Axel Gelfert

This broad and insightful book presents current scholarship in important subfields of philosophy of science and addresses an interdisciplinary and multidisciplinary readership. It groups carefully selected contributions into the four fields of I) philosophy of physics, II) philosophy of life sciences, III) philosophy of social sciences and values in science, and IV) philosophy of mathematics and formal modeling. Readers will discover research papers by Paul Hoyningen-Huene, Keizo Matsubara, Kian Salimkhani, Andrea Reichenberger, Anne Sophie Meincke, Javier Suárez, Roger Deulofeu, Ludger Jansen, Peter Hucklenbroich, Martin Carrier, Elizaveta Kostrova, Lara Huber, Jens Harbecke, Antonio Piccolomini d'Aragona and Axel Gelfert. This collection fosters dialogue between philosophers of science working in different subfields, and brings readers the finest and latest work across the breadth of the field,illustrating that contemporary philosophy of science has successfully broadened its scope of reflection. It will interest and inspire a wide audience of philosophers as well as scholars of the natural sciences, social sciences and the humanities. The volume shares selected contributions from the prestigious second triennial conference of the German Society for Philosophy of Science/ Gesellschaft für Wissenschaftsphilosophie (GWP.2016, March 8, 2016 - March 11, 2016).

The study of similarity is fundamental to biological inquiry. Many homology concepts have been formulated that function successfully to explain similarity in their native domains, but fail to provide an overarching account applicable to variably interconnected and independent areas of biological research despite the monistic standpoint from which they originate. The use of multiple, explicitly articulated homology concepts, applicable at different levels of the biological hierarchy, allows a more thorough investigation of the nature of biological similarity. Responsible epistemological pluralism as advocated herein is generative of fruitful and innovative biological research, and is appropriate given the metaphysical pluralism that underpins all of biology.

That science is more than the unilinear application of general theories to specific empirical circumstances is, one hopes, no longer something that is controversial or requires detailed argument. To be sure, there were times when devising universally applicable theories was seen as the most worthy task of science, with less lofty activities such as experimentation and scientific modeling being relegated to the underbelly of “proper science.” Arguing for a pluralistic recognition of the diversity of scientific practices, methods, and goals, might—at least on the pages of this journal—amount to preaching to the converted. Yet, once the diversity and heterogeneity of science is acknowledged, the real work only starts:...

Whether or not the results of a computer simulation are credible depends to a large extent on the credibilityCredibility of the underlying conceptual model. If a model has been developed explicitly with the goal of running a computer simulation in mind, the two types of credibilityCredibility may seem deeply intertwined. Yet, often enough, conceptual modelsConceptual model predate the subsequent development of simulation techniques, or were first developed outside the context of computer simulation. In such a situation, the specific contribution that a conceptual model makes to the credibility of a simulation requires considerable analysis. How, then, should we assess the credibility of a conceptual model, and which factors ought to playPlay a role in judging whether simulation results derived on its basis are trustworthy? In order to answer these questions, the present chapter begins with the premise that models are never by themselves credible simpliciter, but acquire credibility within a given context of inquiry, which itself depends on the cognitive interests of the inquirer. Judgments concerning the credibility of a conceptual model thus need to be based partly on a characterization of the intrinsic features of the model, partly on the cognitive goals and interests of its users. This realization helps explain why credible models have been variously understood as adequate representations of real-world target systems, as constructions of “credible worlds”Credible world that display internal coherence, and as exploratory tools that may aid our understanding even before a well-developed underlying theory takes shape.

