The ability to generalize from the known to the unknown is central to learning and inference. Two experiments explore the relationship between how a property is explained and how that property is generalized to novel species and artifacts. The experiments contrast the consequences of explaining a property mechanistically, by appeal to parts and processes, with the consequences of explaining the property functionally, by appeal to functions and goals. The findings suggest that properties that are explained functionally are more likely to (...) be generalized on the basis of shared functions, with a weaker relationship between mechanistic explanations and generalization on the basis of shared parts and processes. The influence of explanation type on generalization holds even though all participants are provided with the same mechanistic and functional information, and whether an explanation type is freely generated (Experiment 1), experimentally provided (Experiment 2), or experimentally induced (Experiment 2). The experiments also demonstrate that explanations and generalizations of a particular type (mechanistic or functional) can be experimentally induced by providing sample explanations of that type, with a comparable effect when the sample explanations come from the same domain or from a different domains. These results suggest that explanations serve as a guide to generalization, and contribute to a growing body of work supporting the value of distinguishing mechanistic and functional explanations. (shrink)

This article is about the role of abstraction in mechanistic explanations. Abstraction is widely recognised as a necessary concession to the practicalities of scientific work, but some mechanist philosophers argue that it is also a positive explanatory feature in its own right. I claim that in as much as these arguments are based on the idea that mechanistic explanation exhibits a trade-off between fine-grained detail and generality, they are unsuccessful. Detail and generality both appear to be important (...) sources of explanatory power, but investigators do not need to make a choice between these desiderata, at least when an explanation incorporates further detail through the decomposition of the mechanism's parts. (shrink)

In this paper, I present a general theory of topological explanations, and illustrate its fruitfulness by showing how it accounts for explanatory asymmetry. My argument is developed in three steps. In the first step, I show what it is for some topological property A to explain some physical or dynamical property B. Based on that, I derive three key criteria of successful topological explanations: a criterion concerning the facticity of topological explanations, i.e. what makes it true of a particular system; (...) a criterion for describing counterfactual dependencies in two explanatory modes, i.e. the vertical and the horizontal; and, finally, a third perspectival one that tells us when to use the vertical and when to use the horizontal mode. In the second step, I show how this general theory of topological explanations accounts for explanatory asymmetry in both the vertical and horizontal explanatory modes. Finally, in the third step, I argue that this theory is universally applicable across biological sciences, which helps to unify essential concepts of biological networks. (shrink)

Research in education and cognitive development suggests that explaining plays a key role in learning and generalization: When learners provide explanations—even to themselves—they learn more effectively and generalize more readily to novel situations. This paper proposes and tests a subsumptive constraints account of this effect. Motivated by philosophical theories of explanation, this account predicts that explaining guides learners to interpret what they are learning in terms of unifying patterns or regularities, which promotes the discovery of broad generalizations. Three experiments (...) provide evidence for the subsumptive constraints account: prompting participants to explain while learning artificial categories promotes the induction of a broad generalization underlying category membership, relative to describing items (Exp. 1), thinking aloud (Exp. 2), or free study (Exp. 3). Although explaining facilitates discovery, Experiment 1 finds that description is more beneficial for learning item details. Experiment 2 additionally suggests that explaining anomalous observations may play a special role in belief revision. The findings provide insight into explanation’s role in discovery and generalization. (shrink)

Among the divers factors that have encouraged and sustained scientific inquiry through its long history are two pervasive human concerns which provide, I think, the basic motivation for all scientific research. One of these is man's persistent desire to improve his strategic position in the world by means of dependable methods for predicting and, whenever possible, controlling the events that occur in it. The extent to which science has been able to satisfy this urge is reflected impressively in the vast (...) and steadily widening range of its technological applications. But besides this practical concern, there is a second basic motivation for the scientific quest, namely, man's insatiable intellectual curiosity, his deep concern to know the world he lives in, and to explain, and thus to understand, the unending flow of phenomena it presents to him. (shrink)

Teleological explanations (TEs) account for the existence or properties of an entity in terms of a function: we have hearts because they pump blood, and telephones for communication. While many teleological explanations seem appropriate, others are clearly not warranted-for example, that rain exists for plants to grow. Five experiments explore the theoretical commitments that underlie teleological explanations. With the analysis of [Wright, L. (1976). Teleological Explanations. Berkeley, CA: University of California Press] from philosophy as a point of departure, we examine (...) in Experiment 1 whether teleological explanations are interpreted causally, and confirm that TEs are only accepted when the function invoked in the explanation played a causal role in bringing about what is being explained. However, we also find that playing a causal role is not sufficient for all participants to accept TEs. Experiment 2 shows that this is not because participants fail to appreciate the causal structure of the scenarios used as stimuli. In Experiments 3-5 we show that the additional requirement for TE acceptance is that the process by which the function played a causal role must be general in the sense of conforming to a predictable pattern. These findings motivate a proposal, Explanation for Export, which suggests that a psychological function of explanation is to highlight information likely to subserve future prediction and intervention. We relate our proposal to normative accounts of explanation from philosophy of science, as well as to claims from psychology and artificial intelligence. (shrink)

