Science frequently gives us multiple, compatible ways of solving the same problem or formulating the same theory. These compatible formulations change our understanding of the world, despite providing the same explanations. According to what I call "conceptualism," reformulations change our understanding by clarifying the epistemic structure of theories. I illustrate conceptualism by analyzing a typical example of symmetry-based reformulation in chemical physics. This case study poses a problem for "explanationism," the rival thesis that differences in understanding require ontic (...) explanatory differences. To defend conceptualism, I consider how prominent accounts of explanation might accommodate this case study. I argue that either they do not succeed, or they generate a skeptical challenge. (shrink)

Science and mathematics continually change in their tools, methods, and concepts. Many of these changes are not just modifications but progress---steps to be admired. But what constitutes progress? This dissertation addresses one central source of intellectual advancement in both disciplines: reformulating a problem-solving plan into a new, logically compatible one. For short, I call these cases of compatible problem-solving plans "reformulations." Two aspects of reformulations are puzzling. First, reformulating is often unnecessary. Given that we could already solve a (...) problem using an older formulation, what do we gain by reformulating? Second, some reformulations are genuinely trivial or insignificant. Merely replacing one symbol with another does not lead to intellectual progress. What distinguishes significant reformulations from trivial ones? According to what I call "conceptualism" (or "conceptual empiricism"), reformulations are intellectually significant when they provide a different plan for solving problems. Significant reformulations provide inferentially different routes to the same solution. In contrast, trivial reformulations provide exactly the same problem-solving plans, and hence they do not change our understanding. This answers the second question about what distinguishes trivial from significant reformulations. However, the first question remains: what makes a new way of solving an old problem valuable? Here, a bevy of practical considerations come to mind: one formulation might be faster, less complicated, or use more familiar concepts. According to "instrumentalism," these practical benefits are all there is to reformulating. Some reformulations are simply more instrumentally valuable for meeting the aims of science than others. At another extreme, "fundamentalism" contends that a reformulation is valuable when it provides a more fundamental description of reality. According to this view, some reformulations directly contribute to the metaphysical aim of carving reality at its joints. Conceptualism develops a middle ground between instrumentalism and fundamentalism, preserving their benefits without their costs. I argue that the epistemic value of significant reformulations does not reduce to either practical or metaphysical value. Reformulations are valuable because they are a constitutive part of problem-solving. Both science and mathematics aim at solving all possible problems within their respective domains. Meeting this aim requires being able to plan for any possible problem-solving context, and this requires reformulating. By reformulating, we clarify what we need to know to solve problems. Still, one might wonder whether the value of reformulations requires underlying differences in explanatory power. According to "explanationism," a reformulation is valuable only when it provides a better explanation. Explanationism stands as a rival middle ground position to my own. However, it faces numerous counterexamples. In many cases, two reformulations provide the same explanation while nonetheless providing different ways of understanding a phenomenon. Hence, reformulating can be valuable even when neither formulation is more explanatory. Methodologically, I draw on a variety of case studies to support my account of reformulation. These range from classical mechanics to quantum chemistry, along with examples from mathematics. Symmetry arguments provide a paradigmatic example: the mathematics of symmetry groups radically recasts quantum mechanics and quantum chemistry. Nevertheless, elementary approaches exist that eschew this additional mathematical apparatus, solving problems in a more tedious but less mathematically-demanding manner. Further examples include reformulations of quantum field theory, Arabic vs. Roman numerals, and Fermat's little theorem in number theory. In each case, my account identifies how reformulations change and improve our understanding of science and mathematics. (shrink)

The articulation of an overarching account of scientific explanation has long been a central preoccupation for the philosophers of science. Although a while ago the literature was dominated by two approaches—a causal account and a unificationist account—today the consensus seems to be that the causal account has won. In this paper, I challenge this consensus and attempt to revive unificationism. More specifically, I aim to accomplish three goals. First, I add new criticisms to the standard anti-unificationist arguments, in order (...) to motivate the need for a revision of the doctrine. Second, and most importantly, I sketch such a revised version. Then I argue that, contrary to widespread belief, the causal account and this revised unificationist account of explanation are compatible. Moreover, I also maintain that the unificationist account has priority, since a most satisfactory theory of explanation can be obtained by incorporating the causal account, as a sub-component of the unificationist account. The driving force behind this reevaluation of the received view in the philosophy of explanation is a reconsideration of the role of scientific understanding. (shrink)

The paper has two main aims. The first is to reformulate Hempel's version of the thesis of the symmetry of explanation and prediction, as regards the deductive covering-law model, so as to generalise it and make it no longer subject to some of the criticisms which have been directed at it (Section II). The second aim is to consider, with special critical reference to Hempel's recent treatment in Aspects of Scientific Explanation (New York and London, 1965), some central (...) criticisms of both the constituent parts of the above symmetry thesis, viz. that adequate explanations are potentially predictive (Section III), and that adequate predictive arguments are potentially explanatory (Section IV). (shrink)