Among contemporary epistemologists of testimony, David Hume is standardly regarded as a ‘global reductionist’, where global reductionism requires the hearer to have sufficient first-hand knowledge of the facts in order to individually ascertain the reliability of the testimony in question. In the present paper, I argue that, by construing Hume’s reductionism in too individualistic a fashion, the received view of Hume on testimony is inaccurate at best, and misleading at worst. Overall, Hume is much more willing to regard testimonial acceptance as a natural response to testimony than has traditionally been thought. In particular, Hume believes that indirect evidence of human nature and of the social world around us, can take the place of first-hand evidence of the track record of individual speakers or specific classes of testimony. In developing this interpretation of Hume’s views on testimony, the present paper draws on discussions found in the Treatise, the Enquiry, and in Hume’s writings on historical knowledge. In der zeitgenössischen Debatte um den erkenntnistheoretischen Status zeugnisbasiertenWissens wird gern auf David Hume als den Urheber eines „globalen Reduktionismus“ verwiesen, demzufolge der Zeugnisempfänger über ausreichend empirische Belege für die Verlässlichkeit des betreffenden Zeugnisses verfügen muss. Im vorliegenden Aufsatz soll gezeigt werden, dass die in der Literatur vorherrschende Meinung ein übertrieben „individualistisches“ Bild von Humes Reduktionismus zeichnet; dadurch wird Humes Position in der gegenwärtigen Debatte ungenau und bisweilen irreführend wiedergegeben. Bei genauerer Betrachtung erweist sich Hume als ausgesprochen aufgeschlossen gegenüber dem Akzeptieren fremden Zeugnisses und sieht darin eine Art Grundmuster im testimonialen Umgang mit anderen. Insbesondere konzediert Hume, dass indirekt erworbenes Wissen um die menschliche Natur und die soziale Welt an die Stelle direkter Belege für die Verlässlichkeit einzelner Zeugen treten kann. Die im vorliegenden Aufsatz entwickelte Neuinterpretation stützt sich auf den Treatise, den Enquiry und auf Humes Schriften zum Problem der historischen Erkenntnis.

Epistemologists of testimony have tended to construct highly stylized (so-called “null setting”) examples in support of their respective philosophical positions, the paradigmatic case being the casual request for directions from a random stranger. The present paper analyzes the use of such examples in the early controversy between reductionists and anti-reductionists about testimonial justification. The controversy concerned, on the one hand, the source of whatever epistemic justification our testimony-based beliefs might have, and, on the other hand, the phenomenology of testimonial acceptance and rejection. As it turns out, appeal to “null setting” cases did not resolve, but instead deepened, the theoretical disputes between reductionists and anti-reductionists. This, it is suggested, is because interpreters ‘fill in’ missing details in ways that reflect their own peculiarities in perspective, experience, upbringing, and philosophical outlook. In response, two remedial strategies have been pursued in recent years: First, we could invert the usual strategy and turn to formal contexts, rather than informal settings, as the paradigmatic scenarios for any prospective epistemology of testimony. Second, instead of “null setting” scenarios, we can focus on richly described cases that either include, or are embedded into, sufficient contextual information to allow for educated judgments concerning the reliability and trustworthiness of the testimony and testifiers involved. The prospects of both of these approaches are then discussed and evaluated.

According to one influential view, model-building in science is primarily a matter of simplifying theoretical descriptions of real-world target systems using abstraction and idealization. This view, however, does not adequately capture all types of models. Many contemporary models in the natural and social sciences – from physics to biology to economics – stand in a more tenuous relationship with real-world target systems and have a decidedly stipulative element, in that they create, by fiat, ‘model worlds’ that operate according to some set of specified rules. While such models may be motivated by an interest in actual target phenomena, their validity is not – at least not primarily – to be judged by whether they constitute an empirically adequate representation of any particular empirical system. The present paper compares and contrasts three such types of models: minimal models, toy models, and exploratory models. All three share some characteristics and thus overlap in interesting ways, yet they also exhibit significant differences. It is argued that, in all three cases, modal considerations have an important role to play: by exploring the modal structure of theories and phenomena – that is, by probing possibilities in various ways – such models deepen our understanding and help us gain knowledge not only about what there is in the world, but also about what there could be.

Traditional frameworks for evaluating scientific models have tended to downplay their exploratory function; instead they emphasize how models are inherently intended for specific phenomena and are to be judged by their ability to predict, reproduce, or explain empirical observations. By contrast, this paper argues that exploration should stand alongside explanation, prediction, and representation as a core function of scientific models. Thus, models often serve as starting points for future inquiry, as proofs of principle, as sources of potential explanations, and as a tool for reassessing the suitability of the target system. This is illustrated by a case study of the varied career of reaction-diffusion models in the study of biological pattern formation, which was initiated by Alan Turing in a classic 1952 paper. Initially regarded as mathematically elegant, but biologically irrelevant, demonstrations of how, in principle, spontaneous pattern formation could occur in an organism, such Turing models have only recently rebounded, thanks to advances in experimental techniques and computational methods. The long-delayed vindication of Turing’s initial model, it is argued, is best explained by recognizing it as an exploratory tool.

In this article we argue that idealizations and limiting cases in models play an exploratory role in science. Four senses of exploration are presented: exploration of the structure and representational capacities of theory; proof-of-principle demonstrations; potential explanations; and exploring the suitability of target systems. We illustrate our claims through three case studies, including the Aharonov-Bohm effect, the emergence of anyons and fractional quantum statistics, and the Hubbard model of the Mott phase transitions. We end by reflecting on how our case studies and claims compare to accounts of idealization in the philosophy of science literature such as Michael Weisberg’s three-fold taxonomy.

