This paper offers a systematic classification and characterization of speech acts and their norms. Recently, the normative approach has been applied to various speech acts, most notably to constatives. I start by showing how the work on the norms of assertion has influenced various approaches to the norms of other speech acts. I focus on the fact that various norms of assertion have different extensions, i.e., they denote different clusters of illocutions as belonging to an assertion. I argue that this (...) has consequences for theorising about norms of other speech acts and generates certain arbitrary divisions. In the central part, I analyse two groups of speech acts. Firstly, ordinary speech acts, like predictions or retractions. Secondly, I indicate how the normative view can be extended to so-called ancillary speech acts, like presuppositions or implicatures. I end with a discussion of possible extensions of the normative approach, focusing on the debate on lying. (shrink)

In Molière’s comedy The Imaginary Invalid a doctor “explains” that opium reliably induces sleep because it has a “dormitive virtue.” Molière intended this to be a satirical play on the use of opaque scholastic concepts in medicine, and since then the phrase “dormitive virtue” has become a byword for explanatory failure. However, contemporary work on the metaphysics of grounding and dispositions appears to permit explanations with a strikingly similar structure. In this paper I explore competing verdicts on dormitive virtue explanation, (...) using a model of explanation I call Contextualist Pluralist Non-Realist Backing, or CPN Backing. I show that CPN Backing illuminates the puzzle about dormitive virtue explanation, shows what is required for a resolution, and makes sense of conflicting responses to this case. (shrink)

Antirealism about metaphysical explanation is relatively underexplored. This paper maps out the territory for the antirealist, explaining what it would take to be an antirealist given various different conceptions of metaphysical explanation, and of the relationship between metaphysical explanation and grounding.

Wir Menschen streben danach, die Wirklichkeit zu verstehen. Eine Welt, die wir gut verstehen, ist eine, die wir "im Griff" haben, mit der wir gut umgehen können. Aber was heißt es genau, ein Phänomen der Wirklichkeit zu verstehen? Wie sieht unser Weltbild aus, wenn wir ein Phänomen verstanden haben? Welche Bedingungen müssen erfüllt sein, damit Verstehen gelingt? Die Kernthese des Buches ist, dass wir Phänomene der Wirklichkeit durch noetische Integration verstehen. Wir verstehen Phänomene, indem wir den entsprechenden Informationseinheiten eine sinnvolle (...) und angemessene Position in unserem Weltbild zuschreiben und insofern unser Weltbild in gewissem Maße der Wirklichkeit entspricht. (shrink)

I begin by retracing an argument from Aristotle for final causes in science. Then, I advance this ancient thought, and defend an argument for a stronger conclusion: that no scientific explanation can succeed, if Naturalism is true. The argument goes like this: (1) Any scientific explanation can be successful only if it crucially involves a natural regularity. Next, I argue that (2) any explanation can be successful only if it crucially involves no element that calls out for explanation but lacks (...) one. From (1) and (2) it follows that (3) a scientific explanation can be successful only if it crucially involves a natural regularity, and this regularity does not call out for explanation while lacking one. I then argue that (4) if Naturalism is true, then all natural regularities call out for explanation but lack them. From (3) and (4) it follows that (5) if Naturalism is true, then no scientific explanation can be successful. If you believe that scientific explanation can be (indeed, often has been) successful, as I do, then this is a reason to reject Naturalism. (shrink)

Contemporary debate surrounding the nature of scientific progress has focused upon the precise role played by justification, with two realist accounts having dominated proceedings. Recently, however, a third realist account has been put forward, one which offers no role for justification at all. According to Finnur Dellsén’s (Stud Hist Philos Sci Part A 56:72–83, 2016) noetic account, science progresses when understanding increases, that is, when scientists grasp how to correctly explain or predict more aspects of the world that they could (...) before. In this paper, we argue that the noetic account is severely undermotivated. Dellsén provides three examples intended to show that understanding can increase absent the justification required for true belief to constitute knowledge. However, we demonstrate that a lack of clarity in each case allows for two contrasting interpretations, neither of which serves its intended purpose. On the first, the agent involved lacks both knowledge and understanding; and, on the second, the agent involved successfully gains both knowledge and understanding. While neither interpretation supports Dellsén’s claim that understanding can be prised apart from knowledge, we argue that, in general, agents in such cases ought to be attributed neither knowledge nor understanding. Given that the separability of knowledge and understanding is a necessary component of the noetic account, we conclude that there is little support for the idea that science progresses through increasing understanding rather than the accumulation of knowledge. (shrink)