In lieu of an abstract, here is a brief excerpt of the content:NARRATIVE AND EXPLANATION: EXPLAINING ANNA KARENINA IN THE LIGHT OF ITS EPIGRAPH Marina Ludwigs University ofCalifornia, Irvine In this paper, I will be examining the relation of explanation to narrative, looking briefly at the theoretical side ofthe problematic and in more detail at specific explanatory issues that arise in Tolstoy's novel Anna Karenina. Although the use itselfofthe term "explanation" is not as visible in the humanities as it is (...) in the sciences, the explanatory enterprise by other names is just as prominent. For indeed, an animating impetus behind textual interpretation is an explanation ofhowatextcan be brought into a correspondence with another text, while contemporary critical-theoretical activities of demystifying aesthetic and cultural assumptions, contextualizing historical knowledge, or laying bare ideological presuppositions are, in one way or another, engagements in the explanation ofthe workings of language. I approach humanistic explanation via a brief detour of scientific explanation, which constitutes an already established discourse with a set of defined issues and standard arguments, limiting myself to touching upon issues relevant to the narrativization of explanation. In scientific debates, explanation is defined as an answer to the question of "why?," in contradistinction to the question of "what?," which prompts a description of a phenomenon in question. Descriptive and explanatory conceptual frameworks, however, are interdependent. A physical description involves an "in-depth" understanding of underlying regularities. An explanatory answer to a question is, in its turn, an argument that logically deduces the explanandum (the description ofa phenomenon to be explained) from the explanans (well-understood regularities). This Marina Ludwigs125 formal definition of an explanation necessitates a symmetry between explanation and prediction, because the reconstructed logical sequence can also be read in the other direction, demonstrating the inevitability of what has occurred. Thus the sight of shattered glass and a baseball lying about allows me to explain the accident by invoking the law ofthe conservation ofmomentum and the low shock-resistance ofglass. But the knowledge of these regularities would have also allowed me to predict the same outcome had I seen the baseball flying in its direction ofthe window. The ontological status of "regularities" has elicited a lively debate in the scientific community pertaining to the problem ofthe "real." The standard view of regularities defines them as general laws (the kind we learn about in physics classes) that could be deductive or inductive, deterministic or statistical. A general law may be subsumed under another, even more general law, thus forming a unifying hierarchy of laws. A rival conception appeals to causal mechanisms and defines regularities as established chains oftemporal succession. Both models, the covering-law and the causal one, have been criticized: the former—for its failure to distinguish a law from an accidental generalization; the latter—for its resurrection ofthe metaphysical notion ofcausal influence and its inability to deal with probabilistic events. One of the later contenders is Nancy Cartwright's model, that proposes to conceive of regularities as so-called "nomological machines"—"fixed (enough) arrangements] ofcomponents, or factors, with stable (enough) capacities that in the right sort of stable (enough) environment will, with repeated operation, give rise to the kind of regular behavior that we represent in our scientific laws" (Cartwright 50). Cartwright claims that scientific models work on the ceteris paribus (everything else being equal) basis. That is to say they "hold only in circumscribed conditions or so long as no factors relevant to the effect besides those specified occur" (Cartwright 28), such as inside a battery, refrigerator, or a rocket—insofar as special shielding conditions are in effect (as a counterexample, imagine usingNewton's laws ofmechanics for describing the motion of a dropped crumpled dollar). Cartwright's explanatory framework is thus pragmatic and local, avoiding the twin pitfalls of the metaphysical assumptions underlying the two older models—the totalizing and unifying idea of a covering law, on the one hand, and the influence of causal "force," on the other. What is instead emphasized by her is a procedural aspect of scientific knowledge that has been historically prevalent and reflects the practical exigencies of human existence—the experience of dangers and natural obstacles to human 126Explaining 'Anna Karenina ' desires. When ill-defined impediments are analyzed and reduced to concrete difficulties, specific... (shrink)

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

Hempel seems to hold the following three views: (H1) Understanding is pragmatic/relativistic: Whether one understands why X happened in terms of Explanation E depends on one's beliefs and cognitive abilities; (H2) Whether a scientific explanation is good, just like whether a mathematical proof is good, is a nonpragmatic and objective issue independent of the beliefs or cognitive abilities of individuals; (H3) The goal of scientific explanation is understanding: A good scientific explanation is the one that provides understanding. (...) Apparently, H1, H2, and H3 cannot be all true. Some philosophers think that Hempel is inconsistent, while some others claim that Hempel does not actually hold H3. I argue that Hempel does hold H3 and that he can consistently hold all of H1, H2, and H3 if he endorses what I call the “understanding argument.” I also show how attributing the understanding argument to Hempel can make more sense of his D-N model and his philosophical analysis of the pragmatic aspects of scientific explanation. (shrink)

Three major ways in which temporal asymmetries enter into scientific induction are discussed as follows: 1. An account is given of the physical basis for the temporal asymmetry of recordability, which obtains in the following sense: except for humanly recorded predictions and one other class of advance indicators to be discussed, interacting systems can contain reliable indicators of only their past and not of their future interactions. To deal with the exceptional cases of non-spontaneous "pre-records," a clarification is offered (...) of the essential differences in the conditions requisite to the production of an indicator having retrodictive significance ("post-record"), on the one hand, and of one having predictive significance ("prerecord" or recorded prediction), on the other. Purported counter-examples to the asymmetry of spontaneous recordability are refuted. 2. It is shown how in cases of asymmetric recordability, the associated retrodiction-prediction asymmetry makes for an asymmetry of assertibility as between an explanandum (or an explanans) referring to a future event and one referring to a past one. But it is argued that this epistemological asymmetry in the assertibility per se must be clearly distinguished from a logical asymmetry between the past and the future in regard to the inferability (deductive or inductive) of the explanandum from the explanans. And it is then contended that the failure to distinguish between an epistemological and a logical asymmetry vitiates the critiques that recent writers have offered of the Popper-Hempel thesis, which affirms symmetry of inferability as between predictive and post-explanatory arguments. In reply to Scriven, it is maintained that predictions based on mere indicators (rather than causes) do not establish an asymmetry in scientific understanding as between predictive arguments and post-explanatory ones. 3. As a further philosophical ramification of the retrodiction-prediction asymmetry, a set of sufficient conditions are stated for the correctness of philosophical mechanism as opposed to teleology. (shrink)

The Explanatory Model of Scientific Understanding is a deflationary thesis recently advocated by Kareem Khalifa. EMU is committed to two key ideas: all understanding-relevant knowledge is propositional in nature; and the abilities we use to generate understanding are merely our usual logical reasoning skills. In this paper I provide an argument against both ideas, suggesting that scientific understanding requires a significant amount of non-propositional knowledge not captured by logical relations. I use the Inferential Model of Scientific Understanding (...) to reveal how we can better represent what constitutes understanding a scientific event. In particular, this model accounts for not only logical and probabilistic inferences, but also those conceptual associations and categorizations we must make to comprehend an explanation. (shrink)