Despite being a new term, ‘fake news’ has evolved rapidly. This paper argues that it should be reserved for cases of deliberate presentation of false or misleading claims as news, where these are misleading by design. The phrase ‘by design’ here refers to systemic features of the design of the sources and channels by which fake news propagates and, thereby, manipulates the audience’s cognitive processes. This prospective definition is then tested: first, by contrasting fake news with other forms of public disinformation; second, by considering whether it helps pinpoint conditions for the proliferation of fake news.

Although the emerging field of synthetic biology looks back on barely a decade of development, the stakes are high. It is a multidisciplinary research field that aims at integrating the life sciences with engineering and the physical/chemical sciences. The common goal is to design and construct novel biological components, functions and systems in order to implement, in a controlled way, biological devices and production systems not necessarily found in nature. Among the many potential applications are novel drugs and pesticides, cancer treatments, biofuels, and new materials. According to the most optimistic visions, synthetic biology may thus lead to a biotechnological revolution by transforming microorganisms into ‘factories’ of sorts, which could eventually displace conventional industrial methods.

The present paper argues for the relevance of Immanuel Kant and the German Enlightenment to contemporary social epistemology. Rather than distancing themselves from the alleged ‘individualism’ of Enlightenment philosophers, social epistemologists would be well-advised to look at the substantive discussion of social-epistemological questions in the works of Kant and other Enlightenment figures. After a brief rebuttal of the received view of the Enlightenment as an intrinsically individualist enterprise, this paper charts the historical trajectory of philosophical discussions of testimony as a source of knowledge, via such philosophers as C. Thomasius, C. A. Crusius, J. M. Chladenius, G. F. Meier, and finally Kant. Building on recent work on Kant's epistemology of testimony, the paper considers Kant's broader contributions to social epistemology. This includes an analysis of Kant's comments on the social basis of contingent epistemic standards, e.g. in the sciences, as well as on problems arising from the management of what Kant calls the growing ‘volume of knowledge’. Special attention is paid to the relation between Kant's views and contemporary problems arising both in the context of education and from our increased reliance on scientific experts.

Rumors, for better or worse, are an important element of public discourse. The present paper focuses on rumors as an epistemic phenomenon rather than as a social or political problem. In particular, it investigates the relation between the mode of transmission and the reliability, if any, of rumors as a source of knowledge. It does so by comparing rumor with two forms of epistemic dependence that have recently received attention in the philosophical literature: our dependence on the testimony of others, and our dependence on what has been called the ‘coverage-reliability’ of our social environment (Goldberg 2010). According to the latter, an environment is ‘coverage-reliable’ if, across a wide range of beliefs and given certain conditions, it supports the following conditional: If ~p were true I would have heard about it by now. However, in information-deprived social environments with little coverage-reliability, rumors may transmit information that could not otherwise be had. This suggests that a trade-off exists between levels of trust in the coverage-reliability of official sources and (warranted) trust in rumor as a source of information.

Edgar Allan Poe’s standing as a literary figure, who drew on (and sometimes dabbled in) the scientific debates of his time, makes him an intriguing character for any exploration of the historical interrelationship between science, literature and philosophy. His sprawling ‘prose-poem’ Eureka (1848), in particular, has sometimes been scrutinized for anticipations of later scientific developments. By contrast, the present paper argues that it should be understood as a contribution to the raging debates about scientific methodology at the time. This methodological interest, which is echoed in Poe’s ‘tales of ratiocination’, gives rise to a proposed new mode of—broadly abductive—inference, which Poe attributes to the hybrid figure of the ‘poet-mathematician’. Without creative imagination and intuition, Science would necessarily remain incomplete, evenby its own standards. This concern with imaginative (abductive) inference ties in nicely with his coherentism, which grants pride of place to the twin virtues of Simplicity and Consistency, which must constrain imagination lest it degenerate into mere fancy.

In his work on the epistemology of testimony, Peter Lipton developed an account of testimonial inference that aimed at descriptive adequacy as well as justificatory sophistication. According to ‘testimonial inference to the best explanation’, we accept what a speaker tells us because the truth of her claim figures in the best explanation of the fact that she made it. In this paper, I argue for a modification of this picture. In particular, I argue that IBE plays a dual role in the management and justification of testimony. On the one hand, the coherence and success of our testimony-based projects provides general abductive support for a default stance of testimonial acceptance; on the other hand, we are justified in rejecting specific testimonial claims whenever the best explanation of the instances of testimony we encounter entails, or makes probable, the falsity or unreliability of the testimony in question.Keywords: Testimony; Inference to the best explanation; Abduction; Epistemic justification.

