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

We argue that there is no general theory of explanation that spans the sciences, mathematics, and ethics, etc. More specifically, there is no good reason to believe that substantive and domain-invariant constraints on explanatory information exist. Using Nickel (Noûs 44(2):305–328, 2010 ) as an exemplar of the contrary, generalist position, we first show that Nickel’s arguments rest on several ambiguities, and then show that even when these ambiguities are charitably corrected, Nickel’s defense of general theories of explanation is (...) inadequate along several different dimensions. Specifically, we argue that Nickel’s argument has three fatal flaws. First, he has not provided any compelling illustrations of domain-invariant constraints on explanation. Second, in order to fend off the most vehement skeptics of domain-invariant theories of explanation, Nickel must beg all of the important questions. Third, Nickel’s examples of explanations from different domains with common explanatory structure rely on incorrect formulations of the explanations under consideration, circular justifications, and/or a mischaracterization of the position Nickel intends to critique. Given that the best and most elaborate defense of the generalist position fails in so many ways, we conclude that the standard practice in philosophy (and in philosophy of science in particular), which is to develop theories of explanation that are tailored to specific domains, still is justified. For those who want to buy into a more ambitious project: beware of the costs! (shrink)

Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In contrast (...) to the right to explanation of specific automated decisions claimed elsewhere, the GDPR only mandates that data subjects receive meaningful, but properly limited, information (Articles 13-15) about the logic involved, as well as the significance and the envisaged consequences of automated decision-making systems, what we term a ‘right to be informed’. Further, the ambiguity and limited scope of the ‘right not to be subject to automated decision-making’ contained in Article 22 (from which the alleged ‘right to explanation’ stems) raises questions over the protection actually afforded to data subjects. These problems show that the GDPR lacks precise language as well as explicit and well-defined rights and safeguards against automated decision-making, and therefore runs the risk of being toothless. We propose a number of legislative and policy steps that, if taken, may improve the transparency and accountability of automated decision-making when the GDPR comes into force in 2018. (shrink)

In his seminal book, Philosophy of Psychology: A Contemporary Introduction, José Bermúdez argues that David Marr’s levels of explanation cannot be used as a general framework for thinking about the levels of explanation in cognitive sciences. More specifically, he argues that Marr’s levels of explanation paradigmatically apply to subpersonal modular cognitive processes, while the mind as a whole is also characterized by non-modular cognitive systems. In this paper, I evaluate Bermúdez’s arguments for this conclusion. Part of the (...) evaluation will be based on recent advancements in the active inference framework, suggesting that even non-modular personal processes can be analyzed within the Marrian paradigm. Moreover, I provide some reasons for thinking that Marr’s levels of explanation could also be employed to illuminate the relationship between personal and subpersonal explanations. (shrink)

Theories of explanation seek to tell us what distinctively explanatory information is. The most ambitious ones, such as the DN-account, seek to tell us what an explanation is, tout court. Less ambitious ones, such as causal theories, restrict themselves to a particular domain of inquiry. The least ambitious theories constitute outright skepticism, holding that there is no reasonably unified phenomenon to give an account of. On these views, it is impossible to give any theories of explanation at (...) all. I argue that both the less ambitious and outright skeptical varieties are committed to a certain context-sensitivity of our explanatory discourse. And though this discourse is almost certainly context-sensitive in some respects, it does not exhibit the context-sensitivity less than fully ambitious theories are committed to. Therefore, all accounts that seek to restrict themselves in scope, including causal accounts of explanation, fail. (shrink)

The covering-law model of historical explanation works only for explanation of particulars by particulars, or narrative questions and person and action questions. Wisdom suggests three other explanatory theories that may be integral to historical explanation. What are called Challengeable-cover laws, Function-type laws, and Theoretical-type explanations are introduced and their ranges with respect to covering laws described. The first type are non-trivial generalizations the historian forms where existing covering laws are irrelevant or insufficient, for isolated aspects of their (...) subject matter. Function-type explanatory laws are systemic and answer questions basic in the social sciences where they point beyond particulars to general functions of systems. Theory-type explanations, like Mary Douglas' explanation of taboos, involve theoretical entities or unobservables and operate analogously to theoretical explanations in the natural sciences. Historians often condense generalizations into concepts and treat them as particulars. History thus becomes generality-impregnated narrative. (shrink)

Gers (Biol Philos, 2011) provides a positive and constructive view of the project to generalise Darwinian principles in Geoffrey Hodgson and Thorbjørn Knudsen’s Darwin’s Conjecture. We note considerable overlap with his work and ours, and also with important recent work of Godfrey-Smith ( 2009 ), which Gers cites extensively. But we also note that there are differences in research objectives between Gers and Godfrey-Smith, on the one hand, and ourselves, on the other. Gers and Godfrey-Smith focus on the elucidation of (...) the most general principles possible. Our aim is to derive principles that are sufficiently abstract to span the natural and human social worlds, and then add additional principles to help understand the Darwinian evolution of human society. Furthermore, Gers and Godfrey-Smith critique a replicator concept that is different from ours. Once these points are made apparent, the criticisms are essentially disabled, and we end up in a position with different but complementary and overlapping research projects. (shrink)