Science has multiple goals: to describe the world, as it is now; to predict the future and to make inferences about the past. But science also aims to understand the world - to explain why it is the way it is. But what does it take to explain a phenomenon? What philosophical questions are at stake? In this thorough and clearly written introduction to scientific explanation, Arnon Levy explores the following problems and questions: the background to the topic of (...) scientific explanation, particularly the questions of what an explanation is, what makes a good explanation and why seek them in the first place empiricism about explanation: Hempel's Deductive-Nomological model and criticisms of Hempel's theory unificationism about explanation: are good scientific explanations those fit into an overall 'explanatory store'? causation and explanation: Salmon's 'statistical relevance' and 'mark transmission' arguments causation and explanation: Lewis's description-based model, Woodward's interventionist view and Strevens's criterion of selection theory connections between explanation and understanding non-scientific explanation: metaphysics. Additional features, such as chapter summaries, suggestions for further reading and a glossary make this an excellent resource for students of philosophy of science, metaphysics and philosophy of psychology. (shrink)

The theory of explanatory unification was first proposed by Friedman (1974) and developed by Kitcher (1981, 1989). The primary motivation for this theory, it seems to me, is the argument that this account of explanation is the only account that correctly describes the genesis of scientific understanding. Despite the apparent plausibility of Friedman's argument to this effect, however, I argue here that the unificationist thesis of understanding is false. The theory of explanatory unification as articulated by Friedman and Kitcher (...) thus emerges as fundamentally misconceived. (shrink)

The appeal to mechanisms in scientific explanation is commonplace in contemporary philosophy of science. In short, mechanists argue that an explanation of a phenomenon consists of citing the mechanism that brings the phenomenon about. In this paper, we present an argument that challenges the universality of mechanistic explanation: in explanations of the contemporary features of the eukaryotic cell, biologists appeal to its symbiogenetic origin and therefore the notion of symbiogenesis plays the main explanatory role. We defend the notion that (...) symbiogenesis is non-mechanistic in nature and that any attempt to explain some of the contemporary features of the eukaryotic cell mechanistically turns out to be at least insufficient and sometimes fails to address the question that is asked. Finally, we suggest that symbiogenesis is better understood as a pragmatic scientific law and present an alternative non-mechanistic model of scientific explanation. In the model we present, the use of scientific laws is supposed to be a minimal requirement of all scientific explanations, since the purpose of a scientific explanation is to make phenomena expectable. Therefore, this model would help to understand biologists’ appeal to the notion of symbiosis and thus is shown to be better, for the case under examination, than the mechanistic alternative. (shrink)

Reformulating a scientific theory often leads to a significantly different way of understanding the world. Nevertheless, accounts of both theoretical equivalence and scientific understanding have neglected this important aspect of scientific theorizing. This essay provides a positive account of how reformulation changes our understanding. My account simultaneously addresses a serious challenge facing existing accounts of scientific understanding. These accounts have failed to characterize understanding in a way that goes beyond the epistemology of scientific explanation. By (...) focusing on cases in which we have differences in understanding without differences in explanation, I show that understanding does not reduce to explanation. (shrink)

Recently, biologists and computer scientists who advocate the "strong thesis of artificial life" have argued that the distinction between life and nonlife is important and that certain computer software entities could be alive in the same sense as biological entities. These arguments have been challenged by Sober (1991). I address some of the questions about the rational reconstruction of biology that are suggested by these arguments: What is the relation between life and the "signs of life"? What work (if any) (...) might the concept of "life" (over and above the "signs of life") perform in biology? What turns on scientific disputes over the utility of this concept? To defend my answers to these questions, I compare "life" to certain other concepts used in science, and I examine historical episodes in which an entity's vitality was invoked to explain certain phenomena. I try to understand how these explanations could be illuminating even though they are not accompanied by any reductive definition of "life.". (shrink)

In books such as The World Within the World and The Anthropic Cosmological Principle, astronomer John Barrow has emerged as a leading writer on our efforts to understand the universe. Timothy Ferris, writing in The Times Literary Supplement of London, described him as "a temperate and accomplished humanist, scientist, and philosopher of science--a man out to make a contribution, not a show." Now Barrow offers the general reader another fascinating look at modern physics, as he explores the quest for a (...) single, unifying theory that will unlock nature's secrets. Theories of Everything is more than a history of science, more than a popular report on recent research and discoveries. Barrow provides a reflective, intelligent commentary on what a true Theory of Everything would be--its ingredients, its limitations, and what it could tell us about the universe. Never before, he writes, have physicists been so confident and so eager in the hunt for this "cosmic Rosetta Stone," as he calls it: "a single all-embracing picture of all the laws of nature from which the inevitability of all things seen must follow with unimpeachable logic." He lays out eight essential ingredients for a Theory of Everything and then explores each in turn, tracing how our knowledge has developed and how scientific discovery relates to our changing philosophy and religious thought in each area. Some of these ingredients are obvious--the laws of nature must be explained, for example, as well as its organizing principles--but others may be surprising, such as broken symmetries and selection biases. A Theory of Everything must account for the fact that the universe is "messy and complicated," he tells us, and for the limitations imposed by the questions we ask and the information we can obtain. The key lies in the remarkable capacity of mathematics to express the fundamental workings of the physical world--a language that the human mind is uniquely equipped to understand and manipulate. Barrow examines what mathematics actually is and describes how it makes the universe intelligible and provides a path to the underlying coherence in nature--which has led, in fact, to arguments that the universe itself is a vast computer. Yet even the most complete theory, even the most comprehensive mathematical explanation, cannot account for the uncomputable varieties of human experience and thought. "No non-poetic account of reality," he writes, "can be complete." In a field where the authorities converse in equations and mathematical notations, John Barrow speaks with the voice of thoughtful and knowledgeable humanist. Written with eloquence and expertise, Theories of Everything establishes a new perspective on humanity's efforts to explain the universe. (shrink)