A traditional account of coincidences has it that two facts are coincidental whenever they are not related as cause and effect and do not have a common cause. A recent contribution by Lando : 132–151, 2017) showed that this account is mistaken. In this paper, I argue against two alternative accounts of coincidences, one suggested by Lando, and another by Bhogal : 677–694, 2020), and defend a third one in their place. In short, I propose that how explanatory links relate (...) to non-coincidental facts in explanation is what drives a wedge between coincidences and non-coincidences. This proposal is not susceptible to the worries I raise, and is more general, since it is not restricted to coincidences and non-coincidences involving physical facts. (shrink)

The main purpose of this dissertation is to examine critically and discuss the role of imagination in science and religion, with particular emphasis on its possible epistemic, creative, and meaning-making functions. In order to answer my research questions, I apply theories and concepts from contemporary philosophy of mind on scientific and religious practices. This framework allows me to explore the mental state of imagination, not as an isolated phenomenon but, rather, as one of many mental states that co-exist and interplay (...) in our cogntive architecture. Based on the philosophical discourse of philosophy of mind, four types of imagination are indentified and conceptualized: sensory, propositional, experiential, and creative imagination. These categories are then employed on five phenomena that can be found in scientific and religious environments: metaphors, models, thought experiments, aspect perception, and - in the religious case - rituals. In relation to the concept of religious "seeing" I consider how imaginings may influence visionary experiences and visualization, and compare these phenomena with cases of scientific visualization and eureka experiences. In regard to scientific and religious models, a distinction is made between, on the one hand, two notions of truth and, on the other hand, truth-independent meaning-making. In light of these categories, I differentiate between, and critically discuss, the use of imagination in doxastic, non-doxastic and fictionalist accounts. In light of this investigation, I formulate and defend the position of interactivism, which acknowledges a constant interplay between different attitudes and mental states. In my examination of rituals and scientific and religious thought experiments, special attention is given to the mental capacity to recreate the experiences that are entailed in an imagined scenario. At the end of the investigation, I consider the possible impact that my study might have on how we view science and religion as well as the dialogue bewteen these two fields. (shrink)

This thesis is a philosophical examination of the explanatory roles of diagnoses in psychiatry. In medicine, diagnoses normally serve as causal explanations of patients’ symptoms. Given that psychiatry is a discipline whose practice is shaped by medical traditions, it is often implied that its diagnoses also serve such explanatory functions. This is evident in clinical texts that portray psychiatric diagnoses as referring to diseases that cause symptoms. However, there are problems which cast doubt on whether such portrayals are justified. I (...) address these problems and examine whether psychiatric diagnoses provide explanations of symptoms. The first problem is conceptual. In diagnostic manuals, psychiatric diagnoses are defined by their symptoms. This suggests that invoking them as explanations of the symptoms amounts to circularity. I argue that this can be resolved with an appropriate conceptual framework that captures the complex semantic values of diagnostic terms and their different uses in clinical discourse. I put forward such a framework based on two-dimensional semantics. The second problem is ontological. Empirical research suggests that diagnostic categories in psychiatry do not correspond to invariant causal types, but are associated with variable combinations of diverse causes that interact across biological, psychological, and social levels. Given this heterogeneity, I argue that psychiatric diagnoses fall short of paradigmatic cases of causal explanation, but that some can still provide other sorts of useful causal explanatory information. The original contribution of this thesis is the illumination of the conceptual relations between diagnoses and symptoms. This philosophical work is important, because it can be brought to valuable application in modifying psychiatric practice. (shrink)

