According to David Chalmers, the hard problem of consciousness consists of explaining how and why qualitative experience arises from physical states. Moreover, Chalmers argues that materialist and reductive explanations of mentality are incapable of addressing the hard problem. In this chapter, I suggest that Chalmers’ hard problem can be usefully distinguished into a ‘how question’ and ‘why question,’ and I argue that evolutionary biology has the resources to address the question of why qualitative experience arises from brain states. From this (...) perspective, I discuss the different kinds of evolutionary explanations (e.g., adaptationist, exaptationist, spandrel) that can explain the origins of the qualitative aspects of various conscious states. This argument is intended to clarify which parts of Chalmers’ hard problem are amenable to scientific analysis. (shrink)

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.

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)

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)

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)

Scientists and laypeople alike use the sense of understanding that an explanation conveys as a cue to good or correct explanation. Although the occurrence of this sense or feeling of understanding is neither necessary nor sufficient for good explanation, it does drive judgments of the plausibility and, ultimately, the acceptability, of an explanation. This paper presents evidence that the sense of understanding is in part the routine consequence of two well-documented biases in cognitive psychology: overconfidence and hindsight. In light of (...) the prevalence of counterfeit understanding in the history of science, I argue that many forms of cognitive achievement do not involve a sense of understanding, and that only the truth or accuracy of an explanation make the sense of understanding a valid cue to genuine understanding. (shrink)

Over the last several years a number of leading philosophers – including Catherine Elgin, Linda Zagzebski, Jonathan Kvanvig, and Duncan Pritchard – have grown increasingly dissatisfied with the contemporary focus on knowledge in epistemology and have attempted to “recover” the notion of understanding. According to some of these philosophers, in fact, understanding deserves not just to be recovered, but to supplant knowledge as the focus of epistemological inquiry. This entry considers some of the main reasons why philosophers have taken understanding (...) to be more valuable than knowledge, focusing on claims that it is more transparent, that it better reflects or mirrors the world, and that it is a greater intellectual achievement. (shrink)

This paper challenges the appeal to theory virtues in theory choice as well as the appeal to the intellectual and moral virtues of an agent as determining unique choices between empirically equivalent theories. After arguing that theoretical virtues do not determine the choice of one theory at the expense of another theory, I argue that nor does the appeal to intellectual and moral virtues single out one agent, who defends a particular theory, and exclude another agent defending an alternative theory. (...) I analyse Duhem’s concept of good sense and its recent interpretation in terms of virtue epistemology. I argue that the virtue epistemological interpretation does not show how good sense leads to conclusive choices and scientific progress. (shrink)

How can philosophy of science be of more practical use? One thing we can do is provide practicable advice about how to determine when one empirical claim is relevant to the truth of another; i.e., about evidential relevance. This matters especially for evidence-based policy, where advice is thin—and misleading—about how to tell what counts as evidence for policy effectiveness. This paper argues that good efficacy results (as in randomized controlled trials), which are all the rage now, are only a very (...) small part of the story. To tell what facts are relevant for judging policy effectiveness, we need to construct causal scenarios about will happen when the policy is implemented. (shrink)

Selection explanations explain some non-accidental generalizations in virtue of a selection process. Such explanations are not particulaizable - they do not transfer as explanations of the instances of such generalizations. This is unlike many explanations in the physical sciences, where the explanation of the general fact also provides an explanation of its instances (i.e. standard D-N explanations). Are selection explanations (e.g. in biology) therefore a different kind of explanation? I argue that to understand this issue, we need to see that (...) a standard D-N explanation of some non-accidental generalization (al Fs are Gs) may also ipso facto explain its contrapositive (all non-Gs are non-Fs), but the explanation is particularizable with respect to the former but not to the latter. This can be seen by noting that the Raven Paradox counterexample to the H-D model of confirmation also generates a counterexample to the D-N model of explanation (all ravens are black does not explain why the non-black shoe is a non-raven). In such cases it is natural to take the generalization with the positive predicates to have a particularizable explanation. However, this need not be the case, and in selection explanations it is the generalization with the positive predicates whose explanation is no particularizable. Thus there is no need to suppose that selection explanations are fundamentally different. (shrink)

The pragmatic theory of explanation is an attempt to see explanation as a linguistic response to a cognitive problem where the content of the response depends on the context of the scientific inquiry. The present paper draws on the rhetorical situation, as it is defined by Loyld Bitzer, in order to understand how the context may influence the content as well as the acceptability of the response.