The basic theory of scientific understanding presented in Sections 1–2 exploits three main ideas.First, that to understand a phenomenonP (for a given agent) is to be able to fitP into the cognitive background corpusC (of the agent).Second, that to fitP intoC is to connectP with parts ofC (via arguments in a very broad sense) such that the unification ofC increases.Third, that the cognitive changes involved in unification can be treated as sequences of shifts of phenomena inC. How the theory (...) fits typical examples of understanding and how it excludes spurious unifications is explained in detail. Section 3 gives a formal description of the structure of cognitive corpuses which contain descriptive as well as inferential components. The theory of unification is then refined in the light of so called puzzling phenomena, to enable important distinctions, such as that between consonant and dissonant understanding. In Section 4, the refined theory is applied to several examples, among them a case study of the development of the atomic model. The final part contains a classification of kinds of understanding and a discussion of the relation between understanding and explanation. (shrink)

Scientific explanation is a perennial topic in philosophy of science, but the literature has fragmented into specialized discussions in different scientific disciplines. An increasing attention to scientific practice by philosophers is (in part) responsible for this fragmentation and has put pressure on criteria of adequacy for philosophical accounts of explanation, usually demanding some form of pluralism. This commentary examines the arguments offered by Fagan and Woody with respect to explanation and understanding in scientific practice. I begin (...) by scrutinizing Fagan's concept of collaborative explanation, highlighting its distinctive advantages and expressing concern about several of its assumptions. Then I analyze Woody's attempt to reorient discussions of scientific explanation around functional considerations, elaborating on the wider implications of this methodological recommendation. I conclude with reflections on synergies and tensions that emerge when the two papers are juxtaposed and how these draw attention to critical issues that confront ongoing philosophical analyses of scientific explanation. (shrink)

This chapter presents a historical study of how science has developed and of how philosophical theories of many sorts – philosophy of science, theory of the understanding, and philosophical theology – both enable and constrain certain lines of development in scientific practice. Its topic is change in the legitimacy or acceptability of scientific explanation that invokes purposes, or ends; specifically in the argument from design, in the natural science field of physico-theology, around the start of the eighteenth century. (...) ... The context that produced physico-theology was clearly religious and political. It is unsurprising that a large body of Protestant intellectuals well-placed in a relatively peaceful society with a strong tradition of open speech, would develop links between science and critical discussion of both divinity and the Bible. There were also bounds to the discussion, as Newton, who chose to sit on the sidelines, knew well. Many others on Europe’s continent lived much more intimately with religious division as well as the reminder, in 1633, of Galileo’s failure to arrange a peaceable arrangement between science and religion. These aspects of the rise of physico-theology have not been the focus of this chapter, which has surveyed the philosophical and social origins found in the English context. Science, philosophy of science and other English philosophical currents – most particularly the theory of ideas and understanding that we are familiar with in its later development by John Locke – were formative for a field that might alternatively have been called ‘empirical natural theology.’ Prior shifts in religious sensibility that emptied the Book of Nature of much of its content also prepared the ground. Other philosophical and theological currents not discussed here – most notably theories of divine agency and predestination – and other philosophical trends – the rise of Spinoza’s challenge to such natural theology on the continent – also had both shaping and limiting influences upon the field. Finally, philosophers, including natural philosophers, did much more to promote physico-theology than just write about it: Boyle in particular provided a very important launch pad for the further development of an already healthy tradition of natural theology with his named lectureship, which drew the interest of others in the Royal Society, most notably Isaac Newton, and which spawned two of the most influential physico-theological tracts shortly before and shortly after the turn of the eighteenth century. (shrink)

While the relation between visualization and scientific understanding has been a topic of long-standing discussion, recent developments in physics have pushed the boundaries of this debate to new and still unexplored realms. For it is claimed that, in certain theories of quantum gravity, spacetime ‘disappears’: and this suggests that one may have sensible physical theories in which spacetime is completely absent. This makes the philosophical question whether such theories are intelligible, even more pressing. And if such theories are intelligible, (...) the question then is how they manage to do so. In this paper, we adapt the contextual theory of scientific understanding, developed by one of us, to fit the novel challenges posed by physical theories without spacetime. We construe understanding as a matter of skill rather than just knowledge. The appeal is thus to understanding, rather than explanation, because we will be concerned with the tools that scientists have at their disposal for understanding these theories. Our central thesis is that such physical theories can provide scientific understanding, and that such understanding does not require spacetimes of any sort. Our argument consists of four consecutive steps: We argue, from the general theory of scientific understanding, that although visualization is an oft-used tool for understanding, it is not a necessary condition for it; we criticise certain metaphysical preconceptions which can stand in the way of recognising how intelligibility without spacetime can be had; we catalogue tools for rendering theories without a spacetime intelligible; and we give examples of cases in which understanding is attained without a spacetime, and explain what kind of understanding these examples provide. (shrink)