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

This paper describes an alternative to the common view that explanation in the special sciences involves subsumption under laws. According to this alternative, whether or not a generalization can be used to explain has to do with whether it is invariant rather than with whether it is lawful. A generalization is invariant if it is stable or robust in the sense that it would continue to hold under a relevant if it is stable or robust in the sense that (...) it would continue to hold under a relevant class of changes. Unlike lawfulness, invariance comes in degrees and has other features that are well suited to capture the characteristics of explanatory generalizations in the special sciences. For example, a generalization can be invariant even if it has exceptions or holds only over a limited spatio-temporal interval. The notion of invariance can be used to resolve a number of dilemmas that arise in standard treatments of explanatory generalizations in the special sciences. (shrink)

Many theories of kind representation suggest that people posit internal, essence-like factors that underlie kind membership and explain properties of category members. Across three studies (N = 281), we document the characteristics of an alternative form of construal according to which the properties of social kinds are seen as products of structural factors: stable, external constraints that obtain due to the kind’s social position. Internalist and structural construals are similar in that both support formal explanations (i.e., “category member has property (...) P due to category membership C”), generic claims (“Cs have P”), and the generalization of category properties to individual category members when kind membership and social position are confounded. Our findings thus challenge these phenomena as signatures of internalist thinking. However, once category membership and structural position are unconfounded, different patterns of generalization emerge across internalist and structural construals, as do different judgments concerning category definitions and the dispensability of properties for category membership. We discuss the broader implications of these findings for accounts of formal explanation, generic language, and kind representation. (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)

Explainable artificial intelligence (XAI) aims to help people understand black box algorithms, particularly of their outputs. But what are these explanations and when is one explanation better than another? The manipulationist definition of explanation from the philosophy of science offers good answers to these questions, holding that an explanation consists of a generalization that shows what happens in counterfactual cases. Furthermore, when it comes to explanatory depth this account holds that a generalization that has more abstract variables, (...) is broader in scope and/or more accurate is better. By applying these definitions and contrasting them with alternative definitions in the XAI literature I hope to help clarify what a good explanation is for AI. (shrink)

In this article I argue that there are two different types of understanding: the understanding we get from explanations, and the understanding we get from unification. This claim is defended by first showing that explanation and unification are not as closely related as has sometimes been thought. A critical appraisal of recent proposals for understanding without explanation leads us to discuss the example of a purely classificatory biology: it turns out that such a science can give us understanding (...) of the world through unification of the phenomena, even though it does not give us any explanations. The two types of understanding identified in this paper, while strictly separate, do have in common that both consist in seeing how the individual phenomena of the universe hang together. Explanations give us connections between the phenomena through the asymmetric, ‘vertical’ relation of determination; unifications give us connections through the symmetric, ‘horizontal’ relation of kinship. We then arrive at a general definition of understanding as knowledge of connections between the phenomena, and indicate that there might be more than two types of understanding. (shrink)

Explaining phenomena is a primary goal of science. Consequently, it is unsurprising that gaining a proper understanding of the nature of explanation is an important goal of science education. In order to properly understand explanation, however, it is not enough to simply consider theories of the nature of explanation. Properly understanding explanation requires grasping the relation between explanation and understanding, as well as how explanations can lead to scientific knowledge. This article examines the nature of (...) explanation, its relation to understanding, and how explanations are used to generate scientific knowledge via inferences to the best explanation. Studying these features and applications of explanation not only provides insight into a concept that is important for science education in its own right, but also sheds light on an aspect of recent debates concerning the so-called consensus view of nature of science (NOS). Once the relation between explanation, understanding, and knowledge is clear, it becomes apparent that science is unified in important ways. Seeing this unification provides some support for thinking that there are general features of NOS of the sort proposed by the consensus view and that teaching about these general features of NOS should be a goal of science education. (shrink)