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)

Issues concerning scientific explanation have been a focus of philosophical attention from Pre- Socratic times through the modern period. However, recent discussion really begins with the development of the Deductive-Nomological (DN) model. This model has had many advocates (including Popper 1935, 1959, Braithwaite 1953, Gardiner, 1959, Nagel 1961) but unquestionably the most detailed and influential statement is due to Carl Hempel (Hempel 1942, 1965, and Hempel & Oppenheim 1948). These papers and the reaction to them have structured subsequent discussion (...) concerning scientific explanation to an extraordinary degree. After some general remarks by way of background and orientation (Section 1), this entry describes the DN model and its extensions, and then turns to some well-known objections (Section 2). It next describes a variety of subsequent attempts to develop alternative models of explanation, including Wesley Salmon's Statistical Relevance (Section 3) and Causal Mechanical (Section 4) models and the Unificationist models due to Michael Friedman and Philip Kitcher (Section 5). Section 6 provides a summary and discusses directions for future work. (shrink)

This book introduces readers to the topic of explanation. The insights of Plato, Aristotle, J.S. Mill and Carl Hempel are examined, and are used to argue against the view that explanation is merely a problem for the philosophy of science. Having established its importance for understanding knowledge in general, the book concludes with a bold and original explanation of explanation.

Back cover: This book develops a philosophical account that reveals the major characteristics that make an explanation in the life sciences reductive and distinguish them from non-reductive explanations. Understanding what reductive explanations are enables one to assess the conditions under which reductive explanations are adequate and thus enhances debates about explanatory reductionism. The account of reductive explanation presented in this book has three major characteristics. First, it emerges from a critical reconstruction of the explanatory practice of the life (...) sciences itself. Second, the account is monistic since it specifies one set of criteria that apply to explanations in the life sciences in general. Finally, the account is ontic in that it traces the reductivity of an explanation back to certain relations that exist between objects in the world (such as part-whole relations and level relations), rather than to the logical relations between sentences. Beginning with a disclosure of the meta-philosophical assumptions that underlie the author’s analysis of reductive explanation, the book leads into the debate about reduction(ism) in the philosophy of biology and continues with a discussion on the two perspectives on explanatory reduction that have been proposed in the philosophy of biology so far. The author scrutinizes how the issue of reduction becomes entangled with explanation and analyzes two concepts, the concept of a biological part and the concept of a level of organization. The results of these five chapters constitute the ground on which the author bases her final chapter, developing her ontic account of reductive 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)

Each science proceeds by inventing general principles from which are deduced the consequences to be tested by observation and experiment; the author shows how the implications of this process explain some of its more baffling features and resolves many of the difficulties that philosophers have found in them.

By contrasting three general conceptions of scientific explanation, this paper seeks to clarify the explanandum and to exhibit the fundamental philosophical issues involved in the project of explicating scientific explanation. The three conceptions--epistemic, modal, and ontic--have both historical and contemporary importance. In the context of Laplacian determinism, they do not seem importantly distinct, but in the context of irreducibly statistical explanations, the three are seen to diverge sharply. The paper argues for a causal/mechanical version of the ontic conception, (...) and concludes by exhibiting some striking consequences of this approach. (shrink)

Explanation and understanding are intimately connected notions, but the nature of that connection has generally not been considered a topic worthy of serious philosophical investigation. Most authors have avoided making reference to the notion of understanding in their accounts of explanation because they fear that any mention of the epistemic states of the individuals involved compromises the objectivity of explanation. Understanding is a pragmatic notion, they argue, and pragmatics should be kept at a safe distance from the (...) universal features of explanation. My main contention in this dissertation is that there is a sense in which it is meaningful and useful to talk about objective understanding, and that to characterize this notion it is necessary to formulate an account of objective explanation that makes reference to the beliefs and epistemic goals of the participants in a cognitive enterprise. ;My account of explanation is based on the belief-doubt model of inquiry first proposed by Peirce. Using the tools provided by decision theory, and the models of belief revision developed by Isaac Levi and by Alchourron, Gardenfors, and Makinson, I analyze the objective and pragmatic conditions that a piece of information must fulfill to be both explanatory and epistemically useful to an inquiring agent. The objective basis for an explanation is provided by the relation of probabilistic relevance that the fact described by the explanans bares to the fact described by the explanandum. But an explanation is much more than its foundation. As an epistemological notion, a potential explanation can only be a bona fide explanation if it becomes part of inquiry, that is, if an agent or a group of agents can see any value in it for their cognitive purposes. I provide a way to evaluate an explanation in terms of its credibility, its content, and its explanatory value. I argue that although an objective measure of the credibility and content of an explanation can be established, in many cases a complete determination of its explanatory value will ultimately depend on the interests and goals of the individual inquirers. (shrink)

