contextual theory of explanation. If Park is right, then van Fraassen is in trouble because he rejects IBE as a rational rule of inference. In this reply, I argue that van Fraassen does not use IBE in defending the contextual theory of explanation. I distinguish between several conceptions of IBE: heuristic IBE, objective Bayesian IBE, and ampliative IBE. I argue that van Fraassen (...) holds the ampliative conception of IBE and that his rejection of IBE concerns only ampliative IBE. I also argue that van Fraassen’s defense of the contextual theory of explanation, at best, can be interpreted as an instance of heuristic IBE, but not ampliative IBE. Therefore, I argue, Park’s criticism of van Fraassen misfires. (shrink)

In this article, I will provide a critical overview of the form of non-deductive reasoning commonly known as “Inference to the Best Explanation” (IBE). Roughly speaking, according to IBE, we ought to infer the hypothesis that provides the best explanation of our evidence. In section 2, I survey some contemporary formulations of IBE and highlight some of its putative applications. In section 3, I distinguish IBE from C.S. Peirce’s notion of abduction. After underlining some of the essential elements of IBE, (...) the rest of the entry is organized around an examination of various problems that IBE confronts, along with some extant attempts to address these problems. In section 4, I consider the question of when a fact requires an explanation, since presumably IBE applies only in cases where some explanation is called for. In section 5, I consider the difficult question of how we ought to understand IBE in light of the fact that among philosophers, there is significant disagreement about what constitutes an explanation. In section 6, I consider different strategies for justifying the truth-conduciveness of the explanatory virtues, e.g., simplicity, unification, scope, etc., criteria which play an indispensable role in any given application of IBE. In section 7, I survey some of the most recent literature on IBE, much of which consists of investigations of the status of IBE from the standpoint of the Bayesian philosophy of science. (shrink)

Proponents of ontic conceptions of explanation require all explanations to be backed by causal, constitutive, or similar relations. Among their justifications is that only ontic conceptions can do justice to the ‘directionality’ of explanation, i.e., the requirement that if X explains Y , then not-Y does not explain not-X . Using topological explanations as an illustration, we argue that non-ontic conceptions of explanation have ample resources for securing the directionality of explanations. The different ways in which neuroscientists rely on multiplexes (...) involving both functional and anatomical connectivity in their topological explanations vividly illustrate why ontic considerations are frequently (if not always) irrelevant to explanatory directionality. Therefore, directionality poses no problem to non-ontic conceptions of explanation. (shrink)

Lange argues that some natural phenomena can be explained by appeal to mathematical, rather than natural, facts. In these “distinctively mathematical” explanations, the core explanatory facts are either modally stronger than facts about ordinary causal law or understood to be constitutive of the physical task or arrangement at issue. Craver and Povich argue that Lange’s account of DME fails to exclude certain “reversals”. Lange has replied that his account can avoid these directionality charges. Specifically, Lange argues that in legitimate DMEs, (...) but not in their “reversals,” the empirical fact appealed to in the explanation is “understood to be constitutive of the physical task or arrangement at issue” in the explanandum. I argue that Lange’s reply is unsatisfactory because it leaves the crucial notion of being “understood to be constitutive of the physical task or arrangement” obscure in ways that fail to block “reversals” except by an apparent ad hoc stipulation or by abandoning the reliance on understanding and instead accepting a strong realism about essence. (shrink)

In this article, I consider an important challenge to the popular theory of scientific inference commonly known as ‘inference to the best explanation’, one that has received scant attention.1 1 The problem is that there exists a wide array of rival models of explanation, thus leaving IBE objectionably indeterminate. First, I briefly introduce IBE. Then, I motivate the problem and offer three potential solutions, the most plausible of which is to adopt a kind of pluralism about the rival models of (...) explanation. However, I argue that how ranking explanations on this pluralistic account of IBE remains obscure and pluralism leads to contradictory results. In light of these objections, I attempt to dissolve the problem by showing why IBE does not require a ‘model’ of explanation and by giving an account of what explanation consists in within the context of IBE. (shrink)

Over the last decades, network-based approaches have become highly popular in diverse fields of biology, including neuroscience, ecology, molecular biology and genetics. While these approaches continue to grow very rapidly, some of their conceptual and methodological aspects still require a programmatic foundation. This challenge particularly concerns the question of whether a generalized account of explanatory, organisational and descriptive levels of networks can be applied universally across biological sciences. To this end, this highly interdisciplinary theme issue focuses on the definition, motivation (...) and application of key concepts in biological network science, such as explanatory power of distinctively network explanations, network levels, and network hierarchies. (shrink)

Normative explanations, which specify why things have the normative features they do, are ubiquitous in normative theory and ordinary thought. But there is much less work on normative explanation than on scientific or metaphysical explanation. Skow (2016) argues that a complete answer to the question why some fact Q occurs consists in all of the reasons why Q occurs. This paper explores this theory as a case study of a general theory that promises to offer us a grip on normative (...) explanation which is independent of particular normative theories. I first argue that the theory doesn’t give an adequate account of certain enablers of reasons which are important in normative explanation. I then formulate and reject three responses on behalf of the theory. But I suggest that since theories of this general sort have the right kind of resources to illuminate how normative explanation might be similar to and different from explanations in other domains, they nonetheless merit further exploration by normative theorists. (shrink)

The focus in the literature on scientific explanation has shifted in recent years towards modelbased approaches. The idea that there are simple and true laws of nature has met with objections from philosophers such as Nancy Cartwright (1983) and Paul Teller (2001), and this has made a strictly Hempelian D-N style explanation largely irrelevant to the explanatory practices of science (Hempel & Oppenheim, 1948). Much of science does not involve subsuming particular events under laws of nature. It is increasingly recognized (...) that science across the disciplines is to some degree a patchwork of scientific models, with different methods, strategies, and with varying degrees of successful prediction and explanation. And so accounts of scientific explanation have reflected this change of perspective and model-based approaches have flourished in the explanation literature (Batterman, 2002b; Bokulich, 2008; Craver, 2006; Woodward, 2003). (shrink)

This article discusses the rationality principle, especially in Popper's version, on the occasion of a commentary of Maurice Lagueux's book, Rationality and Explanation in Economics (2010).

Our aim in this paper is to bring the woefully neglected literature on predictive modeling to bear on some central questions in the philosophy of science. The lesson of this literature is straightforward: For a very wide range of prediction problems, statistical prediction rules (SPRs), often rules that are very easy to implement, make predictions than are as reliable as, and typically more reliable than, human experts. We will argue that the success of SPRs forces us to reconsider our views (...) about what is involved in understanding, explanation, good reasoning, and about how we ought to do philosophy of science. (shrink)