The Gettier Problem is the problem of revising the view that knowledge is justified true belief in a way that is immune to Gettier counter-examples. The “Gettier Problem problem”, according to Lycan, is the problem of saying what is misguided about trying to solve the Gettier Problem. In this paper I take up the Gettier Problem problem. I distinguish giving conditions that are necessary and sufficient for knowledge from giving conditions that explain why one knows when one does know. I (...) argue that the problem with the Gettier Problem is that it requires us to articulate conditions that suffice for knowledge even if those conditions are non-explanatory. After defending this view, I take up two related methodological issues, one about the evidence that can be given in favor of an account of knowledge, and one about the role that investigating justification might play in investigating knowledge. (shrink)

In an attempt to improve upon Alexander Pruss’s work (The principle of sufficient reason: A reassessment, pp. 240–248, 2006), I (Weaver, Synthese 184(3):299–317, 2012) have argued that if all purely contingent events could be caused and something like a Lewisian analysis of causation is true (per, Lewis’s, Causation as influence, reprinted in: Collins, Hall and paul. Causation and counterfactuals, 2004), then all purely contingent events have causes. I dubbed the derivation of the universality of causation the “Lewisian argument”. The Lewisian (...) argument assumed not a few controversial metaphysical theses, particularly essentialism, an incommunicable-property view of essences (per Plantinga’s, Actualism and possible worlds, reprinted in: Davidson (ed.) Essays in the metaphysics of modality, 2003), and the idea that counterfactual dependence is necessary for causation. There are, of course, substantial objections to such theses. While I think a fight against objections to the Lewisian argument can be won, I develop, in what follows, a much more intuitive argument for the universality of causation which takes as its inspiration a result from Frederic B. Fitch’s work (J Symb Logic 28(2):135–142, 1963) [with credit to who we now know was Alonzo church’s, Referee Reports on Fitch’s Definition of value, in: (Salerno (ed.), New essays on the knowability paradox, 2009)] that if all truths are such that they are knowable, then (counter-intuitively) all truths are known. The resulting Church–Fitch proof for the universality of causation is preferable to the Lewisian argument since it rests upon far weaker formal and metaphysical assumptions than those of the Lewisian argument. (shrink)

In this paper, I will first clarify Lewis’s influence theory of causation by relying on his theory of events. And then I will consider Michael Strevens’s charge against the sufficiency of Lewis’s theory. My claim is that it is legitimate but does not pose as serious a problem for Lewis’s theory as Strevens thinks because Lewis can surmount it by limiting the scope of his theory to causation between concrete events. Michael Strevens raises an alleged counterexample to the necessity of (...) Lewis’s theory that, if successful, would have a very important advantage over other alleged counterexamples. But I will assert that it is simply mistaken. My defense of Lewis’s theory will shed interesting light on the relationship between Lewis’s theory and Salmon’s mark theory. (shrink)

In this paper I examine Salmon's response to two counterexamples to his conserved quantity (CQ) theory of causation. The first counterexample that I examine involves a time‐wise gerrymandered world line of a series of patches of wall that is absorbing energy as a result of being illuminated in an astrodome. Salmon says that since the gerrymandered world line does not fulfill his “no‐interaction requirement,” his CQ theory does not suffer from the counterexample. But I will argue that his response fails (...) both at a theoretical level and at a practical level. In so doing I point out a problem for CQ theorists' definition of a causal interaction. The second counterexample is concerned with a time‐wise gerrymandered world line of a series of patches that are in shadow, in Hitchcock's well‐known example. Salmon's response is based on a principle that Salmon thinks is derivable from the concept of a conserved quantity. However, I argue that the principle has a counterexample. (shrink)