People often answer why-questions with what we call experiential explanations: narratives or stories with temporal structure and concrete details. In contrast, on most theories of the epistemic function of explanation, explanations should be abstractive: structured by general relationships and lacking extraneous details. We suggest that abstractive and experiential explanations differ not only in level of abstraction, but also in structure, and that each form of explanation contributes to the epistemic goals of individual learners and of science. In particular, (...) experiential explanations support mental simulation and survive transitions across background theories; as a result, they support learning and help us translate between competing frameworks. Experiential explanations play an irreducible role in human cognition – and perhaps in science. (shrink)

There is a widely shared belief that the higher-level sciences can provide better explanations than lower-level sciences. But there is little agreement about exactly why this is so. It is often suggested that higher-level explanations are better because they omit details. I will argue instead that the preference for higher-level explanations is just a special case of our general preference for informative, logically strong, beliefs. I argue that our preference for informative beliefs entirely accounts for why higher-level explanations are sometimes (...) better—and sometimes worse—than lower-level explanations. The result is a step in the direction of the unity of science hypothesis. 1Introduction2Background: Is Omitting Details an Explanatory Virtue? 2.1Anti-reductionist arguments2.2Reductionist argument2.3Logical strength3Bases, Links and Logical Strength4Functionalism and Fodor’s Argument5Two Generalizations6Should the Base Really Be Maximally Strong?7Anti-reductionist Arguments Regarding the Base8Should the Antecedent of the Link Really Be Maximally Weak? (shrink)

In this paper I argue that the common practice of employing moral predicates as explaining phrases can be accommodated on an expressivist account of moral practice. This account does not treat moral explanations as in any way second-rate or derivative, since it subsumes moral explanations under the general theory of program explanations (as defended by Jackson and Pettit). It follows that the phenomenon of moral explanations cannot be used to adjudicate the debate between expressivism and its rivals.

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)

. This paper proposes a generalization of the theory of the process of explanation to include consistent as well as inconsistent situations. The generalization is strong, for example in the sense that, if the background theory and the initial conditions are consistent, it leads to precisely the same results as the theory from the lead paper (Halonen and Hintikka 2004). The paper presupposes (and refers to arguments for the view that) inconsistencies constitute problems and that scientists try to resolve (...) them. (shrink)

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

The aim of this series is to bring together important recent writings in major areas of philosophical inquiry, selected from a variety of sources, mostly periodicals, which may not be conveniently available to the university student or the general reader. The editor of each volume contributes an introductory essay on the items chosen and on the questions with which they deal. A selective bibliography is appended as a guide to further reading. This volume presents a selection of the most important (...) recent writings on the nature of explanation. It covers a broad range of topics from the philosophy of science to the central philosophical terrain of the theory of knowledge. The distinguished contributors include Peter Achinstein, Wesley C. Salmon, Carl G. Hempel, Philip Kitcher, Bas C. van Fraassen, Jaegwon Kim, B. Brody, Timothy McCarthy, Peter Railton, David Lewis, Peter Lipton, James Woodward, and Robert J. Matthews. (shrink)

The idea at the core of the New Mechanical account of explanation can be summarized in the claim that explaining means showing ‘how things work’. This simple motto hints at three basic features of Mechanistic Explanation (ME): ME is an explanation-how, that implies the description of the processes underlying the phenomenon to be explained and of the entities that engage in such processes. These three elements trace a fundamental contrast with the view inherited from Hume and later (...) from strict logical empiricism (see Creath 2017), focused on epistemic and formal features of science and according to which issues concerning the kind of entities and processes that lie within a theory’s domain are extraneous to science and belong instead to ontology or metaphysics. Philosophers belonging to the new mechanical philosophy believe that the received view of scientific explanation (Hempel 2001), pivoting on the notion of law of nature, overshadows this insight. Since its origin in the 17th century, mechanical philosophy aimed to explain natural phenomena by reducing them to mechanisms. Traditional attempts to define the concept of mechanism involved the identification of a limited set of fundamental elements as, for instance, contact action, action at a distance, inertial motion (see e.g. Hesse 2005), and, more recently, transmission of a mark, or of a conserved quantity (see Frisch, this volume). The new mechanical philosophy rejects this austere characterization of mechanisms and mechanistic explanation and aim at providing a novel, philosophically rigorous explication of the concept of mechanism and of its role in scientific explanation and practice. ME has been adopted with profit in philosophy of special sciences (for instance in biomedical sciences, e.g. in the explanation of chemical transmission at synapses ((Machamer, Darden and Craver 2000), MDC henceforth); but also in social sciences, e.g. the three kinds of social mechanisms in Coleman’s analysis of Max Weber’s account of the role of the Protestant ethic in the growth of capitalism (Hedström and Swedberg 1998)), where exceptionless regularities are rarely ever found. In physics, it is generally possible to formulate explanations in law-based form, with the result that the plurality of explanatory forms might be overlooked. This should not come as a surprise, given that physics was the main inspiration for logical empiricists, and, in particular, Newtonian physics was a template for Hempel’s formulation of the covering law model. However, this situation is unfortunate, since, we will argue, knowing how things work is often part of the explanation of physical phenomena. In this chapter, we provide an introduction to the basic features of ME, with specific focus on its application to physics (section 1). The main part of the chapter is devoted to the defence of two theses: on the one hand, some domains of physics are not compatible with mechanistic reasoning and explanation (section 2); on the other hand, a comprehensive account of explanation in physics can’t dispense with ME (section 3). (shrink)