We argue that artificial networks are explainable and offer a novel theory of interpretability. Two sets of conceptual questions are prominent in theoretical engagements with artificial neural networks, especially in the context of medical artificial intelligence: Are networks explainable, and if so, what does it mean to explain the output of a network? And what does it mean for a network to be interpretable? We argue that accounts of “explanation” tailored specifically to neural networks have ineffectively reinvented the wheel. In (...) response to, we show how four familiar accounts of explanation apply to neural networks as they would to any scientific phenomenon. We diagnose the confusion about explaining neural networks within the machine learning literature as an equivocation on “explainability,” “understandability” and “interpretability.” To remedy this, we distinguish between these notions, and answer by offering a theory and typology of interpretation in machine learning. Interpretation is something one does to an explanation with the aim of producing another, more understandable, explanation. As with explanation, there are various concepts and methods involved in interpretation: Total or Partial, Global or Local, and Approximative or Isomorphic. Our account of “interpretability” is consistent with uses in the machine learning literature, in keeping with the philosophy of explanation and understanding, and pays special attention to medical artificial intelligence systems. (shrink)

Modalists think that knowledge requires forming your belief in a “modally stable” way: using a method that wouldn't easily go wrong, or using a method that wouldn't have given you this belief had it been false. Recent Modalist projects from Justin Clarke-Doane and Dan Baras defend a principle they call “Modal Security,” roughly: if evidence undermines your belief, then it must give you a reason to doubt the safety or sensitivity of your belief. Another recent Modalist project from Carlotta Pavese (...) and Bob Beddor defends “Modal Virtue Epistemology”: knowledge is a belief that is maximally modally robust across “normal” worlds. We'll offer new objections to these recent Modalist projects. We will then argue for a rival view, Explanationism: knowing something is believing it because it's true. We will show how Explanationism offers a better account of undermining defeaters than Modalism, and a better account of knowledge. (shrink)

Priority Theory is an increasingly popular view in metaphysics. By seeing metaphysical questions as primarily concerned with what explains what, instead of merely what exists, it promises not only an interesting approach to traditional metaphysical issues but also the resolution of some outstanding disputes. In a recent paper, Louis deRosset argues that Priority Theory isn’t up to the task: Priority Theory is committed to there being explanations that violate a formal constraint on any adequate explanation. This paper critically examines deRosset’s (...) challenge to Priority Theory. We argue that deRosset’s challenge ultimately fails: his proposed constraint on explanation is neither well-motivated nor a general constraint. Nonetheless, lurking behind his criticism is a deep problem for prominent ways of developing Priority Theory, a problem which we develop. (shrink)

In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies will (...) lack a well-defined goal. Aside from providing a clearer objective for XAI, focusing on understanding also allows us to relax the factivity condition on explanation, which is impossible to fulfill in many machine learning models, and to focus instead on the pragmatic conditions that determine the best fit between a model and the methods and devices deployed to understand it. After an examination of the different types of understanding discussed in the philosophical and psychological literature, I conclude that interpretative or approximation models not only provide the best way to achieve the objectual understanding of a machine learning model, but are also a necessary condition to achieve post hoc interpretability. This conclusion is partly based on the shortcomings of the purely functionalist approach to post hoc interpretability that seems to be predominant in most recent literature. (shrink)

This paper develops and motivates a unification theory of metaphysical explanation, or as I will call it, Metaphysical Unificationism. The theory’s main inspiration is the unification account of scientific explanation, according to which explanatoriness is a holistic feature of theories that derive a large number of explananda from a meager set of explanantia, using a small number of argument patterns. In developing Metaphysical Unificationism, I will point out that it has a number of interesting consequences. The view offers a novel (...) conception of metaphysical explanation that doesn’t rely on the notion of a “determinative” or “explanatory” relation; it allows us to draw a principled distinction between metaphysical and scientific explanations; it implies that naturalness and fundamentality are distinct but intimately related notions; and perhaps most importantly, it re-establishes the unduly neglected link between explanation and understanding in the metaphysical realm. A number of objections can be raised against the view, but I will argue that none of these is conclusive. The upshot is that Metaphysical Unificationism provides a powerful and hitherto overlooked alternative to extant theories of metaphysical explanation. (shrink)