I argue for a subsumption of any version of Grice’s first quantity maxim posited to underlie scalar implicature, by developing the idea of implicature recovery as a kind of explanatory inference, as e.g. in science. I take the applicable model to be contrastive explanation, while following van Fraassen’s analysis of explanation as an answer to a why-question. A scalar implicature is embedded in such an answer, one that meets two probabilistic constraints: the probability of the answer, and ‘favoring’. I argue (...) that besides having application at large, outside of linguistic interpretation, these constraints largely account not only for implicatures based on strength order, logical and otherwise, but also for unordered cases. I thus suggest that Grice’s maxim and its descendants are expressions of general explanatory constraints, as they happen to be manifested in this particular explanatory task. I conclude by briefly discussing how I accordingly view Grice’s system outside of scalar implicature. (shrink)

The intuition of the naı¨ve realist, miracle arguments notwithstanding, is countered forcefully by a host of considerations, including the possibility of underdetermination, and criticisms of abductive inferences to explanatory hypotheses. Some have suggested that an induction may be performed, from the perspective of present theories, on their predecessors. Past theories are thought to be false, strictly speaking; it is thus likely that present-day theories are also false, and will be taken as such at an appropriate future time.

Judea Pearl has argued that counterfactuals and causality are central to intelligence, whether natural or artificial, and has helped create a rich mathematical and computational framework for formally analyzing causality. Here, we draw out connections between these notions and various current issues in cognitive science, including the nature of mental “programs” and mental representation. We argue that programs (consisting of algorithms and data structures) have a causal (counterfactual-supporting) structure; these counterfactuals can reveal the nature of mental representations. Programs can also (...) provide a causal model of the external world. Such models are, we suggest, ubiquitous in perception, cognition, and language processing. (shrink)

Minimally, causal realism (as understood here) is the view that accounts of causation in terms of mere, regular or probabilistic conjunction are unsatisfactory, and that causal phenomena are correctly associated with some form of de re necessity. Classic arguments, however, some of which date back to Sextus Empiricus and have appeared many times since, including famously in Russell, suggest that the very notion of causal realism is incoherent. In this paper I argue that if such objections seem compelling, it is (...) only because everyday expressions concerning causal phenomena are misleading with respect to certain metaphysical details. These expressions generally make reference to the relations of events or states of affairs, but ignore or obscure the role played by causal properties. I argue that on a proposed alternative, an analysis in terms of causal processes, more refined descriptions of causal phenomena escape the charge of incoherence. Causal necessity is here located in the relations of causal properties. I distinguish this view from the recent process theories of Salmon and Dowe, which are disinterested in causal realism. (shrink)

Philosophers of the social sciences are increasingly convinced that macro-and micro-explanations are complementary. Whereas macro-explanations are broad, micro-explanations are deep. I distinguish between weak and strong complementarity: Strongly complementary explanations improve one another when integrated, weakly complementary explanations do not. To demonstrate the explanatory autonomy of different levels of explanation, explanatory pluralists mostly presuppose the weak form of complementarity. By scrutinizing the notions of explanatory depth and breadth, I argue that macro- and micro-accounts of the same phenomenon are more often (...) strongly complementary. This invites a revision of the pluralist position in which integration promotes explanatory progress. (shrink)

I propose a deductive-nomological model for mathematical scientific explanation. In this regard, I modify Hempel’s deductive-nomological model and test it against some of the following recent paradigmatic examples of the mathematical explanation of empirical facts: the seven bridges of Königsberg, the North American synchronized cicadas, and Hénon-Heiles Hamiltonian systems. I argue that mathematical scientific explanations that invoke laws of nature are qualitative explanations, and ordinary scientific explanations that employ mathematics are quantitative explanations. I analyse the repercussions of this deductivenomological model (...) on causal explanations. (shrink)

Philosophers of science take it as a datum that Mayor John's having syphilis explains why he, rather than certain nonsyphilitics, had paresis. Using a new hypothetical example, the case of the two dams, it is argued that three independent considerations invalidate these philosophers' starting point.