A new trend in the philosophical literature on scientific explanation is that of starting from a case that has been somehow identified as an explanation and then proceed to bringing to light its characteristic features and to constructing an account for the type of explanation it exemplifies. A type of this approach to thinking about explanation – the piecemeal approach, as I will call it – is used, among others, by Lange (2013) and Pincock (2015) in (...) the context of their treatment of the problem of mathematical explanations of physical phenomena. This problem is of central importance in two different recent philosophical disputes: the dispute about the existence on non-causal scientific explanations and the dispute between realists and antirealists in the philosophy of mathematics. My aim in this paper is twofold. I will first argue that Lange (2013) and Pincock (2015) fail to make a significant contribution to these disputes. They fail to contribute to the dispute in the philosophy of mathematics because, in this context, their approach can be seen as question begging. They also fail to contribute to the dispute in the general philosophy of science because, as I will argue, there are important problems with the cases discussed by Lange and Pincock. I will then argue that the source of the problems with these two papers has to do with the fact that the piecemeal approach used to account for mathematical explanation is problematic. (shrink)

People are habitual explanation generators. At its most mundane, our propensity to explain allows us to infer that we should not drink milk that smells sour; at the other extreme, it allows us to establish facts (e.g., theorems in mathematical logic) whose truth was not even known prior to the existence of the explanation (proof). What do the cognitive operations underlying the inference that the milk is sour have in common with the proof that, say, the square root (...) of two is irrational? Our ability to generate explanations bears striking similarities to our ability to make analogies. Both reflect a capacity to generate inferences and generalizations that go beyond the featural similarities between a novel problem and familiar problems in terms of which the novel problem may be understood. However, a notable difference between analogy-making and explanation-generation is that the former is a process in which a single source situation is used to reason about a single target, whereas the latter often requires the reasoner to integrate multiple sources of knowledge. This seemingly small difference poses a challenge to the task of marshaling our understanding of analogical reasoning to understanding explanation. We describe a model of explanation, derived from a model of analogy, adapted to permit systematic violations of this one-to-one mapping constraint. Simulation results demonstrate that the resulting model can generate explanations for novel explananda and that, like the explanations generated by human reasoners, these explanations vary in their coherence. (shrink)

A large part of the explainable AI literature focuses on what explanations are in general, what algorithmic explainability is more specifically, and how to code these principles of explainability into AI systems. Much less attention has been devoted to the question of why algorithmic decisions and systems should be explainable and whether there ought to be a right to explanation and why. We therefore explore the normative landscape of the need for AI to be explainable and individuals having a (...) right to such explanation. This exploration is particularly relevant to the medical domain where the (im)possibility of explainable AI is high on both the research and practitioners’ agenda. The dominant intuition overall is that explainability has and should play a key role in the health context. Notwithstanding the strong normative intuition for having a right to explanation, intuitions can be wrong. So, we need more than an appeal to intuitions when it comes to explaining the normative significance of having a right to explanation when being subject to AI-based decision-making. The aim of the paper is therefore to provide an account of what might underlie the normative intuition. We defend the ‘symmetry thesis’ according to which there is no special normative reason to have a right to explanation when ‘machines’ in the broad sense, make decisions, recommend treatment, discover tumors, and so on. Instead, we argue that we have a right to explanation in cases that involve automated processing that significantly affect our core deliberative agency and which we do not understand, because we have a general moral right to explanation when choices are made which significantly affect us but which we do not understand. (shrink)

I argue that philosophical issues concerning reductive explanations help constrain the construction of quantum theories with appropriate state spaces. I illustrate this general proposal with two examples of restricting attention to physical states in quantum theories: regular states and symmetry-invariant states. 1Introduction2Background2.1 Physical states2.2 Reductive explanations3The Proposed ‘Correspondence Principle’4Example: Regularity5Example: Symmetry-Invariance6Conclusion: Heuristics and Discovery.

From their conception to the present, the social sciences have invoked a kind of explanation that looks suspect by the standards of the natural sciences. They explain why social practices exist by reference to the purpose or needs they serve. Yet the purposes invoked are generally not the explicit purposes or needs of any individual but of society or social groups. For example, Durkheim claimed that the division of labor in society exists in order to promote social solidarity and (...) Marx thought that the state served to promote the interests of the ruling class. Social scientists have found these explanations as irresistible as their critics have found them mysterious. This chapter traces the controversies over these explanations — generally called functional explanations — and argues that they are widespread in some of our best current social science and that they can provide compelling information in some cases, despite the many doubts about them. (shrink)

It is claimed that Kuipers' approach to explanation opens the possibility for a further refinement of his own refined HD method for the evaluation of theories. One severe problem for the HD method, refined or not, is theory-ladeness. Given that experimental results are theory-laden, the comparative evaluation of alternative hypotheses is always relative to background knowledge. This difficulty can be avoided by supplementing HD considerations with the principle of inference to the best explanation. The authors sketch a program (...) for doing this. The general idea plays on some similarities between Kuipers' account of explanation and Lipton's. The former, however, is considered more flexible than the latter, which makes it even more attractive for the purpose under consideration. (shrink)