What features will something have if it counts as an explanation? And will something count as an explanation if it has those features? In the second half of the 20th century, philosophers of science set for themselves the task of answering such questions, just as a priori conceptual analysis was generally falling out of favor. And as it did, most philosophers of science just moved on to more manageable questions about the varieties of explanation and discipline-specific scientific explanation. Often, such (...) shifts are sound strategies for problem-solving. But leaving fallow certain basic conceptual issues can also result in foundational debates. (shrink)

Can mathematics contribute to our understanding of physical phenomena? One way to try to answer this question is by getting involved in the recent philosophical dispute about the existence of mathematical explanations of physical phenomena. If there is such a thing, given the relation between explanation and understanding, we can say that there is an affirmative answer to our question. But what if we do not agree that mathematics can play an explanatory role in science? Can we still consider that (...) the above question can have an affirmative answer? My main aim here is to give an account that takes mathematics, in some of the cases discussed in the literature, as contributing to our understanding of physical phenomena despite not being explanatory. (shrink)

According to manipulationist accounts of causal explanation, to explain an event is to show how it could be changed by intervening on its cause. The relevant change must be a ‘serious possibility’ claims Woodward 2003, distinct from mere logical or physical possibility—approximating something I call ‘scientific possibility’. This idea creates significant difficulties: background knowledge is necessary for judgments of possibility. Yet the primary vehicles of explanation in manipulationism are ‘invariant’ generalisations, and these are not well adapted to encoding such knowledge, (...) especially in the social sciences, as some of it is non-causal. Ceteris paribus (CP) laws or generalisations labour under no such difficulty. A survey of research methods such as case and comparative studies, randomised control trials, ethnography, and structural equation modeling, suggests that it would be more difficult and in some instances impossible to try to represent the output of each method in invariant generalisations; and that this is because in each method causal and non-causal background knowledge mesh in a way that cannot easily be accounted for in manipulationist terms. Ceteris paribus-generalisations being superior in this regard, a theory of explanation based on the latter is a better fit for social science. (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)

Language is a human universal reflecting our deeply social nature. Among its essential functions, language enables us to quickly and efficiently share information. We tell each other that many things are true—that is, we routinely make assertions. Information shared this way plays a critical role in the decisions and plans we make. In Knowledge and the Norm of Assertion, a distinguished philosopher and cognitive scientist investigates the rules or norms that structure our social practice of assertion. Combining evidence from philosophy, (...) psychology, and biology, John Turri shows that knowledge is the central norm of assertion and explains why knowledge plays this role. -/- Concise, comprehensive, non-technical, and thoroughly accessible, this volume quickly brings readers to the cutting edge of a major research program at the intersection of philosophy and science. It presupposes no philosophical or scientific training. It will be of interest to philosophers and scientists, is suitable for use in graduate and undergraduate courses, and will appeal to general readers interested in human nature, social cognition, and communication. (shrink)

Traditionally, a scientific model is thought to provide a good scientific explanation to the extent that it satisfies certain scientific goals that are thought to be constitutive of explanation. Problems arise when we realize that individual scientific models cannot simultaneously satisfy all the scientific goals typically associated with explanation. A given model’s ability to satisfy some goals must always come at the expense of satisfying others. This has resulted in philosophical disputes regarding which of these goals are in fact necessary (...) for explanation, and as such which types of models can and cannot provide explanations. Explanatory monists argue that one goal will be explanatory in all contexts, while explanatory pluralists argue that the goal will vary based on pragmatic considerations. In this paper, I argue that such debates are misguided, and that both monists and pluralists are incorrect. Instead of any goal being given explanatory priority over others in a given context, the different goals are all deeply dependent on one another for their explanatory power. Any model that sacrifices some explanatory goals to attain others will always necessarily undermine its own explanatory power in the process. And so when forced to choose between individual scientific models, there can be no explanatory victors. Given that no model can satisfy all the goals typically associated with explanation, no one model in isolation can provide a good scientific explanation. Instead we must appeal to collections of models. Collections of models provide an explanation when they satisfy the web of interconnected goals that justify the explanatory power of one another. (shrink)