This paper defends the need for evidential diversity and the mix of methods that that can in train require. The focus is on causal claims, especially ‘singular’ claims about the effects of causes in a specific setting—either what will happen or what has happened. I do so by offering a template that categorises kinds of evidence that can support these claims. The catalogue is generated by considering what needs to happen for a causal process to carry through from putative cause (...) at the start to the targeted effect at the end. The usual call for mixed methods focusses on a single overall claim and argues that we increase certainty by the use of different methods with compensating strengths and weaknesses. My proposals instead focus on the evidence that supports the great many subsidiary claims that must hold if the overall one is to be true. As is typical for singular causal claims, the mix of methods that will generally be required to collect the kinds of evidence I urge will usually have little claim to the kind of rigour that is now widely demanded in evidencing causal claims, especially those for policy/treatment effectiveness. So I begin with an exploration of what seems to be intended by ‘rigour’ in such discussions, since it is seldom made clear just what makes the favoured methods especially rigorous. I then argue that the emphasis on rigour can be counterproductive. Rigour is often the enemy of evidential diversity, and evidential diversity—lots of it—can make for big improvements in the reliability of singular causal predictions and post hoc evaluations. I illustrate with the paragon of rigour for causal claims, randomised controlled trials (RCTs), rehearsing at some length what they can and cannot do to make it easier to assess the importance of rigour in warranting singular causal claims. (shrink)

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

Reductive intellectualists about knowledge-how hold, contra Ryle, that knowing how to do something is just a kind of propositional knowledge. In a similar vein, traditional reductivists about understanding-why insist, in accordance with a tradition beginning with Aristotle, that the epistemic standing one attains when one understands why something is so is itself just a kind of propositional knowledge—viz., propositional knowledge of causes. A point that has been granted on both sides of these debates is that if these reductive proposals are (...) right, then knowledge-how and understanding-why should be susceptible to the same extent as knowledge-that is to being undermined by epistemic luck. This paper reports experimental results that test these luck-based predictions. Interestingly, these results suggest a striking positive correlation between self-reported philosophical expertise and attributions of knowledge-how, understanding-why and knowledge-that which run contrary to reductive proposals. We contextualize these results by showing how they align very well with a particular kind of overarching non-reductive proposal, one that two of the authors have defended elsewhere according to which knowledge-how and understanding-why, but not knowledge-that, essentially involve cognitive achievement. We conclude by situating the interpretive narrative advanced within contemporary discussions about the role of expertise in philosophical judgment. (shrink)

Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal knowledge is necessary for (...) the project, both as a source for handling complexity and as an output for meeting the project’s goals. Consequently, I argue that data-driven claims about causality are fundamentally flawed and causal knowledge should be considered a necessary aspect of Big Data science. In addition, I present the consequences of this result on other data-driven claims, concerning the role of theoretical considerations. I argue that the importance of causal knowledge and other kinds of theoretical engagement in EXPOsOMICS undermine theory-free accounts and suggest alternative ways of framing science based on Big Data. (shrink)

I set out two theses. The first is Lynn Robertson’s: (a) spatial awareness is a cause of object perception. A natural counterpoint is: (b) spatial awareness is a cause of your ability to make accurate verbal reports about a perceived object. Zenon Pylyshyn has criticized both. I argue that nonetheless, the burden of the evidence supports both (a) and (b). Finally, I argue conscious visual perception of an object has a different causal role to both: (i) non-conscious perception of the (...) object, and (ii) experience, e.g. hallucination, that may be subjectively indiscriminable from, but is not, perception of the object. (shrink)

This article focuses on the assessment of mechanistic relations with specific attention to medicine, where mechanistic models are widely employed. I first survey recent contributions in the philosophical literature on mechanistic causation, and then take issue with Federica Russo and Jon Williamson’s thesis that two types of evidence, probabilistic and mechanistic, are at stake in the health sciences. I argue instead that a distinction should be drawn between previously acquired knowledge of mechanisms and yet-to-be-discovered knowledge of mechanisms and that both (...) probabilistic evidence and manipulation are essential with respect to newly discovered mechanisms. (shrink)

Este trabajo propone una herramienta teórica con la que es posible comparar diferentes explicaciones dirigidas a un mismo objeto de estudio. Esta herramienta se compone de tres conjuntos de virtudes: epistémicas, analíticas y pragmáticas. Para apoyar lo anterior se ofrecen dos estudios de caso, el primero compara dos explicaciones psicológicas sobre el espectro autista, el segundo compara dos explicaciones sobre el origen de los números desde una perspectiva empirista.