"Understanding Scientific Progress constitutes a potentially enormous and revolutionary advancement in philosophy of science. It deserves to be read and studied by everyone with any interest in or connection with physics or the theory of science. Maxwell cites the work of Hume, Kant, J.S. Mill, Ludwig Bolzmann, Pierre Duhem, Einstein, Henri Poincaré, C.S. Peirce, Whitehead, Russell, Carnap, A.J. Ayer, Karl Popper, Thomas Kuhn, Imre Lakatos, Paul Feyerabend, Nelson Goodman, Bas van Fraassen, and numerous others. He lauds Popper for advancing (...) beyond verificationism and Hume’s problem of induction, but faults both Kuhn and Popper for being unable to show that and how their work could lead nearer to the truth." —Dr. LLOYD EBY teaches philosophy at The George Washington University and The Catholic University of America, in Washington, DC "Maxwell's aim-oriented empiricism is in my opinion a very significant contribution to the philosophy of science. I hope that it will be widely discussed and debated." – ALAN SOKAL, Professor of Physics, New York University "Maxwell takes up the philosophical challenge of how natural science makes progress and provides a superb treatment of the problem in terms of the contrast between traditional conceptions and his own scientifically-informed theory—aim-oriented empiricism. This clear and rigorously-argued work deserves the attention of scientists and philosophers alike, especially those who believe that it is the accumulation of knowledge and technology that answers the question."—LEEMON McHENRY, California State University, Northridge "Maxwell has distilled the finest essence of the scientific enterprise. Science is about making the world a better place. Sometimes science loses its way. The future depends on scientists doing the right things for the right reasons. Maxwell's Aim-Oriented Empiricism is a map to put science back on the right track."—TIMOTHY McGETTIGAN, Professor of Sociology, Colorado State University - Pueblo "Maxwell has a great deal to offer with these important ideas, and deserves to be much more widely recognised than he is. Readers with a background in philosophy of science will appreciate the rigour and thoroughness of his argument, while more general readers will find his aim-oriented rationality a promising way forward in terms of a future sustainable and wise social order."—David Lorimer, Paradigm Explorer, 2017/2 "This is a book about the very core problems of the philosophy of science. The idea of replacing Standard Empiricism with Aim-Oriented Empiricism is understood by Maxwell as the key to the solution of these central problems. Maxwell handles his main tool masterfully, producing a fascinating and important reading to his colleagues in the field. However, Nicholas Maxwell is much more than just a philosopher of science. In the closing part of the book he lets the reader know about his deep concern and possible solutions of the biggest problems humanity is facing."—Professor PEETER MŰŰREPP, Tallinn University of Technology, Estonia “For many years, Maxwell has been arguing that fundamental philosophical problems about scientific progress, especially the problem of induction, cannot be solved granted standard empiricism (SE), a doctrine which, he thinks, most scientists and philosophers of science take for granted. A key tenet of SE is that no permanent thesis about the world can be accepted as a part of scientific knowledge independent of evidence. For a number of reasons, Maxwell argues, we need to adopt a rather different conception of science which he calls aim-oriented empiricism (AOE). This holds that we need to construe physics as accepting, as a part of theoretical scientific knowledge, a hierarchy of metaphysical theses about the comprehensibility and knowability of the universe, which become increasingly insubstantial as we go up the hierarchy. In his book “Understanding Scientific Progress: Aim-Oriented Empiricism”, Maxwell gives a concise and excellent illustration of this view and the arguments supporting it… Maxwell’s book is a potentially important contribution to our understanding of scientific progress and philosophy of science more generally. Maybe it is the time for scientists and philosophers to acknowledge that science has to make metaphysical assumptions concerning the knowability and comprehensibility of the universe. Fundamental philosophical problems about scientific progress, which cannot be solved granted SE, may be solved granted AOE.” Professor SHAN GAO, Shanxi University, China . (shrink)

Kareem Khalifa’s Understanding, Explanation, and Scientific Knowledge is a splendid book, written in a beautiful and accessible style. It provides the ultimate articulation of his account of explanatory understanding that I am sure will be regarded as one of the landmark publications on the topic of scientific understanding. Many of the central questions regarding scientific understanding are treated from different perspectives in the book. Such questions are: Does understanding require explanations? Must it consist of mostly true information? (...) Is it a species of knowledge? -/- I cannot do justice to all the intricate details of Khalifa’s arguments in a short piece like this, so I will focus on discussing his main line of argument and some of the most salient questions that are addressed in the book, instead of summarizing and commenting on each chapter. (shrink)

Some scientific explanations appear to turn on pure mathematical claims. The enhanced indispensability argument appeals to these ‘mathematical explanations’ in support of mathematical platonism. I argue that the success of this argument rests on the claim that mathematical explanations locate pure mathematical facts on which their physical explananda depend, and that any account of mathematical explanation that supports this claim fails to provide an adequate understanding of mathematical explanation.

Whereas an inference (deductive as well as inductive) is usually viewed as being valid in virtue of its argument form, the present paper argues that scientific reasoning is material inference, i.e., justified in virtue of its content. A material inference is licensed by the empirical content embodied in the concepts contained in the premises and conclusion. Understanding scientific reasoning as material inference has the advantage of combining different aspects of scientific reasoning, such as confirmation, discovery, and explanation. (...) This approach explains why these different aspects (including discovery) can be rational without conforming to formal schemes, and why scientific reasoning is local, i.e., justified only in certain domains and contingent on particular empirical facts. The notion of material inference also fruitfully interacts with accounts of conceptual change and psychological theories of concepts. (shrink)

The orthodox, empiricist covering-law account of scientific explanation, as developed by C. G. Hempel and others, has long dominated philosophical discussions of scientific explanation. In recent years it has met overwhelming critical resistance. We should give up this account of scientific ex.