Cognitive science, as an interdisciplinary research endeavour, seeks to explain mental activities such as reasoning, remembering, language use, and problem solving, and the explanations it advances commonly involve descriptions of the mechanisms responsible for these activities. Cognitive mechanisms are distinguished from the mechanisms invoked in other domains of biology by involving the processing of information. Many of the philosophical issues discussed in the context of cognitive science involve the nature of information processing. For philosophy of science, a central question is (...) what counts as a scientific explanation. But what is a mechanistic explanation and how does it work, how can philosophy of science use it as a solution for the problem of integration in cognitive science? By answering these questions and merging my answers with discussion of concepts of philosophy, normativity and generality, I will investigate the following claim. -/- I claim that philosophy by using strength concepts such as normativity, generality, and a mechanistic philosophy of explanations, can be a most important contributor to cognitive science. I also investigate how philosophy of science could be (can be) a bridge between psychology and neuroscience. We need a distinction between philosophy of cognitive science and philosophy in cognitive science; I am talking about the latter. -/- This claim is very important for the integration and the future of the interdisciplinary field known as cognitive science. -/- Philosophy as a true cognitive science -/- When the Cognitive Science Society was founded, in the late 1970s, philosophy, neuroscience, and anthropology were playing smaller roles. The three disciplines that formed the core group were artificial intelligence, psychology, and linguistics. The curious thing is that George Miller, a psychologist and an important founder of cognitive sciences in a hexagon diagram that he presented, put philosophy at the top of the diagram and neuroscience at the very bottom. There is enough agreement now that neuroscience is the most important contributor to cognitive science and there are fair connections between philosophy and neuroscience. In that diagram there was almost no connection between philosophy and neuroscience. -/- The developments and rise of cognitive science in the last half-century has been accompanied by considerable amount of philosophical activity. Perhaps no other area within analytic philosophy in the second half of that period has attracted more attention or produced more publications. (Bechtel and Graham, 1998. Rumelhart and Bly 1999. Bechtel, Mandik, Mundale 2001. Thagard, 2007. Bennett and Dennett et al, 2007. Bennett and Hacker, 2008. Andler, 2009. Frankish and Ramsey, 2012.) -/- Many philosophers of science offer conclusions that have a direct bearing on cognitive science and its practitioners can profit from closer engagement with the rest of cognitive science. For example, William Bechtel has discussed three projects, two in naturalistic philosophy of mind and one in naturalistic philosophy of science that have been pursued during the past 30 years, that he contends, can make theoretical and methodological contributions to cognitive science (Bechtel, 2009). Paul Thagard is another example of the mentioned emerging school of philosophers of science that define cognitive science as the interdisciplinary investigation of mind and intelligence (Thagard, 2006). Thagard by presenting some general but important philosophical questions such as, “What is the nature of the explanations and theories developed in cognitive science?”, and by providing answers to these central questions has showed how philosophy of science can help cognitive science by the advantage of its generality. Andrew Brook, however, believes that philosophical approaches have never had a settled place in cognitive science but he is listed in a group of the philosophers of science that they are contributing very closely the cognitive science (Brook, 2009). Daniel Dennett , as well as being a member the mentioned naturalistic philosophers of science, believes that there is much good work for philosophers to do in cognitive science if they adopt the constructive attitude that prevails in science. -/- What are mechanisms? Let us begin abstractly before considering an example. Mechanisms are collections of entities and activities organized together to do something (cf. Machamer, Darden, & Craver, 2000; Craver & Darden, 2001; Bechtel &Richardson, 1993; Glennan, 1996). These explanations are known as ‘mechanistic explanations’. By using and developing these mechanistic explanations of philosophy of science one can draw normative consequences for cognitive science. Paul Thagard (Thagard, 2006 and 2009), William Bechtel (Bechtel, 2008 and 2009), Andrew Brook (Brook, 2008) investigated and promoted using the ‘normativity’ in philosophy to show a better and crucial role for philosophy of science in an interdisciplinary known as cognitive science. Some philosophers have thought that, in order to pursue this normative function, philosophy must distance itself from empirical matters, but there are examples where the investigations of descriptive and normative issues go hand in hand. ( Thagard, 2009). -/- I will investigate how we can reduce a higher-level science such as psychology to neuroscience without the problems of reductionism but via mechanistic explanations. By problem I mean psychology does not lose its autonomy. -/- Conclusion -/- If cognitive science is all about understanding the human mind, or if cognitive science is the interdisciplinary investigation of mind and intelligence, since the whole life of philosophy was involving with the ways of knowing (epistemology) and conceptions of reality (metaphysics), also philosophy has considered the so-called mind-body problem ( identity theory, functionalism, and heuristic identity theory) , then philosophy could be the most deserved discipline to be a most contributor in cognitive science. I tried to discuss this by using the three advantages in philosophy, normativity, and generality and by introducing an emerging school of mechanistic (not mechanical) philosophers. One thing left, as cognitive science is a two-way street, philosophers need also to stop in a station of cognitive science and learn from the most important advances in brain and neuroscience. -/- . (shrink)