Many think that sentences about what metaphysically explains what are true iff there exist grounding relations. This suggests that sceptics about grounding should be error theorists about metaphysical explanation. We think there is a better option: a theory of metaphysical explanation which offers truth conditions for claims about what metaphysically explains what that are not couched in terms of grounding relations, but are instead couched in terms of, inter alia, psychological facts. We do not argue that our account is superior (...) to grounding-based accounts. Rather, we offer it to those already ill-disposed towards grounding. (shrink)

Many philosophers embrace grounding, supposedly a central notion of metaphysics. Grounding is widely assumed to be irreflexive, but recently a number of authors have questioned this assumption: according to them, it is at least possible that some facts ground themselves. The primary purpose of this paper is to problematize the notion of self-grounding through the theoretical roles usually assigned to grounding. The literature typically characterizes grounding as at least playing two central theoretical roles: a structuring role and an explanatory role. (...) Once we carefully spell out what playing these roles includes, however, we find that any notion of grounding that isn’t irreflexive fails to play these roles when they are interpreted narrowly, and is redundant for playing them when they are interpreted more broadly. The upshot is that no useful notion of grounding can allow a fact to ground itself. (shrink)

Scientific explanations must bear the proper relationship to the world: they must depict what, out in the world, is responsible for the explanandum. But explanations must also bear the proper relationship to their audience: they must be able to create human understanding. With few exceptions, philosophical accounts of explanation either ignore entirely the relationship between explanations and their audience or else demote this consideration to an ancillary role. In contrast, I argue that considering an explanation’s communicative role is crucial to (...) any satisfactory account of explanation. (shrink)

We might think that thought experiments are at their most powerful or most interesting when they produce new knowledge. This would be a mistake; thought experiments that seek understanding are just as powerful and interesting, and perhaps even more so. A growing number of epistemologists are emphasizing the importance of understanding for epistemology, arguing that it should supplant knowledge as the central notion. In this chapter, I bring the literature on understanding in epistemology to bear on explicating the different ways (...) that thought experiments increase three important kinds of understanding: explanatory, objectual and practical. (shrink)

This is an introduction to the volume "Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations", edited by A. Reutlinger and J. Saatsi (OUP, forthcoming in 2017). -/- Explanations are very important to us in many contexts: in science, mathematics, philosophy, and also in everyday and juridical contexts. But what is an explanation? In the philosophical study of explanation, there is long-standing, influential tradition that links explanation intimately to causation: we often explain by providing accurate information about the causes of the (...) phenomenon to be explained. Such causal accounts have been the received view of the nature of explanation, particularly in philosophy of science, since the 1980s. However, philosophers have recently begun to break with this causal tradition by shifting their focus to kinds of explanation that do not turn on causal information. The increasing recognition of the importance of such non-causal explanations in the sciences and elsewhere raises pressing questions for philosophers of explanation. What is the nature of non-causal explanations - and which theory best captures it? How do non-causal explanations relate to causal ones? How are non-causal explanations in the sciences related to those in mathematics and metaphysics? This volume of new essays explores answers to these and other questions at the heart of contemporary philosophy of explanation. The essays address these questions from a variety of perspectives, including general accounts of non-causal and causal explanations, as well as a wide range of detailed case studies of non-causal explanations from the sciences, mathematics and metaphysics. (shrink)

Explanatory realism is the position that all explanations give information about whatever metaphysically determines the explanandum. This view is popular and plays a central role in metaphysics, but in this paper I argue that explanatory realism is false. In Sect. 1 I introduce explanatory realism in its weak and strong versions, and discuss the argumentative work that explanatory realism is used for in contemporary metaphysics. In Sect. 2 I present a series of problem cases for explanatory realism, including explanation by (...) analogy, explanations involving rules, reduction ad absurdum explanations and certain statistical explanations. In Sect. 3 I consider and reject two modified versions of explanatory realism: the position that explanatory realism is true only of explanation in metaphysics, and the position that determinative explanation is the most complete form of explanation. In conclusion I consider explanatory antirealism and explanatory pluralism as alternatives to explanatory realism. (shrink)