This chapter examines and criticizes the main arguments offered for scientific realism, here identified as the following view: Science aims to give us, in its theories, a literally true story of what the world is like; and acceptance of a scientific theory involves the belief that it is true. In contrast, constructive empiricism, which also opts for a literal understanding of scientific language, is the following view: Science aims to give us theories which are empirically adequate; and (...) acceptance of a theory involves as belief only that it is empirically adequate. Topics examined include the ’theory/observation dichotomy’, observable versus unobservable entities, epistemology and the epistemic community, inference to the best explanation, principle of the common cause, and fictionalism. The views of Smart, Sellars, Reichenbach, Putnam, and Dummett are considered. It is argued that the arguments offered for scientific realism, though telling against logical positivism, do not support it over and against constructive empiricism. (shrink)

Call an explanation in which a non-mathematical fact is explained—in part or in whole—by mathematical facts: an extra-mathematical explanation. Such explanations have attracted a great deal of interest recently in arguments over mathematical realism. In this article, a theory of extra-mathematical explanation is developed. The theory is modelled on a deductive-nomological theory of scientific explanation. A basic DN account of extra-mathematical explanation is proposed and then redeveloped in the light of two difficulties that the basic theory faces. The final (...) view appeals to relevance logic and uses resources in information theory to understand the explanatory relationship between mathematical and physical facts. 1Introduction2Anchoring3The Basic Deductive-Mathematical Account4The Genuineness Problem5Irrelevance6Relevance and Information7Objections and Replies 7.1Against relevance logic7.2Too epistemic7.3Informational containment8Conclusion. (shrink)

In this essay, I attempt to assess Henk de Regt and Dennis Dieks recent pragmatic and contextual account of scientific understanding on the basis of an important historical case-study: understanding in Newton’s theory of universal gravitation and Huygens’ reception of universal gravitation. It will be shown that de Regt and Dieks’ Criterion for the Intelligibility of a Theory (CIT), which stipulates that the appropriate combination of scientists’ skills and intelligibility-enhancing theoretical virtues is a condition for scientific understanding, is (...) too strong. On the basis of this case-study, it will be shown that scientists can understand each others’ positions qualitatively and quantitatively, despite their endorsement of different worldviews and despite their convictions as what counts as a proper explanation. (shrink)

An increasingly common form of naturalism associated with the study of morality is what might be called “scientific naturalism,” which takes as its subject matter various empirical phenomena associated with talk of “morality” and aims to subject them to scientific inquiry, just like any other empirical phenomena. This is unproblematic when it comes to scientific investigations into the origins of the human capacity for normative guidance or moral emotions, or the neurophysiology associated with moral feeling and behavior, (...) but things get much more complicated when it comes to the project of explaining our moral beliefs. It is, of course, an empirical phenomenon that we hold the moral beliefs we do, so it may seem obvious that this too can be causally explained using scientific tools. But, while there is room for scientific inquiry into causal factors, such as evolutionary influences, that have plausibly helped to shape many moral beliefs to some degree, it is a mistake to assume that our moral beliefs across the board can best be explained through appeal exclusively to scientifically accessible causes. This scientific naturalist exclusivity assumption is in fact deeply problematic, overlooking (or prematurely dismissing) the possibility that at least many of our moral beliefs are best explained through our grasping of good reasons for them – considerations we correctly understand as justifying them, though this is not something that shows up in scientific causal explanations. It is easy to miss this point about the potential role of the appreciation of justification by the believing mind when considering moral judgments simply from the external perspective of an amoral anthropologist, but it becomes clear when taking up the internal perspective of the committed moral agent, as when thinking about why we ourselves believe that human trafficking is wrong. This matters because, while science is invoked by those who purport to provide “debunking explanations” of our moral beliefs across the board (showing them to result simply from causal factors insensitive to any objective moral facts), they are actually relying on the scientific naturalist exclusivity assumption, thus begging the question against their opponents, who hold that we have knowledge of objective morality as a result of grasping good reasons for it. I explore these complexities surrounding the explanation of our moral beliefs and argue that while the picture advocated by debunkers remains a possibility, it is certainly not established by science, and recent arguments purporting to debunk the idea of knowable, objective morality fail. (shrink)

According to the no miracles argument, scientific realism provides the only satisfactory explanation of the predictive success of science. It is argued in the present article that a different explanatory strategy, based on the posit of strong limitations to the underdetermination of scientific theory building by the available empirical data, offers a more convincing understanding of scientific success.

Predictivists use the no miracle argument to argue that “novel” predictions are decisive evidence for theories, while mere accommodation of “old” data cannot confirm to a significant degree. But deductivists claim that since confirmation is a logical theory-data relationship, predicted data cannot confirm more than merely deduced data, and cite historical cases in which known data confirmed theories quite strongly. On the other hand, the advantage of prediction over accommodation is needed by scientific realists to resist Laudan’s criticisms of (...) the no miracle argument. So, if the deductivists are right, the most powerful argument for realism collapses. There seems to be an inescapable contradiction between these prima facie plausible arguments of predictivists and deductivists; but this puzzle can be solved by understanding what exactly counts as novelty, if novel predictions must support the no miracle argument, i.e., if they must be explainable only by the truth of theories. Taking my cues from the use-novelty tradition, I argue that (1) the predicted data must not be used essentially in building the theory or choosing the auxiliary assumptions. This is possible if the theory and its auxiliary assumptions are plausible independently of the predicted data, and I analyze the consequences of this requirement in terms of best explanation of diverse bodies of data. Moreover, the predicted data must be (2) a priori improbable, and (3) heterogeneous to the essentially used data. My proposed notion of novelty, therefore, is not historical, but functional. Hence, deductivists are right that confirmation is independent of time and of historical contingencies such as if the theorist knew a datum, used it, or intended to accommodate it. Predictivists, however, are right that not all consequences confirm equally, and confirmation is not purely a logical theory-data relation, as it crucially involves background epistemic conditions and the notion of best explanation. Conditions (1)–(3) make the difference between prediction and accommodation, and account for the confirming power of theoretical virtues such as non ad-hocness, non-fudging, non-overfitting, independence and consilience. I thus show that functional novelty (a) avoids the deductivist objections to predictivism, (b) is a gradual notion, in accordance with the common intuition that confirmation comes in degrees, and (c) supports the no miracle argument, so vindicating scientific realism. (shrink)