Although standard Machine Learning models are optimized for making predictions about observations, more and more they are used for making predictions about the results of actions. An important goal of Explainable Artificial Intelligence (XAI) is to compensate for this mismatch by offering explanations about the predictions of an ML-model which ensure that they are reliably action-guiding. As action-guiding explanations are causal explanations, the literature on this topic is starting to embrace insights from the literature on causal models. Here I take (...) a step further down this path by formally defining the causal notions of sufficient explanations and counterfactual explanations. I show how these notions relate to (and improve upon) existing work, and motivate their adequacy by illustrating how different explanations are action-guiding under different circum- stances. Moreover, this work is the first to offer a formal definition of actual causation that is founded entirely in action-guiding explanations. Although the definitions are motivated by a focus on XAI, the analysis of causal explanation and actual causation applies in general. I also touch upon the significance of this work for fairness in AI by showing how actual causation can be used to improve the idea of path-specific counterfactual fairness. (shrink)

In this paper, I propose that applying the methods of data science to “the problem of whether mathematical explanations occur within mathematics itself” (Mancosu 2018) might be a fruitful way to shed new light on the problem. By carefully selecting indicator words for explanation and justification, and then systematically searching for these indicators in databases of scholarly works in mathematics, we can get an idea of how mathematicians use these terms in mathematical practice and with what frequency. The results (...) of this empirical study suggest that mathematical explanations do occur in research articles published in mathematics journals, as indicated by the occurrence of explanation indicators. When compared with the use of justification indicators, however, the data suggest that justifications occur much more frequently than explanations in scholarly mathematical practice. The results also suggest that justificatory proofs occur much more frequently than explanatory proofs, thus suggesting that proof may be playing a larger justificatory role than an explanatory role in scholarly mathematical practice. (shrink)

The Problem of Old Evidence is a perennial issue for Bayesian confirmation theory. Garber (Test Sci Theor 10:99–131, 1983) famously argues that the problem can be solved by conditionalizing on the proposition that a hypothesis deductively implies the existence of the old evidence. In recent work, Hartmann and Fitelson (Philos Sci 82(4):712–717, 2015) and Sprenger (Philos Sci 82(3):383–401, 2015) aim for similar, but more general, solutions to the Problem of Old Evidence. These solutions are more general because they allow the (...) explanatory relationship between a new hypothesis and old evidence to be inductive, rather than deductive. In this paper, I argue that these solutions are either unsound or under-motivated, depending on the case of inductive explanation that we have in mind. This lends support to the broader claim that Garber–Style Bayesian confirmation cannot capture the sense in which new hypotheses that do not deductively imply old evidence nevertheless seem to be confirmed via old evidence. (shrink)

For the generalizations of thermodynamics to obtain, it appears that a very ‘special’ initial condition of the universe is required. Is this initial condition itself in need of explanation? I argue that it is not. In so doing, I offer a framework in which to think about ‘special’ initial conditions in all areas of science, though I concentrate on the case of thermodynamics. I urge the view that it is not always a serious mark against a theory that it (...) must posit an ‘improbable’ initial condition. (shrink)

Can religious premises ever be cited legitimately in explanations of matters of fact? Scientific practice is generally regarded as the source of our explanatory paradigms and the final arbiter of matters of fact, and is so constituted that it could never endorse such explanations. Neither would they be sanctioned by the non-cognitive reconstructions of religious discourse currently fashionable. I argue: Some scientific constraints on explanations, such as consistency, testability, and corrigibility, are generally legitimate in non-scientific contexts. Other cognitive values, such (...) as clarity and simplicity, though not constraints, still have adequate credentials to serve globally in the evaluation of theories and explanations. In addition to these, science employs overtly ideological constraints on explanation, plus a number of parochial values, including control, replicability, and skepticism. These serve to circumscribe the range of acceptable explanations more narrowly than reasonable standards of rationality would necessitate. In particular, they are responsible for precluding religious explanations unnecessarily. ;Finally, one can reconstruct from religious contexts a system of cognitive values with broad application that takes exception to scientific norms pertaining to the status of teleological explanations, the ranking of outstanding problem areas in importance, the usefulness of anecdotal material, and the appropriateness of pragmatic conceptions of truth. The additional explanations this value structure sanctions will be less secure than scientific explanations generally, and somewhat idiosyncratic. They may be appropriate when no scientific explanations are possible or available, or if the religious explanation is teleological and the scientific explanation is not. Near-death experiences represent a major potential source of religious explanations, although one in great need of development. More generally, our ability to give religious explanations is hampered by inadequate theoretical articulations of the concept of God. (shrink)