Much of ordinary memory is autobiographical; memory of what one saw and did, where and when. It may derive from your own past experiences, or from what other people told you about your past life. It may be phenomenologically rich, redolent of that autumn afternoon so long ago, or a few austere reports of what happened. But all autobiographical memory is first-person memory, stateable using ‘I’. It is a memory you would express by saying, ‘I remember I . . .’.

This contribution claims that the two fundamental notions of causation at work in the health sciences are manipulative and mechanistic, and investigates what kinds of evidence matter for the assessment of causal relations. This article is a development of our 2007 article, ‘Plurality of Causality’, where we argue for a pluralistic account of causation with an eye to econometrics and a single medical example. The present contribution has a wider focus, and considers the notion of evidence within a whole range (...) of disciplines belonging to the health sciences. Section 1 addresses the relations between kinds of evidence and causal accounts, and it is shown how different notions of causation can be employed in various medical cases. Section 2 calls attention to issues crucial for any adequate epistemological theory of causation, such as the distinctions between types and tokens, observational and experimental regimes, explanation and prediction. Lastly, the notion of context is articulated, highlighted in its role in the assessment of causal links. All these issues are tackled in the framework of what we label a ‘bottom–up’ epistemology. (shrink)

Riassunto: Il dibattito in filosofia della mente è caratterizzato dal crescente interesse per nuove forme di eliminativismo, note con il nome di teorie enattiviste radicali della mente. Secondo la concezione enattivista radicale, il contenuto intenzionale di uno stato mentale è empiricamente sottodeterminato, pertanto non può essere utilizzato quale elemento di una spiegazione naturalistica del comportamento. Tuttavia, sebbene il riferimento ai contenuti intenzionali non sia conciliabile con il naturalismo ontologico, esso è invece compatibile con una forma di naturalismo metodologico. Seguendo l’analisi (...) semantica proposta da Carnap per i termini teorici, è possibile concepire uno stato mentale come un veicolo simbolico il cui significato è stabilito per mezzo di osservazioni e scelte convenzionali. Attraverso un caso di studio riguardante le funzioni cognitive della corteccia somatosensoriale, l’articolo fornisce le indicazioni programmatiche per un’interpretazione delle spiegazioni intenzionali del comportamento in accordo con la metodologia delle scienze naturali. Parole chiave: Contenuto mentale; Enattivismo radicale; Intenzionalità; Naturalismo; Teleosemantica; Teoria della spiegazione T he Methodological Status of Intentional Contents: The philosophy of mind debate is characterized by increasing consensus regarding a new type of eliminativism, also known as the radical enactivist theory of mind. According to the radical enactivist view, the intentional content of a mental state is empirically undetermined, therefore it cannot figure as part of a naturalistic explanation of behavior. However, although the notion of intentional content is not compatible with any form of ontological naturalism, it is compatible with a form of methodological naturalism. Following Carnap’s semantic analysis of theoretical concepts, it is possible to conceive of intentional mental states as a symbolic vehicles whose meaning can be conventionally established on the basis of empirical observation. In order to support this claim, I refer to a case study on the cognitive functions of somatosensory cortex. This article provides arguments for building an intentional explanation of behavior based on methodological approaches in the natural sciences. Keywords: Mental Content; Radical Enactivism; Intentionality; Naturalism; Teleosemantics; Theory of Explanation. (shrink)