In his influential 1960 paper ‘The Unreasonable Effectiveness of Mathematics in the Natural Sciences’, Eugene P. Wigner raises the question of why something that was developed without concern for empirical facts—mathematics—should turn out to be so powerful in explaining facts about the natural world. Recent philosophy of science has developed ‘Wigner’s puzzle’ in two different directions: First, in relation to the supposed indispensability of mathematical facts to particular scientific explanations and, secondly, in connection with the idea that aesthetic criteria track theoretical desiderata such as empirical success. An important aspect of Wigner’s article has, however, been overlooked in these debates: his worries about the underdetermination of physical theories by mathematical frameworks. The present paper argues that, by restoring this aspect of Wigner’s argument to its proper place, Wigner’s puzzle may become an instructive case study for the teaching of core issues in the philosophy of science and its history.

The present paper argues that ‘mature mathematical formalisms’ play a central role in achieving representation via scientific models. A close discussion of two contemporary accounts of how mathematical models apply—the DDI account (according to which representation depends on the successful interplay of denotation, demonstration and interpretation) and the ‘matching model’ account—reveals shortcomings of each, which, it is argued, suggests that scientific representation may be ineliminably heterogeneous in character. In order to achieve a degree of unification that is compatible with successful representation, scientists often rely on the existence of a ‘mature mathematical formalism’, where the latter refers to a—mathematically formulated and physically interpreted—notational system of locally applicable rules that derive from (but need not be reducible to) fundamental theory. As mathematical formalisms undergo a process of elaboration, enrichment, and entrenchment, they come to embody theoretical, ontological, and methodological commitments and assumptions. Since these are enshrined in the formalism itself, they are no longer readily obvious to either the novice or the proficient user. At the same time as formalisms constrain what may be represented, they also function as inferential and interpretative resources.

Much of Arnold Hauser’s work on the social history of art and the philosophy of art history is informed by a concern for the cognitive dimension of art. The present paper offers a reconstruction of this aspect of Hauser’s project and identifies areas of overlap with the sociology of knowledge—where the latter is to be understood as both a separate discipline and a going intellectual concern. Following a discussion of Hauser’s personal and intellectual background, as well as of the shifting political and academic setting of his work, the paper addresses one of Hauser’s central questions, viz. how best to square a thoroughgoing commitment to the social nature of art with the reality of successive artistic styles, given that the latter seem to be characterizable on purely formal grounds. This is followed by a discussion of Hauser’s conflicted views on the relation between art, science, and technology. This injects a tension into Hauser’s work, due to his initial reluctance to explain just how the aesthetic and the cognitive realms relate. The final part of the paper, through a closer examination of the analogies and disanalogies that Hauser sees between art history and the history of science, attempts to give a positive answer—“on Hauser’s behalf”, as it were—to the question of whether art may be credited with a specific cognitive dimension of its own, and if so, what its contribution to our cognitive enterprise may consist in

Taking scientific practice as its starting point, this book charts the complex territory of models used in science. It examines what scientific models are and what their function is. Reliance on models is pervasive in science, and scientists often need to construct models in order to explain or predict anything of interest at all. The diversity of kinds of models one finds in science – ranging from toy models and scale models to theoretical and mathematical models – has attracted attention not only from scientists, but also from philosophers, sociologists, and historians of science. This has given rise to a wide variety of case studies that look at the different uses to which models have been put in specific scientific contexts. By exploring current debates on the use and building of models via cutting-edge examples drawn from physics and biology, the book provides broad insight into the methodology of modelling in the natural sciences. It pairs specific arguments with introductory material relating to the ontology and the function of models, and provides some historical context to the debates as well as a sketch of general positions in the philosophy of scientific models in the process.

In its original form due to Ian Hacking, entity realism postulates a criterion of manipulative success which replaces explanatory virtue as the criterion of justified scientific belief. The article analyses the foundations on which this postulate rests and identifies the conditions on which one can derive a form of entity realism from it. It then develops in detail an extensive class of counterexamples, drawing on the notion of quasi-particles in condensed matter physics. While the phenomena associated with quasi-particles pass the entity realist's criterion of manipulative success, quasi-particles themselves are illusions, and can be seen to be so even on the basis of the largely non-theoretical "home truths" that one must be ready to admit as background knowledge. Hence, Hacking's entity realism is shown to be incoherent.