Some philosphers of science of an empiricist and pragmatist bent have proposed models of statistical explanation, but have then become sceptical of the adequacy of these models. It is argued that general considerations concerning the purpose of function of explanation in science which are usually appealed to by such philosophers show that their scepticism is not well taken; for such considerations provide much the same rationale for the search for statistical explanations, as these philosophers have characterized them, as (...) they do for lawlike explanations. But, it is further argued, a significant piece of what is frequently offered as an explanation of well known phenomena in statistical mechanics, fails to meet this general "pragmatic rationale" for statistical, or indeed any kind of, explanation. The question then arises whether the physicists have misconstrued the value of this piece of physical theorizing, ergodic theory, taking it to be explanatory when it is actually not; or whether, instead, the philosopher's account of just what is genuinely explanatory is too narrow. (shrink)

For example, from the point of view of pure conceptual analysis, since the reduction of what is not understood to what is understood is new understanding, explanation seems to involve growth of understanding. But is it the only kind of growth of understanding? It seems that explanation is quantitative growth of understanding. Could there be a qualitative growth of understanding and if so what would it be? And how would qualitative growth of understanding relate to explanation?

What is the relevance of an analytical philosophy of history to the practice of history? There are four fundamental criticisms of the existing analytical philosophy: analytical philosophers have concentrated on old, dualistic traditions of history; they have not provided sufficient empirical validation for their explanatory theories; they have paid little attention to the preliminary operations necessary to the writing of historical explanation; and they have ignored important stages of growth within the study of history. These are criticisms of the (...) existing apragmatic philosophies of history, which lack a necessary empirical basis and become static, tied to one research tradition within historical scholarship. A pragmatic philosophy of history would focus on the growth of historical scholarship. The "History of Society," a name for the global approach to history, operates under the rules of comparative history. In the framework of a typology of the comparative method, types of difference and contrast refer back to the dominating types of macrocausality, generality, and inclusion. The logic of historical explanations is greatly determined by the choice of a particular type of comparative history. A pragmatic analysis demonstrates that a plurality of shades of meaning are possible in historical explanation, and that the traditional apragmatic dualist theory of a tension between the global and particular provides insufficient description. (shrink)

In a series of papers, Papineau argues that the Swampman scenario is not even the start of an objection to teleosemantics as a scientific reduction of belief. It is against this claim that I want to argue here. I shall argue that our intuition about the scenario questions the adequacy of the conceptual foundations of teleosemantics, namely, success semantics and the etiological conception of biological function, on which the explanatory power of the theory rests. In the course of argument, some (...) general connections between explanation and modality will be developed that shed a new light on Kripke’s analysis of necessary a posteriori propositions. The upshot will be that teleosemanticists should tackle the Swampman objection head-on. (shrink)

I argue that manipulationist theories of causation fail as accounts of causal structure, and thereby as theories of “actual causation” and causal explanation. I focus on two kinds of problem cases, which I call “Perceived Abnormality Cases” and “Ontological Dependence Cases.” The cases illustrate that basic facts about social systems—that individuals are sensitive to perceived abnormal conditions and that certain actions metaphysically depend on institutional rules—pose a challenge for manipulationist theories and for counterfactual theories more generally. I then show (...) how law-based accounts of causal structure can answer such challenges. The moral of the story is that the basic manipulationist idea that our interest in causal structure is driven by our interest in manipulating our environment faces decisive problems in a central domain of application, the social sciences. (shrink)

The theme of the dissertation is that we should not be too cautious about engaging in metaphysics of modality; what may appear to be a refusal to engage in metaphysical speculation may instead involve a commitment to epistemic consequences that we should not accept. In Part I, I argue that David Lewis's modal realism implies that scepticism towards induction is rationally unavoidable. I conclude that his theory must be rejected. ;While not endorsing Lewis's account of the nature of possible worlds, (...) I argue that the recombination principle is what is causing the problems, and that this principle will cause problems when combined with any theory of modality according to which there are objective matters of fact as to what is possible or necessary. ;I conclude that we must reject the recombination principle, and that any principle we accept in its place must be one which will not lead to inductive scepticism. This suggests that we cannot countenance any objective possibilities that contravene actual natural laws. ;In Part II, I argue that one sort of explanation is closely connected with objective possibility: A fundamental explanation for some state of affairs involves saying something about its nature that has implications for what is objectively possible. I defend a weak form of the principle of sufficient reason, according to which every state of affairs has a fundamental explanation ;I go on to recast and defend a version of the Cosmological Argument for the existence of God. This argument, on my view, is plausible only when taken as an inductive argument, and indeed, as an inference to the best explanation. I argue that the theistic hypothesis deserves to be taken seriously on its merits as an explanation; more generally, I claim that it is not sufficient grounds for rejecting any hypothesis simply to say that it involves commitments as to what is possible or necessary. A willingness to accept some such commitments is an unavoidable consequence of what we normally take to be rational ways of forming beliefs. (shrink)