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

In this paper, I consider the relationship between Inference to the Best Explanation and Bayesianism, both of which are well-known accounts of the nature of scientific inference. In Sect. 2, I give a brief overview of Bayesianism and IBE. In Sect. 3, I argue that IBE in its most prominently defended forms is difficult to reconcile with Bayesianism because not all of the items that feature on popular lists of “explanatory virtues”—by means of which IBE ranks competing explanations—have confirmational import. (...) Rather, some of the items that feature on these lists are “informational virtues”—properties that do not make a hypothesis \ more probable than some competitor \ given evidence E, but that, roughly-speaking, give that hypothesis greater informative content. In Sect. 4, I consider as a response to my argument a recent version of compatibilism which argues that IBE can provide further normative constraints on the objectively correct probability function. I argue that this response does not succeed, owing to the difficulty of defending with any generality such further normative constraints. Lastly, in Sect. 5, I propose that IBE should be regarded, not as a theory of scientific inference, but rather as a theory of when we ought to “accept” H, where the acceptability of H is fixed by the goals of science and concerns whether H is worthy of commitment as research program. In this way, IBE and Bayesianism, as I will show, can be made compatible, and thus the Bayesian and the proponent of IBE can be friends. (shrink)

I discuss the idea of relativistic causality, i.e., the requirement that causal processes or signals can propagate only within the light-cone. After briefly locating this requirement in the philosophy of causation, my main aim is to draw philosophers' attention to the fact that it is subtle, indeed problematic, in relativistic quantum physics: there are scenarios in which it seems to fail. I set aside two such scenarios, which are familiar to philosophers of physics: the pilot-wave approach, and the Newton-Wigner representation. (...) I instead stress two unfamiliar scenarios: the Drummond-Hathrell and Scharnhorst effects. These effects also illustrate a general moral in the philosophy of geometry: that the mathematical structures, especially the metric tensor, that represent geometry get their geometric significance by dint of detailed physical arguments. (shrink)

I compare deterministic and stochastic hidden variable models of the Bell experiment, exphasising philosophical distinctions between the various ways of combining conditionals and probabilities. I make four main claims. (1) Under natural assumptions, locality as it occurs in these models is equivalent to causal independence, as analysed (in the spirit of Lewis) in terms of probabilities and conditionals. (2) Stochastic models are indeed more general than deterministic ones. (3) For factorizable stochastic models, relativity's lack of superluminal causation does not favour (...) locality over completeness. (4) If we prohibit all superluminal causation, then the violation of the Bell inequality teaches us a lesson, besides quantum mechanics' familiar ones that quantities can lack precise values and that pairs of quantities can lack joint probabilities: namely, some pairs of events are not screened off by their common past. (shrink)

Enhanced indispensability arguments claim that Scientific Realists are committed to the existence of mathematical entities due to their reliance on Inference to the best explanation. Our central question concerns this purported parity of reasoning: do people who defend the EIA make an appropriate use of the resources of Scientific Realism to achieve platonism? We argue that just because a variety of different inferential strategies can be employed by Scientific Realists does not mean that ontological conclusions concerning which things we should (...) be Scientific Realists about are arrived at by any inferential route which eschews causes, and nor is there any direct pressure for Scientific Realists to change their inferential methods. We suggest that in order to maintain inferential parity with Scientific Realism, proponents of EIA need to give details about how and in what way the presence of mathematical entities directly contribute to explanations. (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)

Explainable artificial intelligence (XAI) seeks to produce explanations for those machine learning methods which are deemed opaque. However, there is considerable disagreement about what this means and how to achieve it. Authors disagree on what should be explained (topic), to whom something should be explained (stakeholder), how something should be explained (instrument), and why something should be explained (goal). In this paper, I employ insights from means-end epistemology to structure the field. According to means-end epistemology, different means ought to be (...) rationally adopted to achieve different epistemic ends. Applied to XAI, different topics, stakeholders, and goals thus require different instruments. I call this the means-end account of XAI. The means-end account has a descriptive and a normative component: on the one hand, I show how the specific means-end relations give rise to a taxonomy of existing contributions to the field of XAI; on the other hand, I argue that the suitability of XAI methods can be assessed by analyzing whether they are prescribed by a given topic, stakeholder, and goal. (shrink)