It is commonly assumed that grounding relations are asymmetric. Here I develop and argue for a theory of metaphysical structure that takes grounding to be nonsymmetric rather than asymmetric. Even without infinite descending chains of dependence, it might be that every entity is grounded in some other entity. Having first addressed an immediate objection to the position under discussion, I introduce two examples of symmetric grounding. I give three arguments for the view that grounding is nonsymmetric (I call this view (...) ‘metaphysical interdependence’). These arguments are: (i) that metaphysical interdependence is the only theory able to reconcile competing intuitions about grounding; (ii) that it is the only theory consistent with both ‘gunk’ and ‘junk’; and (iii) that offers a satisfactory solution to the problem concerning whether or not grounding is itself grounded. (shrink)

In recent years, metaphysics has undergone what some describe as a revolution: it has become standard to understand a vast array of questions as questions about grounding, a metaphysical notion of determination. Why should we believe in grounding, though? Supporters of the revolution often gesture at what I call the Argument from Explanatoriness: the notion of grounding is somehow indispensable to a metaphysical type of explanation. I challenge this argument and along the way develop a “reactionary” view, according to which (...) there is no interesting sense in which the notion of grounding is explanatorily indispensable. I begin with a distinction between two conceptions of grounding, a distinction which extant critiques of the revolution have usually failed to take into consideration: grounding qua that which underlies metaphysical explanation and grounding qua metaphysical explanation itself. Accordingly, I distinguish between two versions of the Argument from Explanatoriness: the Unexplained Explanations Version for the first conception of grounding, and the Expressive Power Version for the second. The paper’s conclusion is that no version of the Argument from Explanatoriness is successful. (shrink)

In this dissertation, I argue that understanding possesses unique epistemic value. I propose and defend a novel account of understanding that I call the management account of understanding, which is the view that an agent A understands a subject matter S just in case A has the ability to extract the relevant information and exploit it with the relevant cognitive capacities to answer questions in S. Since inquiry is the process of raising and answering questions, I argue that without understanding, (...) it would be impossible to engage in successful inquiry. I argue that understanding is indispensable for effective cognition and that it is irreducible to other epistemic categories, such as knowledge, justification, or rationality. Understanding is an irreducible component of epistemic excellence. In arguing for this account, I focus on the nature and requirements of cognition and pay less attention to intuitions about hypothetical cases, in contrast to previous approaches to understanding. I draw upon psychology and cognitive science, especially work on the frame problem, to demonstrate the importance (and difficulty) of finding relevant information and exploiting it in relevant ways to answer questions. One’s cognitive system must be organized in such a way that one has the ability to think the relevant thoughts in the relevant ways to answer the relevant questions. This reveals well-defined directions in which future research on understanding should move. In addition to proposing and defending the management account of understanding, I explore several features of understanding, including some interesting consequences of the management account. I argue that the management account and commonly used methods of measuring degrees of understanding imply that understanding can be based on false beliefs. I argue that the management account (and any account of understanding that implies understanding is an ability) implies that understanding can be acquired by luck. I also argue that understanding is ontologically prior to explanation: a good explanation is essentially an act that produces understanding in the relevant cognitive background. (shrink)

In the recent philosophy of explanation, a growing attention to and discussion of non-causal explanations has emerged, as there seem to be compelling examples of non-causal explanations in the sciences, in pure mathematics, and in metaphysics. I defend the claim that the counterfactual theory of explanation (CTE) captures the explanatory character of both non-causal scientific and metaphysical explanations. According to the CTE, scientific and metaphysical explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the explanans. I (...) support this claim by illustrating that CTE is applicable to Euler’s explanation (an example of a non-causal scientific explanation) and Loewer’s explanation (an example of a non-causal metaphysical explanation). (shrink)

