In this paper, I offer an analysis of the radical disagreement over the adequacy of string theory. The prominence of string theory despite its notorious lack of empirical support is sometimes explained as a troubling case of science gone awry, driven largely by sociological mechanisms such as groupthink (e.g. Smolin 2006). Others, such as Dawid (2013), explain the controversy by positing a methodological revolution of sorts, according to which string theorists have quietly turned to nonempirical methods of theory assessment given (...) the technological inability to directly test the theory. The appropriate response, according to Dawid, is to acknowledge this development and widen the canons of acceptable scientific methods. As I’ll argue, however, the current situation in fundamental physics does not require either of these responses. Rather, as I’ll suggest, much of the controversy stems from a failure to properly distinguish the “context of justification” from the “context of pursuit”. Both those who accuse string theorists of betraying the scientific method and those who advocate an enlarged conception of scientific methodology objectionably conflate epistemic justification with judgements of pursuit-worthiness. Once we get clear about this distinction and about the different norms governing the two contexts, the current situation in fundamental physics becomes much less puzzling. After defending this diagnosis of the controversy, I’ll show how the argument patterns that have been posited by Dawid as constituting an emergent methodological revolution in science are better off if reworked as arguments belonging to the context of pursuit. (shrink)

The aim of this paper is to offer an account of epistemic justification suitable for the context of theory pursuit, that is, for the context in which new scientific ideas, possibly incompatible with the already established theories, emerge and are pursued by scientists. We will frame our account paradigmatically on the basis of one of the influential systems of epistemic justification: Laurence Bonjour’s coherence theory of justification. The idea underlying our approach is to develop a set of criteria which indicate (...) that the pursued system is promising of contributing to the epistemic goal of robustness of scientific knowledge and of developing into a candidate for acceptance. In order to realize this we will (a) adjust the scope of Bonjour’s standards—consistency, inferential density, and explanatory power, and (b) complement them by the requirement of a programmatic character. In this way we allow for the evaluation of the “potential coherence” of the given epistemic system. (shrink)

In his late years, Thomas Kuhn became interested in the process of scientific specialization, which does not seem to possess the destructive element that is characteristic of scientific revolutions. It therefore makes sense to investigate whether and how Kuhn’s insights about specialization are consistent with, and actually fit, his model of scientific progress through revolutions. In this paper, I argue that the transition toward a new specialty corresponds to a revolutionary change for the group of scientists involved in such a (...) transition. I will clarify the role of the scientific community in revolutionary changes and characterize the incommensurability across specialties as possessing both semantic and methodological aspects. The discussion of the discovery of the structure of DNA will serve both as an illustration of my main argument and as reply to one criticism raised against Kuhn—namely, that his model cannot capture cases of revolutionary yet non-disruptive episodes of scientific progress. Revisiting Kuhn’s ideas on specialization will shed new light on some often overlooked features of scientific change. (shrink)

In this paper I examine the epistemic function of agent-based models of scientific inquiry, proposed in the recent philosophical literature. In view of Boero and Squazzoni’s classification of ABMs into case-based models, typifications and theoretical abstractions, I argue that proposed ABMs of scientific inquiry largely belong to the last category. While this means that their function is primarily exploratory, I suggest that they are epistemically valuable not only as a temporary stage in the development of ABMs of science, but by (...) providing insights into theoretical aspects of scientific rationality. I illustrate my point with two examples of highly idealized ABMs of science, which perform two exploratory functions: Zollman’s ABM which provides a proof-of-possibility in the realm of theoretical discussions on scientific rationality, and an argumentation-based ABM, which provides insights into potential mechanisms underlying the efficiency of scientific inquiry. (shrink)

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. (shrink)

The aim of this paper is, on the one hand, to critically investigate Kuhn’s stance on the assessment of the pursuit worthiness of scientific theories, and, on the other hand, to show the actuality of some of Kuhn’s points on this issue, in view of their critical analysis. To this end we show that Kuhn presents certain tools, which may help scientists to overcome communication breakdowns when engaging in the process of rational deliberation regarding the question whether a theory is (...) worthy of further pursuit. These tools are persuasion, translation and interpretation. However, we argue that the perspective of epistemic semantic monism present in Kuhn’s work obstructs the full applicability of these tools. We show that dropping this perspective makes the notions of persuasion and interpretation more fruitful, and moreover, allows for a pluralism of scientific theories and practices that complements the pluralism based on disagreement among scientists, emphasized by Kuhn. (shrink)

This paper examines lessons obtained by means of simulations in the form of agent-based models about the norms that are to guide disagreeing scientists. I focus on two types of epistemic and methodological norms: norms that guide one’s attitude towards one’s own theory, and norms that guide one’s attitude towards the opponent’s theory. Concerning I look into ABMs that have been designed to examine the context of peer disagreement. Here I challenge the conclusion that the given ABMs provide a support (...) for the so-called Steadfast Norm, according to which one is epistemically justified in remaining steadfast in their beliefs in face of disagreeing peers. I argue that the proposed models at best provide evidence for a weaker norm, which concerns methodological steadfastness. Concerning I look into ABMs aimed at examining epistemic effects of scientific interaction. Here I argue that the models provide diverging suggestions and that the link between each ABM and the type of represented inquiry is still missing. Moreover, I examine alternative strategies of arguing in favor of the benefits of scientific interaction, relevant for contemporary discussions on scientific pluralism. (shrink)