In the debate on causal explanation in biology, in the past two decades largely influenced by the new mechanist approach, the concept of a pathway has recently reemerged as a promising research agenda, 551-572, 2018; The British Journal for the Philosophy of Science, 72, 131-158, 2021). Ross’ account of biological explanation differentiates several autonomous types of causal structures that play explanatory and other roles across the life sciences. NM, however, prioritizes mechanisms as vehicles of biological explanations. According to this program, (...) the causal architecture of biological pathways and other causal structures, such as cascades and processes, can be interpreted with at least one of the NM’s mechanism concepts. In other words, these alternative causal structures are not sufficiently distinctive to merit the explanatory autonomy with regard to the NM corresponding concepts. We examine the explanatory practice of molecular biology and concur with Ross that there are indeed distinct types of causal structures, not all falling under the concept of a mechanism. Nonetheless, we show that the concept of mechanism is referring to a privileged causal structure, at the center of explanatory efforts in molecular biology. Pathways and other causal concepts, while somewhat distinct from mechanisms themselves, are explanatorily relevant to the degree in which they exhibit mechanistic features, are parts of a mechanistic architecture, or may lead to a mechanistic arrangement. What emerges in that manner is a hierarchy of causal structures with mechanisms at the explanatory top, and lower levels differing in the degree in which they contribute to mechanistic arrangements. (shrink)

This paper aims to better motivate the naturalization of metaphysics by identifying and criticizing a class of theories I call ’free range metaphysics’. I argue that free range metaphysics is epistemically inadequate because the constraints on its content—consistency, simplicity, intuitive plausibility, and explanatory power—are insufficiently robust and justificatory. However, since free range metaphysics yields clarity-conducive techniques, incubates science, and produces conceptual and formal tools useful for scientifically engaged philosophy, I do not recommend its discontinuation. I do recommend, however, ending the (...) discipline’s bad faith. That is, I urge that free range metaphysics not be taken to have fully satisfactory epistemic credentials over and above its pragmatic ones. (shrink)

Quine, taking the molecular constitution of matter as a paradigmatic example, offers an account of the relation between theory confirmation and ontology. Elsewhere, he deploys a similar ontological methodology to argue for the existence of mathematical objects. Penelope Maddy considers the atomic/molecular theory in more historical detail. She argues that the actual ontological practices of science display a positivistic demand for “direct observation,” and that fulfillment of this demand allows us to distinguish molecules and other physical objects from mathematical abstracta. (...) However, the confirmation of the atomic/molecular theory and the development of scientists’ ontological attitudes towards atoms was more complicated and subtle than even Maddy supposes. The present paper argues that the history of the theory in fact supports neither Quine’s and Maddy’s accounts of scientific ontology. There was no general demand from scientists to “see” atoms before they were reckoned to be real; but neither did the indispensable appearance of atoms in the best theory of chemical combination suffice to convince scientists of their reality. (shrink)

Contributing to the recent debate on whether or not explanations ought to be differentiated from arguments, this article argues that the distinction matters to science education. I articulate the distinction in terms of explanations and arguments having to meet different standards of adequacy. Standards of explanatory adequacy are important because they correspond to what counts as a good explanation in a science classroom, whereas a focus on evidence-based argumentation can obscure such standards of what makes an explanation explanatory. I provide (...) further reasons for the relevance of not conflating explanations with arguments (and having standards of explanatory adequacy in view). First, what guides the adoption of the particular standards of explanatory adequacy that are relevant in a scientific case is the explanatory aim pursued in this context. Apart from explanatory aims being an important aspect of the nature of science, including explanatory aims in classroom instruction also promotes students seeing explanations as more than facts, and engages them in developing explanations as responses to interesting explanatory problems. Second, it is of relevance to science curricula that science aims at intervening in natural processes, not only for technological applications, but also as part of experimental discovery. Not any argument enables intervention in nature, as successful intervention specifically presupposes causal explanations. Students can fruitfully explore in the classroom how an explanatory account suggests different options for intervention. (shrink)