In pedagogical contexts and in everyday life, we often come to believe something because it would best explain the data. What is it about the explanatory endeavor that makes it essential to everyday learning and to scientific progress? There are at least two plausible answers. On one view, there is something special about having true explanations. This view is highly intuitive: it’s clear why true explanations might improve one’s epistemic position. However, there is another possibility—it could be that the process (...) of seeking, generating, or evaluating explanations itself puts one in a better epistemic position, even when the outcome of the process is not a true explanation. In other words, it could be that accurate explanations are beneficial, or it could be that high-quality explaining is beneficial, where there is something about the activity of looking for an explanation that improves our epistemic standing. The main goal of this paper is to tease apart these two possibilities, both theoretically and empirically, which we align with “Inference to the Best Explanation” and “Explaining for the Best Inference”, respectively. We also provide some initial support for EBI and identify promising directions for future research. (shrink)

The goal of this paper is to develop a counterfactual theory of explanation. The CTE provides a monist framework for causal and non-causal explanations, according to which both causal and non-causal explanations are explanatory by virtue of revealing counterfactual dependencies between the explanandum and the explanans. I argue that the CTE is applicable to two paradigmatic examples of non-causal explanations: Euler’s explanation and renormalization group explanations of universality.

I use a contrastive theory of causal explanation to analyze the notion of a genetic trait. The resulting definition is relational, an implication of which is that no trait is genetic always and everywhere. Rather, every trait may be either genetic or non-genetic, depending on explanatory context. I also outline some other advantages of connecting the debate to the wider causation literature, including how that yields us an account of the distinction between genetic traits and genetic dispositions.

I propose and defend the hypothesis that understanding is the norm of explanation. On this proposal, an explanation should express understanding. I call this the understanding account of explanation. The understanding account is supported by social and introspective observations. It is also supported by the relationship between knowledge and understanding, on the one hand, and assertion and explanation, on the other.

Philosophical work on explanation has focused on the following two topics: theories of explanation, intended to enumerate necessary and sufficient conditions for explanation, and inference to the best explanation as the strongest form of justification for ontological or metaphysical claims. I critically examine the most important philosophical work in both of these areas and defend my own conclusions about the connections between explanation and ontology. I argue that all of our inferences about the nature of the world, in ontology or (...) metaphysics, presuppose criteria for acceptable explanation. I first examine the metaphysics of Plato, Aristotle, and Leibniz, arguing that their metaphysical reasoning was guided by assumptions about the nature of explanation. I also survey some recent work in ontology and find inference to the best explanation offered as the strongest available method of defending existence claims. To conclude this discussion, I offer an original argument for the thesis that all reasoning about existence claims, being nondeductive, presupposes some criteria for acceptable explanations, or a theory of explanation. Carl Hempel and Wesley Salmon have been two of the most influential philosophers offering theories of explanation, and I examine their work with the intention of discovering ontological or metaphysical assumptions shaping their theories of explanation. I argue that Hempel's theory rests on deterministic assumptions, and I argue the Salmon's theory of causality, which he admits supports his theory of explanation, is subject to empiricist criticisms. Theories of explanation typically rest on assumptions about the nature of the world, I argue, and I explain why this is so with an original theory of explanation connecting it to the psychological phenomenon of understanding. We rely on understanding in the identification of explanations, and understanding requires establishing a metaphysical context for an explanandum-event. I end by indicating the possibility of generating vicious justificatory circles through the reciprocal relationship of support between explanation and ontology, and I argue that vicious circles can be avoided only by grounding all ontological reasoning in a fundamental explanatory task of giving order to experience through a system of categories. (shrink)

By briefly reviewing three well-known scientific revolutions in fundamental physics (the discovery of inertia, of special relativity and of general relativity), I claim that problems that were supposed to be crying for a dynamical explanation in the old paradigm ended up receiving a structural explanation in the new one. This claim is meant to give more substance to Kuhn’s view that revolutions are accompanied by a shift in what needs to be explained, while suggesting at the same time the existence (...) of a pattern that is common to all of the discussed case-studies. It remains to be seen whether also quantum mechanics, in particular entanglement, conforms to this pattern. (shrink)