To date, no satisfactory account of the connection between natural-scientific and historical explanation has been given, and philosophers seem to have largely given up on the problem. This paper is an attempt to resolve this old issue and to sort out and clarify some areas of historical explanation by developing and applying a method that will be called “pragmatic explication” involving the construction of definitions that are justified on pragmatic grounds. Explanations in general can be divided into “dynamic” (...) and “static” explanations, which are those that essentially require relations across time and those that do not, respectively. The problem of assimilating historical explanations concerns dynamic explanation, so a general analysis of dynamic explanation that captures both the structure of natural-scientific and historical explanation is offered. This is done in three stages: In the first stage, pragmatic explication is introduced and compared to other philosophical methods of explication. In the second stage pragmatic explication is used to tie together a series of definitions that are introduced in order to establish an account of explanation. This involves an investigation of the conditions that play the role in historiography that laws and statistical regularities play in the natural sciences. The essay argues that in the natural sciences, as well as in history, the model of explanation presented represents the aims and overarching structure of actual causal explanations offered in those disciplines. In the third stage the system arrived at in the preceding stage is filled in with conditions available to and relevant for historical inquiry. Further, the nature and treatment of causes in history and everyday life are explored and related to the system being proposed. This in turn makes room for a view connecting aspects of historical explanation and what we generally take to be causal relations. (shrink)

The question of the dimensionality of space has informed the development of physics since the beginning of the twentieth century in the quest for a unified picture of quantum processes and gravitation. Scientists have worked within various approaches to explain why the universe appears to have a certain number of spatial dimensions. The question of why space has three dimensions has a genuinely philosophical nature that can be shaped as a problem of justifying a contingent necessity of the world. In (...) contrast to explanations of three-dimensionality based on anthropic arguments, we support the search for a theory that provides a justification for the dimensionality of space based on a combination of deductive and inductive reasoning applied to science. In doing so, we argue that Kant correctly approached the question in “Thoughts on the true estimation of living forces” by connecting space dimensionality and the inverse square law. In expounding the strategy of Kant’s argument, we describe the main features of a general Kantian explanation of the dimensionality of space and discuss them with respect to current accounts of explanation in the philosophy of science, such as inference to the best explanation and the deductive-nomological model. (shrink)

Some properties are causally relevant for a certain effect, others are not. In this paper we describe a problem for our understanding of this notion and then offer a solution in terms of the notion of a program explanation.

Humeans and anti-Humeans agree that laws of nature should explain scientifically particular matters of fact. One objection to Humean accounts of laws contends that Humean laws cannot explain particular matters of fact because their explanations are harmfully circular. This article distinguishes between metaphysical and semantic characterizations of the circularity and argues for a new semantic version of the circularity objection. The new formulation suggests that Humean explanations are harmfully circular because the content of the sentences being explained is part of (...) the content of the sentences doing the explaining. I describe the nature of partial content and demonstrate how this account of partial content renders Humean explanations ineffective while sparing anti-Humean explanations from the same fate. 1Introduction2Standard Formulations of the Circularity Charge3Humean Responses4Semantic Characterizations of the Circularity Worry 4.1Hempel and Oppenheim’s semantic circularity concern4.2A new version of the semantic circularity charge4.3Partial content as a guide to circularity5Humean Responses to the Semantic Circularity Charge 5.1Smuggling in metaphysics through the back door?5.2Do anti-Humean laws fare any better?5.3The over-generalization concern6ConclusionAppendix. (shrink)

We argue that two powerful error-theoretic concepts provide a general framework that satisfactorily accounts for key aspects of the explanation of physical patterns. This method gives an objective criterion to determine which mathematical models in a class of neighboring models are just as good as the exact one. The method also emphasizes that abstraction is essential for explanation and provides a precise conceptual framework that determines whether a given abstraction is explanatorily relevant and justified. Hence, it increases our (...) epistemological understanding of how one should go about reconstructing scientific practices by making clear that, at a fundamental level, a key aspect of mathematical modeling consists in exactly solving nearby problems. (shrink)

I WISH to defend the claim that imagining what it would be like to be in "someone else's shoes" can serve to explain that person's actions. This commonsense view has considerable plausibility, but requires clarification to be philosophically defensible; discussions of explanation often assume that understanding requires a theory of the thing understood. If understanding requires a theory, then however much imagining what it would be like to be in another person's situation might sooth one's curiosity, it cannot provide (...) real understanding. I shall argue that imagining oneself in someone else's situation does more than that: it allows actions to be explained without recourse to a theory of human behavior. The resulting explanations are real explanations, not just some reassuring facsimile thereof. (shrink)