We show that five important elements of the ‘nomological package’— laws, counterfactuals, chances, dispositions, and counterfactuals—needn’t be a problem for the Growing-Block view. We begin with the framework given in Briggs and Forbes (in The real truth about the unreal future. Oxford studies in metaphysics. Oxford University Press, Oxford, 2012 ), and, taking laws as primitive, we show that the Growing-Block view has the resources to provide an account of possibility, and a natural semantics for non-backtracking causal counterfactuals. We show (...) how objective chances might ground a more fine-grained concept of feasibility, and furnished a places in the structure where causation and dispositions might fit. The Growing-Block view, thus understood, provides the resources to explain the close link between modality and tense, so that it predicts modal change as time passes. This account lets us capture not only what the future might hold for us, and also what might have been. (shrink)

This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and causal-mechanistic), a joint study of discovery and explanation, and an abandonment of models of theory reduction in favor of accounts of explanatory reduction. Of particular current interest are philosophical accounts of complex explanations that appeal (...) to different levels of organismal organization and use contributions from different biological disciplines. The essay lays out one model that views explanatory integration across different disciplines as being structured by scientific problems. I emphasize the philosophical need to take the explanatory aims pursued by different groups of scientists into account, as explanatory aims determine whether different explanations are competing or complementary and govern the dynamics of scientific practice, including interdisciplinary research. I distinguish different kinds of pluralism that philosophers have endorsed in the context of explanation in biology, and draw several implications for science education, especially the need to teach science as an interdisciplinary and dynamic practice guided by scientific problems and explanatory aims. (shrink)

I argue against a priori objections to the view that causation may be reducible to some micro-structural process in principle discoverable by physics. I distinguish explanation from causation, and argue that the main objections to such a reduction stem from conflating these two notions. Explanation is the collection of pragmatically relevant, possibly counterfactual information about causation; and causation is to be identified in a necessary a posteriori way with whatever physical processes underwrite our explanatory claims.

Sober and Elgin defend the claim that there are a priori causal laws in biology. Lange and Rosenberg take issue with this on Humean grounds, among others. I will argue that Sober and Elgin don’t go far enough – there are a priori causal laws in many sciences. Furthermore, I will argue that this thesis is compatible with a Humean metaphysics and an empiricist epistemology.

If there is content that we reason on, cognitive content, it is in the head and accessible to reasoning mechanisms. This paper discusses the phenomenal theory of cognitive content, according to which cognitive contents are the contents of phenomenal consciousness. I begin by distinguishing cognitive content from the closely associated notion of narrow content. I then argue, drawing on prior work, that the phenomenal theory can plausibly account for the cognitive contents of many relatively simple mental states. My main focus (...) in this paper is the question whether the phenomenal theory can account for the apparently abstract and complex cognitive contents of "high-level" thoughts. It might seem dubious that the theory can account for such cognitive contents, because cognitive phenomenology is too scarce and too thin. However, I argue there are in fact few abstract or complex cognitive contents, so the phenomenal theory's predictions are correct. This position explains some apparently irrational behavior that is otherwise hard to explain, and it makes sense of the central role of inner speech and other forms of consciousness in reasoning. (shrink)

La notion d'objet physique est au cceur de la problématique métaphysique du réalisme: réalistes et antiréalistes construisent habituellement leurs positions sur la base de différentes conceptions de cette notion. De façon générale, les réalistes prétendent que les objets physiques existent et possè-dent des propriétés intrinsèques les définissant indépendamment de nos facultés de perception et de conceptualisation. Par rapport à cette caractérisation, qui nous accompagnera tout au long du texte, nous nous plaçons dans le clan des antiréalistes. Toutefois, notre but présent (...) n'est pas tant de critiquer la conception réaliste de l'objet physique que de proposer les grandes lignes d'une forme d'antiréalisme cohérente. Pour nous situer dans le débat contemporain nous contrasterons nos idées avec le réalisme interne de Putnam et le phénoménalisme, deux positions qui se rapprochent de la nôtre par leur réjet de la notion réaliste d'objet physique. Cependant, le réalisme interne et le phénoménalisme, nous le verrons, prennent souvent la forme de thèses portant sur le langage, ce que nous voudrons éviter de faire. II est à notre avis avantageux, pour répondre à la question qui sert de titre à ce texte, de ramener le débat en deçà des questions de langage, au niveau de la perception non épistémique, oùl'on peut encore, selon les termes de Dretske, voir sans croire. (shrink)