Explanations implicitly end with something that makes sense, and begin with something that does not make sense. A statistical relationship, for example, a numerical fact, does not make sense; an explanation of this relationship adds something, such as causal information, which does make sense, and provides an endpoint for the sense-making process. Does social science differ from natural science in this respect? One difference is that in the natural sciences, models are what need ‘‘understanding.’’ In the social sciences, matters (...) are more complex. There are models, such as causal models, which need to be understood, but also depend on background knowledge that goes beyond the model and the correlations that make it up, which produces a regress. The background knowledge is knowledge of in-filling mechanisms, which are normally made up of elements that involve the direct understanding of the acting and believing subjects themselves. These models, and social science explanations generally, are satisfactory only when they end the regress in this kind of understanding or use direct understanding evidence to decide between alternative mechanism explanations. (shrink)

According to the Stoics, human beings enslave themselves. When they change from nonrational children into rational adults, human beings form false beliefs about what is good and what is bad. These beliefs enslave them to things that are neither good nor bad. The author argues for an interpretation of how the Stoics understood the reasoning in terms of which human beings form these false beliefs. This interpretation helps makes sense of the argument against Chrysippus’s explanation of the origin of (...) vice that Galen attributes to Posidonius. It also helps explain how the Stoics could think that nature is provident and that nature constructs human beings so that they enslave themselves when they change from nonrational children into rational adults. (shrink)

Philosophers of mathematics commonly distinguish between explanatory and non-explanatory proofs. An important subclass of mathematical proofs are proofs by induction. Are they explanatory? This paper addresses the question, based on general principles about explanation. First, a recent argument for a negative answer is discussed and rebutted. Second, a case is made for a qualified positive take on the issue.

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)

Laws through which we explain particular events need not be laws which describe uniform sequences of events; they may be laws stating uniform connections between two types of factor contained within a complex event. Hempel's apparent insistence that laws state the conditions invariably accompanying a type of complex event, that the event be an instance of the laws "covering" it, results from the Humean analysis in which causation obtains between types of events and "the cause" means necessary conditions. But historians (...) often depict sufficient conditions. On the other hand, some knowledge of general laws is a presupposition of Dray's "continuous series" model of historical explanation. (shrink)

"The arc of the moral universe is long but it bends towards justice." (Martin Luther King) -/- A moral explanation is an explanation of a particular or type of event (or fact or state of affairs) that features moral terms in the explaining phrase. Here are some examples. First, one way of the above quote is as the claim that, in the broad sweep of history, societies tend toward more just institutions, and that they do so precisely because (...) these institutions are just. This is a moral explanation of social development. Second, historians might claim that “The injustice of slavery contributed to its demise”: this is a moral explanation of a historical event. Third, I might say that “I believe that Hitler was morally depraved because he was morally depraved”: this is a moral explanation of a moral belief. Finally, philosophers sometimes say things like “In the original Trolley case, it is morally right to flick the switch, because this will lead to the morally best outcome”: this is a moral explanation of a particular moral fact. -/- The issue of the availability of moral explanations of these types is relevant to both normative ethics and metaethics. In normative ethics the availability of moral explanations is bound up with the possibility of general normative theories. In metaethics the issue of moral explanations is closely tied to the doctrine of moral realism. In what follows I first trace the relevance of moral explanations to normative ethics and metaethics, before considering some examples in detail. (shrink)

In this paper I critically examine the notion of explanation used in Artificial Intelligence in general, and in the theory of belief revision in particular. I focus on two of the best known accounts in the literature: Pagnucco’s abductive expansion functions and Gärdenfors’ counterfactual analysis. I argue that both accounts are at odds with the way in which this notion has historically been understood in philosophy. They are also at odds with the explanatory strategies used in actual scientific practice. (...) At the end of the paper I outline the desiderata for an epistemologically motivated, scientifically informed belief revision model for explanation. (shrink)