In this paper, I outline a heuristic for thinking about the relation between explanation and understanding that can be used to capture various levels of “intimacy”, between them. I argue that the level of complexity in the structure of explanation is inversely proportional to the level of intimacy between explanation and understanding, i.e. the more complexity the less intimacy. I further argue that the level of complexity in the structure of explanation also affects the explanatory depth in a similar way (...) to intimacy between explanation and understanding, i.e. the less complexity the greater explanatory depth and vice versa. (shrink)

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

A scientific theory, in order to be accepted as a part of theoretical scientific knowledge, must satisfy both empirical and non-empirical requirements, the latter having to do with simplicity, unity, explanatory character, symmetry, beauty. No satisfactory, generally accepted account of such non-empirical requirements has so far been given. Here, a proposal is put forward which, it is claimed, makes a contribution towards solving the problem. This proposal concerns unity of physical theory. In order to satisfy the non-empirical (...) requirement of unity, a physical theory must be such that the same laws govern all possible phenomena to which the theory applies. Eight increasingly demanding versions of this requirement are distinguished. Some implications for other non-empirical requirements, and for our understanding of science are indicated. (shrink)

Although there is increasing interest in philosophy of science in transcendental reasoning, there is hardly any discussion about transcendental arguments. Since this might be related to the dominant understanding of transcendental arguments as a tool to defeat epistemological skepticism, and since the power of transcendental arguments to achieve this goal has convincingly been disputed by Barry Stroud, this contribution proposes, first, a new definition of the transcendental argument which allows its presentation in a simple modus ponens and, second, a pragmatist (...) re-interpretation of this argument form that leaves it to the scientific community to debate, criticize, refine, or reaffirm its core claim: a premise which claims that the truth of a certain assumption is a necessary condition for something that is generally accepted. The proposed “logico-pragmatist interpretation” highlights the role of transcendental arguments as a methodological step to move science forward, just as abduction and inference to the best explanation do. (shrink)

In this book, Richard Campbell reformulates Anselm’s proof to show that factual evidence confirmed by modern cosmology validly implies that God exists. Anselm’s proof, which was never the “ontological argument” attributed to him, emerges as engaging with current philosophical issues concerning existence and scientific explanation.

The practice of justifying scientific explanations generates argumentative patterns in which several types of arguments may play a role. This paper is aimed at identifying these patterns on the basis of an exploration of the institutional conventions regarding the nature, the shape and the quality of scientific explanations as reflected in the writings of influential philosophers of science. First, a basic pattern for justifying scientific explanations is described. Then, two types of extensions of this pattern are presented. (...) These extensions are derived from philosophical accounts of requirements for the quality of explanations and the choice of the best explanation from a number of candidate explanations respectively. The description of the second extension will make clear how pragmatic argumentation plays a role in argumentative patterns within the scientific domain. (shrink)

Mathematics plays a central role in much of contemporary science, but philosophers have struggled to understand what this role is or how significant it might be for mathematics and science. In this book Christopher Pincock tackles this perennial question in a new way by asking how mathematics contributes to the success of our best scientific representations. In the first part of the book this question is posed and sharpened using a proposal for how we can determine the content of (...) a scientific representation. Several different sorts of contributions from mathematics are then articulated. Pincock argues that each contribution can be understood as broadly epistemic, so that what mathematics ultimately contributes to science is best connected with our scientific knowledge. In the second part of the book, Pincock critically evaluates alternative approaches to the role of mathematics in science. These include the potential benefits for scientific discovery and scientific explanation. A major focus of this part of the book is the indispensability argument for mathematical platonism. Using the results of part one, Pincock argues that this argument can at best support a weak form of realism about the truth-value of the statements of mathematics. The book concludes with a chapter on pure mathematics and the remaining options for making sense of its interpretation and epistemology. Thoroughly grounded in case studies drawn from scientific practice, this book aims to bring together current debates in both the philosophy of mathematics and the philosophy of science and to demonstrate the philosophical importance of applications of mathematics. (shrink)

Van Fraassen (1980) and Winther (2009) claim that we can explain phenomena in terms of scientific theories without believing that they are true. I argue that we ought to believe that they are true in order to use them to explain and understand phenomena. A scientific antirealist who believes that scientific theories are merely empirically adequate cannot use them to explain or to understand phenomena. The mere belief that they are empirically adequate produces neither explanation nor understanding (...) of phenomena. Explanation and understanding are the benefits of science only a scientific realist is entitled to. (shrink)

This book provides a distinctive and rich conception of methodology within international studies. From a rereading of the works of leading Western thinkers about international studies, Hayward Alker rediscovers a 'neo-Classical' conception of international relations which is both humanistic and scientific. He draws on the work of classical authors such as Aristotle and Thucydides; modern writers like Machiavelli, Vico, Marx, Weber, Deutsch and Bull; and post-modern writers like Havel, Connolly and Toulmin. The central challenge addressed is how to integrate (...) 'positivist' or 'falsificationist' research styles within humanistic or interpretive ones. The author argues that appropriate, philosophically informed reformulations of conventional statistical and game-theoretic analyses are possible, and describes a number of humanistic methodologies for international relations, including argumentation analysis, narrative modeling, computational models of political understanding and reconstructive analysis. (shrink)

Richard Boyd and Nicholas Sturgeon develop distinctive naturalistic arguments for scientific realism and moral realism. Each defends a realist position by an inference to the best explanation. In this paper, I suggest that these arguments for realism should be reformulated, with the law of likelihood replacing inference to the best explanation. The resulting arguments for realism do not work.

In this paper significant challenges are raised with respect to the view that explanation essentially involves unification. These objections are raised specifically with respect to the well-known versions of unificationism developed and defended by Michael Friedman and Philip Kitcher. The objections involve the explanatory regress argument and the concepts of reduction and scientific understanding. Essentially, the contention made here is that these versions of unificationism wrongly assume that reduction secures understanding.