To give a causal explanation is to give information about causal history. But a vast amount of causal history lies behind anything that happens, far too much to be included in any intelligible explanation. This is the Problem of Limitation for explanatory information. To cope with this problem, explanations must select for what is relevant to and adequate for answering particular inquiries. In the present paper this idea is used in order to distinguish two kinds of causal explanation, on the (...) grounds of systematic differences in their conditions of relevance and adequacy. It is further argued that these two forms of causal explanation are interdependent and their interaction provides an instrument through which causal knowledge is acquired and enhanced. What we understand causation in the world to be is neither unconditioned regularity, nor counterfactual dependence, but the sum of correct answers to explanatory inquiries of these two interdependent kinds. (shrink)

RESUMO Os debates sobre o Realismo Científico não só tiveram um começo e um desenvolvimento contemporâneos aos do Realismo Modal e Realismo Nomológico, mas suas temáticas estiveram também profundamente entrelaçadas. Certa atitude realista em relação às teorias científicas tem sido muitas vezes acompanhada pela adoção de compromissos com a modalidade objetiva e as leis naturais. No entanto, as relações entre estas três posições têm sido pouco exploradas. Neste artigo defendo que manter o RC indiretamente envolve assumir compromissos com o RM (...) e o RN. No primeiro caso, por causa dos argumentos que dão suporte ao RC; no segundo, uma vez que, dentro das alternativas disponíveis no debate sobre as leis, o RN é comparativamente melhor para o realista científico. ABSTRACT Debates on scientific realism not only had a beginning and contemporary developments before those on Modal Realism and on Nomological Realism, also their thematics were deeply entangled. Some realist attitude regarding other scientific theories has many times been followed by the adoption of commitments with an objective modality and the natural laws. Nevertheless, the relations among these three positions have been little explored. In this article I hold that keeping SR indirectly means committing to MR and NR. In the first case, because of the arguments supporting SR, in the second case, once within the options available in the debate on the laws, NR is - by comparison - better for the scientific realism. (shrink)

A widespread need to explain the behavior and outcomes of AI-based systems has emerged, due to their ubiquitous presence. Thus, providing renewed momentum to the relatively new research area of eXplainable AI (XAI). Nowadays, the importance of XAI lies in the fact that the increasing control transference to this kind of system for decision making -or, at least, its use for assisting executive stakeholders- already affects many sensitive realms (as in Politics, Social Sciences, or Law). The decision-making power handover to (...) opaque AI systems makes mandatory explaining those, primarily in application scenarios where the stakeholders are unaware of both the high technology applied and the basic principles governing the technological solutions. The issue should not be reduced to a merely technical problem; the explainer would be compelled to transmit richer knowledge about the system (including its role within the informational ecosystem where he/she works). To achieve such an aim, the explainer could exploit, if necessary, practices from other scientific and humanistic areas. The first aim of the paper is to emphasize and justify the need for a multidisciplinary approach that is beneficiated from part of the scientific and philosophical corpus on Explaining, underscoring the particular nuances of the issue within the field of Data Science. The second objective is to develop some arguments justifying the authors’ bet by a more relevant role of ideas inspired by, on the one hand, formal techniques from Knowledge Representation and Reasoning, and on the other hand, the modeling of human reasoning when facing the explanation. This way, explaining modeling practices would seek a sound balance between the pure technical justification and the explainer-explainee agreement. (shrink)