A story does more than recount events; it recounts events in a way that renders them intelligible, thus conveying not just information but also understanding. We might therefore be tempted to describe narrative as a genre of explanation. When the police invite a suspect to “tell his story,” they are asking him to explain the blood on his shirt or his absence from home on the night of the murder; and whether he is judged to have a “good story” (...) will depend on its adequacy as an explanation. Can we account for the explanatory force of narrative with the models of explanation available in the philosophy of science? Or does narrative convey a different kind of understanding, which requires a different model and perhaps even a term other than ‘explanation’? (shrink)

This chapter explores some of the ways that mechanisms are invoked in neuroscience and looks at a selection of the philosophical problems that arise when trying to understand mechanistic explanations. It introduces a series of historical case studies that illustrate how neuroscientists have depended on mechanistic metaphors in their efforts to understand the mind and brain, and how their mechanistic explanations have developed over time. The chapter highlights what contemporary philosophers have identified as the fundamental features of mechanisms and mechanistic (...) explanation. It considers some of the methodological issues that arise in neuroscience including how to integrate psychological with neural models, how to generalize findings in model organisms like the sea slug Aplysia to human learning and memory, and whether to favor top-down or bottom-up methods. Constructing multi-level mechanistic explanations involves intensive collaboration across different branches of science, and involves many challenges, both pragmatic and methodological. (shrink)

Much recent work on mathematical explanation has presupposed that the phenomenon involves explanatory proofs in an essential way. I argue that this view, ‘proof chauvinism’, is false. I then look in some detail at the explanation of the solvability of polynomial equations provided by Galois theory, which has often been thought to revolve around an explanatory proof. The article concludes with some general worries about the effects of chauvinism on the theory of mathematical explanation. 1Introduction 2Why I (...) Am Not a Proof Chauvinist 2.1Proof chauvinism and mathematical practice 2.2Proof chauvinism and philosophy 3An Example: Galois Theory and Explanatory Proof 4Conclusion. (shrink)

This paper focuses on two conflations which frequently appear within the philosophy of history and other fields concerned with action explanation. The first of these, which I call the Conflating View of Reasons, states that the reasons for which we perform actions are reasons why (those events which are) our actions occur. The second, more general conflation, which I call the Conflating View of Action Explanation, states that whatever explains why an agent performed a certain action explains why (...) (that event which was) her action occurred. Both conflations ignore the fact that there are at least two distinct objects that legitimately qualify as objects of action explanation2. As Jennifer Hornsby (1993) has previous suggested, one thing we might wish to explain is ‘why did A do what she did?’ another is, ‘why did the event of her doing it occur?’ -/- I shall argue that when these two views are combined they give rise to a futile debate about explanation in the philosophies of history and the social sciences, and to an almost identical debate in moral psychology and the philosophy of mind. In so doing, I shall also examine a proposed distinction between explaining a phenomenon, and rendering it intelligible. I conclude by distinguishing between four different objects of historical understanding, each of which is to be understood in the light of the aforementioned distinctions between event and thing done, and explanation and intelligibility. (shrink)

There are three main approaches to scientific explanation in the philosophical literature. The unification approach claims that science explains by fitting the particular facts and events within a general theoretical framework. The mechanistic approach claims that science explains by identifying mechanisms. According to the manipulationist approach an explanation ought to be such that it can be used to answer a “what-if-things-had-been-different question.” The article examines whether these three approaches are compatible or not in the case of the social (...) sciences, and it concludes by defending explanatory pluralism. (shrink)

It’s commonly held that particular moral facts are explained by ‘natural’ or ‘descriptive’ facts, though there’s disagreement over how such explanations work. We defend the view that general moral principles also play a role in explaining particular moral facts. More specifically, we argue that this view best makes sense of some intuitive data points, including the supervenience of the moral upon the natural. We consider two alternative accounts of the nature and structure of moral principles—’the nomic view’ and ‘moral platonism’—before (...) considering in what sense such principles obtain of necessity. (shrink)

We defend a noetic account of intramathematical explanation. On this view, a piece of mathematics is explanatory just in case it produces understanding of an appropriate type. We motivate the view by presenting some appealing features of noeticism. We then discuss and criticize the most prominent extant version of noeticism, due to Inglis and Mejía Ramos, which identifies explanatory understanding with the possession of well-organized cognitive schemas. Finally, we present a novel noetic account. On our view, explanatory understanding arises (...) from meeting specific explanatory objectives. We defend a cluster-concept account of explanatory objectives and identify four important subfamilies within the relevant network of resemblance relations. The resulting view is objectivist (in the sense that it takes explanatory success to be a matter of observer-independent fact), broader in scope than why-question-based accounts, compatible with empirical findings on experts’ explanatory judgments, and capable of generalizing (with appropriate provisos) to scientific explanation as a whole. It thus fulfills Friedman’s half-century-old demand for a general and objectivist theory which accounts for the link between explanation and understanding. (shrink)