Do multi-level selection explanations of the evolution of social traits deepen the understanding provided by single-level explanations? Central to the former is a mathematical theorem, the multi-level Price decomposition. I build a framework through which to understand the explanatory role of such non-empirical decompositions in scientific practice. Applying this general framework to the present case places two tasks on the agenda. The first task is to distinguish the various ways of suppressing within-collective variation in fitness, and moreover to evaluate their (...) biological interest. I distinguish four such ways: increasing retaliatory capacity, homogenising assortment, and collapsing either fitness structure or character distribution to a mean value. The second task is to discover whether the third term of the Price decomposition measures the effect of any of these hypothetical interventions. On this basis I argue that the multi-level Price decomposition has explanatory value primarily when the sharing-out of collective resources is `subtractable'. Thus its value is more circumscribed than its champions Sober and Wilson (1998) suppose. (shrink)

Even with the lack of consensus on the nature of an argument, the thesis that explanations and arguments are distinct is near orthodoxy in well-known critical thinking texts and in the more advanced argumentation literature. In this paper, I reconstruct two rationales for distinguishing arguments from explanations. According to one, arguments and explanations are essentially different things because they have different structures. According to the other, while some explanations and arguments may have the same structure, they are different things because (...) explanations are used for different purposes than arguments. I argue that both rationales fail to motivate a distinction between arguments and explanations. Since these are the only rationales for distinguishing arguments from explanations that I am prepared to take seriously, I don’t see why we should exclude explanations from being arguments. (shrink)

This paper describes one style of functional analysis commonly used in the neurosciences called task-bound functional analysis. The concept of function invoked by this style of analysis is distinctive in virtue of the dependence relations it bears to transient environmental properties. It is argued that task-bound functional analysis cannot explain the presence of structural properties in nervous systems. An alternative concept of neural function is introduced that draws on the theoretical neuroscience literature, and an argument is given to show that (...) this alternative concept of may help to overcome the explanatory limitations of task-bound functional analysis. (shrink)

The Linda paradox is a key topic in current debates on the rationality of human reasoning and its limitations. We present a novel analysis of this paradox, based on the notion of verisimilitude as studied in the philosophy of science. The comparison with an alternative analysis based on probabilistic confirmation suggests how to overcome some problems of our account by introducing an adequately defined notion of verisimilitudinarian confirmation.

Defenders of pragmatic encroachment in epistemology (or what I call practicalism) need to address two main problems. First, the view seems to imply, absurdly, that knowledge can come and go quite easily—in particular, that it might come and go along with our variable practical interests. We can call this the stability problem. Second, there seems to be no fully satisfying way of explaining whose practical interests matter. We can call this the “whose stakes?” problem. I argue that both problems can (...) be addressed in roughly the same terms. More exactly, I argue that by first clarifying the whose stakes? problem an answer to the stability problem naturally falls out. (shrink)

The ontic conception of scientific explanation has been constructed and motivated on the basis of a putative lexical ambiguity in the term explanation. I raise a puzzle for this ambiguity claim, and then give a deflationary solution under which all ontically-rendered talk of explanation is merely elliptical; what it is elliptical for is a view of scientific explanation that altogether avoids the ontic conception. This result has revisionary consequences for New Mechanists and other philosophers of science, many of whom have (...) assimilated their conception of explanation to the ontic conception. (shrink)

Epistemologists have recently debated whether understanding is a species of knowledge. However, because they have offered little in the way of a detailed analysis of understanding, they lack the resources to resolve this issue. In this paper, I propose that S understands why p if and only if S has the non-Gettierised true belief that p, and for some proposition q, S has the non-Gettierised true belief that q is the best available explanation of p, S can correctly explain p (...) with q, and S can identify the features that make q the best explanation of p. On this analysis, understanding is reducible to knowing that p and that q is the best available explanation of p. (shrink)