The topic of the presence, legitimacy and epistemic worth of narrative explanations in different kinds of scientific discourse has already enjoyed several revivals within related discussions in contemporary philosophy of science. In fact, we have recently witnessed a more extensive, more unprejudiced and ambitious attention to narrative modes of making science. I think we need a systematic theoretical framework in order to categorize these different functions of narratives and understand their role in scientific explanatory and justificatory practice. My (...) claim is that some distinctions and analytic tools developed within the field of contemporary Argumentation Theory might be of help. (shrink)

argumentation has been shown to be a powerful tool within many fields such as artificial intelligence, logic and legal reasoning. In this paper we enhance Dung’s well-known abstract argumentation framework with explanatory capabilities. We show that an explanatory argumentation framework (EAF) obtained in this way is a useful tool for the modeling of scientific debates. On the one hand, EAFs allow for the representation of explanatory and justificatory arguments constituting rivaling scientific views. On the other hand, different procedures (...) for selecting arguments, corresponding to different methodological and epistemic requirements of theory evaluation, can be formulated in view of our framework. (shrink)

The paper examines the integration of virtue epistemology into the philosophy of science, emphasizing its potential to deepen our understanding of scientific inquiry. The article begins by considering the limitations of traditional epistemological frameworks that focus on beliefs. The discussion is set in the context of the “value turn” in contemporary epistemology. Arguments are made to move towards recognizing the significance of intellectual virtues and the nature of epistemic agents. The current gaps in definitions of intellectual virtues about reliabilist (...) and responsibilist approaches are examined and conceptual steps are proposed to bridge these gaps. It is suggested that the local and general epistemic goals of science should be clearly distinguished and then different ways of knowing should be attributed to these goals. These ways of knowing are proposed to be seen as exemplifying the realization of reliable skills and intellectual character traits. In sum, the article argues that adopting a virtue epistemology not only enriches the discourse on scientific knowledge but also promotes a culture of responsibility and integrity in the scientific community. (shrink)

Factivism is the view that understanding why a natural phenomenon takes place must rest exclusively on (approximate) truths. One of the arguments for nonfactivism—the opposite view, that falsehoods can play principal roles in producing understanding—relies on our inclination to say that past, false, now superseded but still important scientific theories (such as Newtonian mechanics) do provide understanding. In this paper, my aim is to articulate what I take to be an interesting point that has yet to be discussed: the (...) natural way in which nonfactivism fits within the unificationist account of scientific explanation. I contend that unificationism gives non-factivists a better framework to uphold their position. After I show why this is so, toward the end of the paper I will express doubts with regard to the viability of de Regt’s (2015) kind of non-factivism, based on the idea that understanding should be captured in terms of (scientific) skill. (shrink)

The “No Miracle Argument” for scientific realism contends that the only plausible explanation for the predictive success of scientific theories is their truthlikeness, but doesn’t specify what ‘truthlikeness’ means. I argue that if we understand ‘truthlikeness’ in terms of Kullback-Leibler (KL) divergence, the resulting realist thesis (RKL) is a plausible explanation for science’s success. Still, RKL probably falls short of the realist’s ideal. I argue, however, that the strongest version of realism that the argument can plausibly establish is (...) RKL. The realist needs another argument for establishing a stronger realist thesis. (shrink)

According to the no miracles argument, scientific realism provides the only satisfactory explanation of the predictive success of science. It is argued in the present article that a different explanatory strategy, based on the posit of limitations to the underdetermination of scientific theory building by the available empirical data, offers a more convincing understanding of scientific success.

Blackburn argues against naturalistic moral realism. He argues that there is no conceptual entailment from satisfying a naturalistic predicate to satisfying a moral predicate. But the moral is conceptually supervenient on the natural. However, this conjunction of conceptual supervenience with lack of conceptual entailment is something the non-realist can explain, but the realist cannot. I argue first that Blackburn’s best formulation of his challenge is his first one. Subsequently he reformulates it as a demand for a ‘ban on mixed worlds’. (...) Critics have directed their arguments against this formulation but they are ineffective against Blackburn’s first formulation. My second thesis is, even so formulated the realist can meet the challenge. The bare conceptual supervenience of the moral on the natural can be given a realist explanation by understanding names of moral properties as descriptive names of natural properties. (shrink)

The relationship between philosophy and science in contemporary times is closer than ever. From the methodology perspective, scientific and philosophical research has a clear sequential relationship. It is highlighted in the following aspects: 1. the methodology of scientific research, including theoretical assumptions and data modeling, parallels with apparent similarities in conceptual analysis and logical deduction in philosophy;2. consistency of analytical argumentation methods in scientific research and philosophical research;3. naturalism is currently a research approach that both scientific (...) and philosophical research adopt. There has been a significant dispute over the relationship between philosophy and science among contemporary philosophers. This dispute focuses on the impact of scientific development on philosophy research. Nowadays, no one would deny the existence of this impact, but there is no consensus on the impact's nature, scope, and role. Wittgenstein's conception of certainty can provide valuable insights to understand the relationship between philosophy and science. In addition, we conclude the pragmatic turn in cognitive science because we misinterpret the cognitive scientists' emphasis on action as a practical claim and interpret the cognitive scientists' views with pragmatism. The theoretical analysis and research suggestions philosophers provide are becoming essential focuses in contemporary artificial intelligence research, including the interpretability of computer technology, the ethical norms of artificial intelligence technology, and the possible conception of human beings in the future. The interdisciplinary study of science and philosophy will achieve more significant development. In sum, understanding the nature of philosophy can be given a new explanation from a future perspective. The future outlook here refers to the starting point from possible world scenarios that can be conceived and traced back to all the facts happening in the present world, thereby giving an appropriate explanation to the real world. (shrink)