We aim to develop a form of debunking argument according to which an agent’s belief is undermined if the reasons she gives in support of her belief are best explained as rationalizations. This approach is a more sophisticated form of what Shaun Nichols has called best-explanation debunking, which he contrasts with process debunking, i.e., debunking by means of showing that a belief has been generated by an epistemically defective process. In order to develop our approach, we identify an example (...) of such a best-explanation debunking argument in Joshua Greene’s attack on deontology. After showing that this argument is not an instance of process debunking, we offer our best-explanation approach as a generalization of Greene’s argument. Finally, we defend our approach by showing that it is not susceptible to some criticisms that Nichols has leveled against a less sophisticated form of best-explanation debunking. (shrink)

This MPhil dissertation presents a novel account of teleological explanations in biology. I outline the “shorthand approach” to such explanations, on which they are taken to convey implicit evolutionary explanations. “Selected effects” accounts of teleological explanation dominate recent literature, but they struggle to accommodate teleological explanations of complex traits built through cumulative selection. I articulate the general notion of a landscape explanation, which, applied to biology, explains the evolution of complex features in a population by citing salient features (...) of the population’s fitness landscape. I show that such explanations lend themselves to a teleological shorthand. I close with remarks concerning when a teleological explanation of a trait is legitimate, and why teleological language strikes us as appropriate when we give evolutionary explanations. (shrink)

This book consists of four major papers written by Peter Achinstein, Peter Geach, Wesley Salmon, and J. L. Mackie. Each of the papers has two commentaries. Achinstein’s paper is commented on by Mary Hesse and R. Harré; Geach’s paper, by Peter Winch and Grete Henry; Salmon’s paper, by D. H. Mellor and L. Jonathan Cohen; Mackie’s paper, by Renford Bambrough and Martin Hollis. Each author of the original paper then replies to his two commentators. All four papers are concerned with (...) some aspect of the concept of explanation. Achinstein’s and Salmon’s papers are extensions and justifications of their previous work. For example, Salmon has argued against Hempel’s account of scientific explanation and has maintained that certain scientific explanations are not arguments of any kind, and that consequently they need not embody the high probabilities that would be required to provide reasonable ground for expectation of the event to be explained. He argues instead that a statistical explanation of a particular event "consists of an assemblage of factors relevant to the occurrence or non-occurrence of the event to be explained, along with the associated probability values". He indicates in the present volume that he does not wish to create the impression "that ability to transmit a mark is any mysterious kind of necessary connection or ‘power’ of the sort Hume criticized in Locke". There is little likelihood that Salmon would be misconstrued in this way. Also there is recent literature to the effect that Locke was clearer on the issues of causality than Hume and that there is nothing "mysterious" in Locke’s notion of powerful particulars. Why are they any more mysterious than the passive particulars preferred by Humeans? (shrink)

The essays in this volume grew out of a seminar examining the possibility of the emergence of a new consensus in the philosophy of science. While that issue is not resolved, we are presented with the most thorough examination of problems associated with the deductive-nomological model of explanation and its variants since the publication of Hempel's Aspects of Scientific Explanation and other Essays in the Philosophy of Science. The discussion begins with Wesley Salmon's monograph-length review of the past (...) forty years of work in the tradition initiated by Hempel and Oppenheim in their groundbreaking article "Studies in the Logic of Explanation". As one of the major players in the debates, Salmon's personal account is informative; it provides a useful introduction to the topic and covers the recent history of work on explanation in a manner that allows the uninitiated to follow the arguments and intricacies of the essays that follow. A main theme in Salmon's essay, as in much of his work, is the relation between the theory of explanation and the concept of causation. Given that the notion of causal laws plays a dominant role in DN explanations, this discussion is most welcome. Causation is also a clear concern of many of the other papers. The resolution of some of the tensions between Salmon's approach to causation, and the various roles of explanation in the philosophy of science, is, in fact, one of the main objectives of the extended concluding piece by Philip Kitcher. For Kitcher, explanations serve as unifying mechanisms for theories within different disciplines. Unification in turn also serves as a criterion for choosing between competing theories. The interplay between, on the one hand, Salmon's attention to the problems deriving from Hempel's initial formulation of DN and, on the other hand, Kitcher's concerns with Salmon's conceptualization of causation, produces one of the more fascinating dialectics of the volume. By attending to their dialogue, we see just how far the theory of explanation has come in the last forty years and yet how slow progress can be when fundamental problems are deeply entrenched. Causation continues to bedevil us. With one exception, the remaining contributors to this volume seem to confirm that judgment. Matti Sintonen, Paul Humphreys, David Papineau, Nancy Cartwright, James Woodward, and Merilee Salmon explore the many facets of causation as it applies to clarifying our explanatory objectives. Peter Railton is an exception. In his paper Railton reminds us that behind the epistemological and pragmatic concerns of most of the other contributors, Wesley Salmon included, there lies a set of metaphysical concerns. A thorough analysis of causation and, hence, a resolution to many of the DN model's problems requires a logically prior assessment of the relation between the epistemology of causation and the metaphysics of necessity. How one decides that issue or cluster of issues, Railton reminds us, will play heavily in the controversies between realists and nonrealists over the proper use of the principle of inference to the best explanation. (shrink)