In this paper we assess the explanatory role of idealizations in ‘design explanations’, a type of functional explanation used in biology. In design explanations, idealizations highlight which factors make a difference to phenomena to be explained: hypothetical, idealized, organisms are invoked to make salient which traits of extant organisms make a difference to organismal fitness. This result negates the view that idealizations serve only pragmatic benefits, and complements the view that idealizations highlight factors that do not make a difference. (...) This analysis in particular strengthens the perspective that idealizations are means to highlight difference making factors, and identifies a novel, more direct role for idealizations in doing so. It thus offers a novel argument why in some explanatory contexts idealizations are in-eliminable. (shrink)

I offer an account of the relation between explanations of behaviour in terms of psychological states and explanations in terms of neural states that: makes it transparent how they can be true together; explains why explanations in terms of psychological states are characteristically of behaviour described in general and relational terms, and explains why certain sorts of neurological investigations undermine psychological explanations of behaviour, while others leave them intact. In the course of the argument, I offer an account of implicit (...) theories. (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)

If one had all the true particular statements that there are would such a collection be deficient for the purpose of science? In particular, would we still require a type of explanation that requires irreducible appeal to universals, and modalities. An argument to this conclusion is examined. In the situation envisaged, the realists needed distinctions such as between accidental and essential properties, or generalizations that are accidently true and those that are lawful and true, cannot be made. The argument (...) then is rejected: appeal to universals, and the need for explanations td tell us what might have happened, cannot be secured when science no longer need discover the truth about the world. Particulars maintain their claim to epistemological and ontological priority over universals. (shrink)

Propositional temporalism is the view that there are temporary propositions: propositions that are true, but not always true. Factual futurism is the view that there are futurist facts: facts that obtain, but that will at some point not obtain. Most A-theoretic views in the philosophy of time are committed both to propositional temporalism and to factual futurism. Mark Richard, Jeffrey King and others have argued that temporary propositions are not fit to be the contents of propositional attitudes, or to be (...) the semantic values of natural language utterances. But these discussions have overlooked another role that the A-theorist’s posits struggle to play: the role of facts in explaining other facts. Focusing on the case of action explanation by reasons, this paper presents the challenge that explanation poses for factual futurism. It then brings that challenge to bear against propositional temporalism and the A-theory more generally. My argument saddles the factual futurist with surprising commitments concerning reasons, facts and explanation. The futurist might accept those commitments and pay the price. The alternative – which I prefer – is to reject factual futurism, and with it the A-theory. (shrink)

The Scientific Revolution is often associated with a transition to a ``mechanistic'' world view. However, ``mechanization'' is not the term that best captures the distinctive nature of modern physics: ``mathematization'' would be a better characterization. Modern physics attempts to find mathematical relations between quantities, and does not require that these relations be interpreted in terms of mechanisms. Moreover, in modern physics there are cases in which it is unnatural to give the mathematical formalism a mechanistic interpretation, even if ``mechanistic'' is (...) broadly construed. Both on the level of ontology and that of explanation physics turns out to be more general and liberal than what is suggested by the catchphrase that physics explains by identifying mechanisms. Although mechanistic explanation remains an important conceptual tool, in particular for achieving understanding, it is not the only one available and cannot lay claim to fundamentality. (shrink)

Frank Jackson and Philip Pettit have defended a non-reductive account of causal relevance known as the ‘program explanation account’. Allegedly, irreducible mental properties can be causally relevant in virtue of figuring in non-redundant program explanations which convey information not conveyed by explanations in terms of the physical properties that actually do the ‘causal work’. I argue that none of the possible ways to spell out the intuitively plausible idea of a program explanation serves its purpose, viz., defends non-reductive (...) physicalism against Jaegwon Kim’s Causal Exclusion Argument according to which non-reductive physicalism is committed to epiphenomenalism because irreducible mental properties are ‘screened off’ from causal relevance by their physical realizers. Jackson and Pettit’s most promising explication of a program explanation appeals to the idea of invariance of effect under variation of realization, but I show that invariance of effect under variation of realization is neither necessary nor sufficient for causal relevance. (shrink)

The aim of this article is to provide a way of resolving the apparent dilemma between our requirement as agents that actions should be free and our demand as spectators that all events should be predictable and explicable on the basis of antecedent conditions. I hope to show that what has often been incorrectly regarded as a logical incompatibility between freedom and determinism is, in fact, a disparity but not an over-all contradiction between the viewpoint of an agent and that (...) of a spectator. While it is logically impossible for a person to deliberate about his conduct in a given matter from the standpoint of an agent and also predict it as a spectator, this is the only logical incompatibility between these positions, and it does not preclude the two points of view from being equally legitimate ways of viewing action. Perhaps it has sometimes been a vague recognition of the fact that one logically cannot both deliberate upon and predict one’s own conduct in a certain matter that has led some philosophers to conclude erroneously that choice on the part of an agent is inconsistent with prediction or explanation of his decision on the part of any spectator. This unwarranted conclusion is equivalent to denying that conduct can be regarded both from the standpoint of the agent and that of the spectator. (shrink)