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)

How do why-interrogatives work? How do they express the questions they express, in the contexts in which they express them? In this essay, I argue that, at a fundamental level, why-interrogatives work just like other wh-interrogatives, particularly other adjunct wh-interrogatives, and they express the questions they express, in the contexts in which they express them, by the same means that other wh-interrogatives do. These conclusions go against a trend in recent work on why-interrogatives, which holds that they are syntactically and (...) semantically unlike other wh-interrogatives. Since the claim that why-interrogatives are unlike other wh-interrogatives has been taken to support various philosophical theses about the nature of why-questions and explanation, showing that why-interrogatives are just like other wh-interrogatives undermines this line of support for these theses. (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)

In this paper I assume that we have some intuitive knowledge—i.e. beliefs that amount to knowledge because they are based on intuitions. The question I take up is this: given that some intuition makes a belief based on it amount to knowledge, in virtue of what does it do so? We can ask a similar question about perception. That is: given that some perception makes a belief based on it amount to knowledge, in virtue of what does it do so? (...) A natural idea about perception is that a perception makes a belief amount to knowledge in part by making you sensorily aware of the concrete objects it is about. The analogous idea about intuition is that an intuition makes a belief amount to knowledge in part by making you intellectually aware of the abstract objects it is about. I expand both ideas into fuller accounts of perceptual and intuitive knowledge, explain the main challenge to this sort of account of intuitive knowledge (i.e. the challenge of making sense of intellectual awareness), and develop a response to it. (shrink)

Can phenomenal consciousness be given a reductive natural explanation? Exponents of an.

The paper is an examination of the ways and extent to which neuroscience places constraints on cognitive science. In Part I, I clarify the issue, as well as the notion of levels in cognitive inquiry. I then present and address, in Part II, two arguments designed to show that facts from neuroscience are at a level too low to constrain cognitive theory in any important sense. I argue, to the contrary, that there are several respects in which facts from neurophysiology (...) will constrain cognitive theory. Part III then turns to an examination of Connectionism and Classical Cognitivism to determine which, if either, is in a better position to accomodate neural constraints in the ways suggested in Part II. (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)

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)

Ernst Mayr’s concept of dual causality in biology with the two forms of causes continues to provide an essential foundation for the philosophy of biology. They are equivalent to functional and evolutionary causes with both required for full biological explanations. The natural sciences can be classified into nomological, historical nomological and historical dual causality, the last including only biology. Because evolutionary causality is unique to biology and must be included for all complete biological explanations, biology is autonomous from the physical (...) sciences. (shrink)

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

In this paper I examine two aspects of Hempel’s covering-law models of explanation. These are (i) nomic subsumption and (ii) explication by models. Nomic subsumption is the idea that to explain a fact is to show how it falls under some appropriate law. This conception of explanation Hempel explicates using a pair of models, where, in this context, a model is a template or pattern such that if something fits it, then that thing is an explanation. A range of well-known (...) counter-examples to Hempel’s models has led his successors to seek alternatives. Problems with limited amendments have encouraged some theorists of explanation to abandon nomic subsumption. So, in particular, causal components have come to be regarded as essential, even though Hempel had intended his model to capture causal explanation as well.1 Here I want to examine the prospects for retaining nomic subsumption by rejecting the other feature of Hempel’s approach – explication by models. An examination of the counter-examples will suggest that it is a mistake to imagine that a limited quantity of information about laws and antecedent conditions will be able to provide an actual explanation – other information, about explanations, may be relevant. This in turn leads me to examine what I shall call structural approaches. They are structural because the status of something as an explanation depends on its fitting into a structure of explanations. There are two structural approaches I shall examine. One is holistic – it proposes that we consider explanation hand-in-hand with the concept of law. This account of explanation inherits its holistic nature from the holistic (or sys- tematic) character of laws of nature. The second supervenience view I shall consider is not global as the holistic approach is. Instead it concentrates on the ‘vertical’ structure of explanations, whereby the existence of a nomic explanation at one level reflects explanations on lower levels on which it supervenes. These structural approaches were first proposed in Bird Synthese 120: 1–18, 1999. © 1999 Kluwer Academic Publishers.. (shrink)

Is the nature of explanation a metaphysical issue? Or has it more to do with psychology and pragmatics? To put things in a different way: what are primary relata in an explanation? What sorts of thing explain what other sorts of thing? David Lewis identifies two senses of ‘explanation’ (Lewis 1986, 217–218). In the first sense, an explanation is an act of explaining. I shall call this the subjectivist sense, since its existence depends on some subject doing the explaining. Hence (...) it is people who, in this sense, explain things. In the second of his two senses, Lewis says, quoting Sylvain Bromberger, that one may properly ask of an explanation “Does anyone know it? Who thought of it first? Is it very complicated?” (Lewis 1986, 218; Bromberger 1965). In this second sense, no subject is needed, the explanation can remain unknown, perhaps for ever. So I call this the objectivist sense. (shrink)