Whether, and in what sense, research in phenomenology and phenomenological psychopathology has—in addition to its descriptive and hermeneutic value—explanatory power is somewhat controversial. This paper shows why it is legitimate to recognize such explanatory power. To this end, the paper analyzes two central concerns underlying the debate about explanation in phenomenology: (a) the warning against reductionism, which is implicit in a conception of causal explanation exclusively based on models of natural/physical causation; and (b) the warning against top-down generalizations, (...) which neglect the specificity of the individual. While acknowledging that these two caveats express serious concerns regarding the debate on explanatory models, I show that phenomenology has the resources to respond to them. These can be found in analyses of different types of causation relating to different regions of reality and in the structure of explanatory models based on exemplarity. On the basis of these analyses, I defend a pluralist account vis-à-vis explanatory models. (shrink)

Where E is the proposition that [If H and O were true, H would explain O], William Roche and Elliot Sober have argued that P(H|O&E) = P(H|O). In this paper I argue that not only is this equality not generally true, it is false in the very kinds of cases that Roche and Sober focus on, involving frequency data. In fact, in such cases O raises the probability of H only given that there is an explanatory connection between them.

Grounding is typically associated to metaphysical explanation on the basis of the explanatory role’s being characteristic of grounding as well. Some even say that all what metaphysical explanation does is tracking the grounding relation. However, recently Maurin has argued that grounding does not “inherit” its properties from metaphysical explanation and, consequently, we should be “separatists”. In this paper separatism will be defended from the perspective of metaphysical explanation thus giving a turn to the separatist strategy. In (...) particular, the structural difference between grounding and metaphysical explanation will be pointed out as affecting also the explanatory function. It will be shown how dispositions and essentialist claims play different roles in the two theories. Lastly, it will be claimed that the two theories diverge on accounting for law-like and accidental generalizations. Provided these arguments are sound, there will be good reason to tell metaphysical explanation apart from grounding. (shrink)

People make significant decisions in contexts of risk and uncertainty. Some of these decisions seem wise under the circumstances, and others seem like irrational choices. In both cases, people offer reasons as clarifications and explanations of these choices to others and to themselves. Argument analysis, a technique well known in philosophy and more generally in the humanities, can explicate the strands of assumptions, intermediate conclusions, data, warrants, and claims that the person articulates. But alone, argument analysis often falls short of (...) revealing why the person’s decision makes sense to that person. Thefindings of empirical research into the influences of cognitive heuristics, the mental shortcuts we all use in decision making and problem solving, adds focus to the analysis of these choices. This paper links these two powerful analytic strategies, and provides a much fuller, more fruitful picture of explanations for seemingly irrational choices. Using an example explanation for deciding not to quit smoking, the paper makes both its methodological argument and its implicit argument for the significance of extending this analytical strategy to applied contexts. The implications of extending this analysis of everyday argument to management, health care, and education could be profound. (shrink)

A semantic universal, which we here dub the Veridical Uniformity Universal, has recently been argued to hold of responsive verbs (those that take both declarative and interrogative complements). This paper offers a preliminary explanation of this universal: verbs satisfying it are easier to learn than those that do not. This claim is supported by a computational experiment using artificial neural networks, mirroring a recent proposal for explaining semantic universals of quantifiers. This preliminary study opens up many avenues for future (...) work on explaining semantic universals more generally, which are discussed in the conclusion. (shrink)

It has recently been argued that a non-Bayesian probabilistic version of inference to the best explanation (IBE*) has a number of advantages over Bayesian conditionalization (Douven [2013]; Douven and Wenmackers [2017]). We investigate how IBE* could be generalized to uncertain evidential situations and formulate a novel updating rule IBE**. We then inspect how it performs in comparison to its Bayesian counterpart, Jeffrey conditionalization (JC), in a number of simulations where two agents, each updating by IBE** and JC, respectively, try (...) to detect the bias of a coin while they are only partially certain what side the coin landed on. We show that IBE** more often prescribes high probability to the actual bias than JC. We also show that this happens considerably faster, that IBE** passes higher thresholds for high probability, and that it in general leads to more accurate probability distributions than JC. (shrink)