It has often been claimed by philosophical theologians that the concept of God functions as an ‘ultimate explanation’ of the nature of the universe. In recent years, various theologians have regarded this notion of ‘ultimate explanation’ as one which has a central place in religious belief; and they construe the concept of God, at least in part, and sometimes mainly, as a concept which provides such an explanation. On the other hand, from the time of David Hume (...) there has been a long line of eminent philosophers who have found the whole idea of an ultimate explanation—something which completely explains absolutely everything—an incoherent one, analogous to the idea of the square of a circle. I think it worth trying to explore the possibilities and limits of the notion, and attempting to assess its importance for religious belief. First, I will briefly sketch the notion as it is found in recent work, and then offer an analysis of the notion of ‘explanation’ in general. Finally, I will try to ascertain the nature and limits of the notion in religion. (shrink)

“Explanation” refers to a wide range of activities, with a family resemblance between them. Most satisfactory explanations in a discipline for a domain fail to satisfy some general desiderata, while fulfilling others. This can happen in various ways. Why? An idealizing response would be to say that in real science explanations fall short along some dimensions, so that for any explanatory failure there is a conceivable improvement that addresses its shortcomings. The improvement may be more accurate causally or possess (...) more unifying power, or deliver deeper understanding. We formulate a drastically less idealizing response. We argue that there are typically trade-offs in explanation, so that in strengthening one explanatory virtue one will usually weaken another. Scientific explanations, if this is correct, are constrained by such trade-offs. Particular trade-offs are appropriate for particular explanatory vehicles. There are the overarching equations of theoretical physics, which produce unification at the expense of causal detail; there are theoretical models of phenomena that occupy a middle ground between generality and the detailed workings of particular cases and get closer to explaining the workings of specific systems at the expense of unification. Sometimes experiments aim at general causal patterns at the expense of particular detail; and sometimes they are designed to give us information of particular detail at the expense of generality. There are further trade-offs associated with other vehicles of explanation. We provide examples from physics and biology. (shrink)

Frank Jackson and Philip Pettit have defended a non-reductive account of causal relevance known as the ‘program explanation account’. Allegedly, irreducible mental properties can be causally relevant in virtue of figuring in non-redundant program explanations which convey information not conveyed by explanations in terms of the physical properties that actually do the ‘causal work’. I argue that none of the possible ways to spell out the intuitively plausible idea of a program explanation serves its purpose, viz., defends non-reductive (...) physicalism against Jaegwon Kim’s Causal Exclusion Argument according to which non-reductive physicalism is committed to epiphenomenalism because irreducible mental properties are ‘screened off’ from causal relevance by their physical realizers. Jackson and Pettit’s most promising explication of a program explanation appeals to the idea of invariance of effect under variation of realization, but I show that invariance of effect under variation of realization is neither necessary nor sufficient for causal relevance. (shrink)

Predictive risk modelling is a computational method used to generate probabilities correlating events. The output of such systems is typically represented by a statistical score derived from various related and often arbitrary datasets. In many cases, the information generated by such systems is treated as a form of evidence to justify further action. This paper examines the nature of the information generated by such systems and compares it with more orthodox notions of evidence found in epistemology. The paper focuses on (...) a specific example to illustrate the issues: The New Zealand Government has proposed implementing a predictive risk modelling system which purportedly identifies children at risk of a maltreatment event before the age of five. Timothy Williamson’s conception of epistemology places a requirement on knowledge that it be explanatory. Furthermore, Williamson argues that knowledge is equivalent to evidence. This approach is compared to the claim that the output of such computational systems constitutes evidence. While there may be some utility in using predictive risk modelling systems, I argue, since an explanatory account of the output of such algorithms that meets Williamson’s requirements cannot be given, doubt is cast upon the resulting statistical scores as constituting evidence on generally accepted epistemic grounds. The algorithms employed in such systems are geared towards identifying patterns which turn out to be good correlations. However, rather than providing information about specific individuals and their exposure to risk, a more valid explanation of a high probability score is that the particular variables related to incidents of maltreatment are just higher amongst certain subgroups in a population than they are amongst others. The paper concludes that any justification of the information generated by such systems is generalised and pragmatic at best and the application of this information to individual cases raises various ethical issues. (shrink)