In a situation in which several explanations compete, is the one that is better qua explanation also the one we should regard as the more likely to be true? Realists usually answer in the affirmative. They then go on to argue that since realism provides the best explanation for the success of science, realism can be inferred to. Nonrealists, on the other hand, answer the above question in the negative, thereby renouncing the inference to realism. In this paper I separate (...) the two issues. In the first section it is argued that a rationale can be provided for the inference to the best explanation; in the second, that this rationale cannot justify an inference to realism. The defence of the inference rests on the claim that our standards of explanatory power are subject to critical examination, which, in turn, should be informed by empirical considerations. By means of a comparison of the realist's explanation for the success of science with that of conventionalism and instrumentalism it is then shown that realism does not offer a superior explanation and should not, therefore, be inferred to. (shrink)

The notion of a severe test has played an important methodological role in the history of science. But it has not until recently been analyzed in any detail. We develop a generally Bayesian analysis of the notion, compare it with Deborah Mayo’s error-statistical approach by way of sample diagnostic tests in the medical sciences, and consider various objections to both. At the core of our analysis is a distinction between evidence and confirmation or belief. These notions must be kept separate (...) if mistakes are to be avoided; combined in the right way, they provide an adequate understanding of severity. Those who think that the weight of the evidence always enables you to choose between hypotheses “ignore one of the factors (the prior probability) altogether, and treat the other (the likelihood) as though it ...meant something other than it actually does. This is the same mistake as is made by someone who has scruples about measuring the arms of a balance (having only a tape measure at his disposal ...), but is willing to assert that the heavier load will always tilt the balance (thereby implicitly assuming, although without admitting it, that the arms are of equal length!). (Bruno de Finetti, Theory of Probability)2. (shrink)

I argue that standard explanationist solutions to the problem of creeping minimalism are largely on the right track, but they fail to correctly specify the kind of explanation that is relevant to distinguishing realism from quasirealism. Quasirealism should not be distinguished from realism in terms of the explanations it gives of why a normative judgment—a normative sentence or attitude—has the semantic content that it has. Rather, it should be distinguished in terms of the explanations it offers of what the semantic (...) content of a normative judgment is. (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)

’s glue logic for computing logical form dynamic. This allows us to model a dialogue agent’s understanding of what the update of the semantic representation of the dialogue would be after his next contribution, including the effects of the rhetorical moves that he is contemplating performing next. This is a pre-requisite for developing a model of how agents reason about what to say next. We make the glue logic dynamic by using a dynamic public announcement logic ( pal ). We (...) extend pal with a particular variety of default reasoning suited to reasoning about discourse—this default reasoning being an essential component of inferring the pragmatic effects of one’s dialogue moves. We add to the pal language a new type of announcement, known as ceteris paribus announcement, and this is used to model how an agent anticipates the (default) pragmatic effects of his next dialogue move. Our extended pal validates certain intuitive patterns of default inference that existing pal s for practical reasoning do not. We prove that the dynamic glue logic has a pspace validity problem, and as such is no more complex than pal with multiple $${\square}$$ operators. (shrink)

We defend deflationism about truth against a pressing challenge, which is to explain how deflationists can understand the role that the _concept_ of truth appears to play in accounts of several other philosophically important concepts. We provide three strategies that deflationists can employ in response to the specific challenge regarding assertion that has been raised in several recent articles, viz., that the truth concept plays an ineliminable explanatory role in an account of assertion. We then show how to extend our (...) strategies to accounts of other central philosophical concepts, by applying them to accounts of belief, knowledge, and logical validity. The result is a set of recipes for deflationists about truth to employ in developing responses to worries that might be raised about the explanatory role of the truth concept. (shrink)

The widely accepted view states that an intention to deceive is not necessary for lying. Proponents of this view, the so-called non-deceptionists, argue that lies are simply insincere assertions. We conducted three experimental studies with false explanations, the results of which put some pressure on non-deceptionist analyses. We present cases of explanations that one knows are false and compare them with analogical explanations that differ only in having a deceptive intention. The results show that lay people distinguish between such false (...) explanations and to a higher degree classify as lies those explanations that are made with the intention to deceive. Non-deceptionists fail to distinguish between such cases and wrongly classify both as lies. This novel empirical finding indicates the need for supplementing non-deceptionist definitions of lying, at least in some cases, with an additional condition, such as an intention to deceive. (shrink)

This paper investigates the conception of causation required in order to make sense of natural selection as a causal explanation of changes in traits or allele frequencies. It claims that under a counterfactual account of causation, natural selection is constituted by the causal relevance of traits and alleles to the variation in traits and alleles frequencies. The “statisticalist” view of selection (Walsh, Matthen, Ariew, Lewens) has shown that natural selection is not a cause superadded to the causal interactions between individual (...) organisms. It also claimed that the only causation at work is those aggregated individual interactions, natural selection being only predictive and explanatory, but it is implicitly committed to a process-view of causation. I formulate a counterfactual construal of the causal statements underlying selectionist explanations, and show that they hold because of the reference they make to ecological reliable factors. Considering case studies, I argue that this counterfactual view of causal relevance proper to natural selection captures more salient features of evolutionary explanations than the statisticalist view, and especially makes sense of the difference between selection and drift. I eventually establish equivalence between causal relevance of traits and natural selection itself as a cause. (shrink)

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

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)

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)

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 tremendous philosophical focus on how to characterize explanatory metaphysical dependence has eclipsed a number of other unresolved issued about scientific explanation. The purpose of this paper is taxonomical. I will outline a number of other questions about the nature of explanation and its role in science—eight, to be precise—and argue that each is independent. All of these topics have received some philosophical attention, but none nearly so much as it deserves. Furthermore, existing views on these topics have been obscured (...) by not distinguishing among these independent questions and, especially, by not separating them from the question of what metaphysical dependence relation is explanatory. Philosophical analysis of scientific explanation would be much improved by attending more carefully to these, and probably still other, elements of an account of explanation. (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)

Argues that there is no interpretation of the commonly-accepted idea that "explanation is that which produces understanding" on which it is of any use for finding what philosophers looking for a theory of explanation have been after. Contains a close examination of a couple of philosophers' attempts to use this idea for that purpose.

Um dos grandes desafios da era da informação consiste em filtrar informações claras, rigorosas e atualizadas sobre tópicos importantes. O mesmo vale para a filosofia. Como encontrar conteúdo filosófico confiável em meio a milhares de artigos publicados diariamente na internet? Para ir ainda mais longe, como encontrar uma introdução a algum tópico com uma lista de referências bibliográficas atualizadas e que seja organizada por um especialista da área? Já que você começou a ler este livro, é provável que tenha ouvido (...) falar em algum momento da Enciclopédia Stanford de Filosofia, disponível gratuitamente na internet desde 1995. A página da Stanford faz exatamente isso. Ela cobre inúmeros verbetes sobre quase tudo em filosofia, oferecendo informação confiável sobre temas como feminismo, filosofia na América Latina, zumbis, metafísica e milhares de outros tópicos. A sugestão típica aos profissionais da filosofia que têm interesse em começar a estudar algum tópico, mas não sabem sequer por onde começar, é procurar pelo verbete relevante da Stanford. Infelizmente, o grande empecilho da página para o nosso contexto é que todos os verbetes estão disponíveis apenas em inglês, algo que cria um obstáculo a inúmeros estudantes e interessados que não dominam a língua. Neste sentido, acreditamos que esta publicação preencha um hiato importante na filosofia brasileira. Embora a filosofia no Brasil tenha se profissionalizado e expandido ao longo dos anos, há ainda lacunas em diversas áreas, e os verbetes foram aqui selecionados cuidadosamente no intuito de preencher ao menos algumas dessas lacunas. Este livro apresenta quatro verbetes cruciais para a filosofia, aqui divididos em quatro capítulos: (1) condições necessárias e suficientes, (2) referência (3) causação e (4) consciência. (shrink)

Complex systems are to be seen as typically having multiple levels of organization. For instance, in the behavioural and cognitive sciences, there has been a long lasting trend, promoted by the seminal work of David Marr, putting focus on three distinct levels of analysis: the computational level, accounting for the What and Why issues, the algorithmic and the implementational levels specifying the How problem. However, the tremendous developments in neuroscience knowledge about processes at different scales of organization together with the (...) complexity of today cognitive theories suggest that there will hardly be only three levels of explanation. Instead, there will be many different degrees of commitments corresponding to the different granularities—from high-level (behavioural) models to low-level (neural and molecular) models of the cognitive research program. For instance, Bayesian approaches, that are usually advocated for formalizing Marr’s computational level and rational behaviour, have even been adopted to model synaptic plasticity and axon guidance by molecular gradients. As a result, we can consider the behavioural scientist as dealing with models at a multiplicity of levels. The purpose of this Research Topic in Frontiers in Theoretical and Philosophical Psychology is to promote an approach to the role of the levels and explanation and models which is of interest for cognitive scientists, neuroscientists, psychologists, behavioural scientists, and philosophers of science. (shrink)