This paper analyzes the rapid and unexpected rise of deep learning within Artificial Intelligence and its applications. It tackles the possible reasons for this remarkable success, providing candidate paths towards a satisfactory explanation of why it works so well, at least in some domains. A historical account is given for the ups and downs, which have characterized neural networks research and its evolution from “shallow” to “deep” learning architectures. A precise account of “success” is given, in order to sieve out (...) aspects pertaining to marketing or sociology of research, and the remaining aspects seem to certify a genuine value of deep learning, calling for explanation. The alleged two main propelling factors for deep learning, namely computing hardware performance and neuroscience findings, are scrutinized, and evaluated as relevant but insufficient for a comprehensive explanation. We review various attempts that have been made to provide mathematical foundations able to justify the efficiency of deep learning, and we deem this is the most promising road to follow, even if the current achievements are too scattered and relevant for very limited classes of deep neural models. The authors’ take is that most of what can explain the very nature of why deep learning works at all and even very well across so many domains of application is still to be understood and further research, which addresses the theoretical foundation of artificial learning, is still very much needed. (shrink)

Haag’s theorem cries out for explanation and critical assessment: It sounds the alarm that something is (perhaps) not right in one of the standard ways of constructing interacting fields to be used in generating predictions for scattering experiments. Viewpoints as to the precise nature of the problem, the appropriate solution, and subsequently-called-for developments in areas of physics, mathematics, and philosophy differ widely. In this paper, we develop and deploy a conceptual framework for critically assessing these disparate responses to Haag’s theorem. (...) Doing so reveals the driving force of more general questions as to the nature and purpose of foundational work in physics. (shrink)

In philosophy of science, abstraction tends to be subsumed under representation, often being described as the omission of a target’s features when it is represented. This approach to abstraction sidesteps cognitive aspects of abstraction processes. However, cognitive aspects of abstraction are important in understanding the role of historically grounded epistemic criteria supporting modeling in science. Drawing on recent work on the relation between metaphor and abstraction, we introduce the concept of paths of abstraction, and use historical and contemporary examples to (...) point to their role in guiding the development of relevance criteria which support modeling strategies in science. (shrink)

I discuss changes of perspective of four kinds in science and about science. Section 2 defends a perspectival nonrealism—something akin to Giere’s perspectival realism but not a realism—against the idea of complete, “Copernican” objectivity. Section 3 contends that there is an inverse relationship between epistemological conservatism and scientific progress. Section 4 casts doubt on strong forms of scientific realism by taking a long-term historical perspective that includes future history. Section 5 defends a partial reversal in the status of so-called context (...) of discovery and context of justification. Section 6 addresses the question of how we can have scientific progress without scientific realism—how progress is possible without the accumulation of representational truth. The overall result is a pragmatic instrumentalist perspective on the sciences and how to study them philosophically, one that contains a kernel of realism—instrumental realism. (shrink)

In his influential paper, 'Why Was the Logic of Discovery Abandoned?', Laudan contends that there has been no philosophical rationale for a logic of discovery since the emergence of consequentialism in the 19th century. It is the purpose of this paper to show that consequentialism does not involve the rejection of all types of logic of discovery. Laudan goes too far in his interpretation of the historical shift from generativism to consequentialism, and his claim that the context of pursuit belongs (...) to neither discovery nor justification is based on narrow interpretations of the contexts of discovery and justification. As a result, Laudan draws unwarranted conclusions concerning both the early and contemporary defenders of a logic of discovery. A methodological logic of discovery - which involves self-corrective methods of hypothesis generation that promote the long-term goals of science and which require consequential support for justification - is a type of logic of discovery that survives the shift to consequentialism. (shrink)

Empirical success is a central criterion for scientific decision-making. Yet its understanding in philosophical studies of science deserves renewed attention: Should philosophers think differently about the advancement of science when they deal with the uncertainty of outcome in ongoing research in comparison with historical episodes? This paper argues that normative appeals to empirical success in the evaluation of competing scientific explanations can result in unreliable conclusions, especially when we are looking at the changeability of direction in ongoing investigations. The challenges (...) we encounter arise from the inherent dynamics of disciplinary and experimental objectives in research practice. In this paper we discuss how these dynamics inform the evaluation of empirical success by analyzing three of its requirements: data accommodation, instrumental reliability, and predictive power. We conclude that the assessment of empirical success in developing inquiry is set against the background of a model’s interactive success and prospective value in an experimental context. Our argument is exemplified by the analysis of an apparent controversy surrounding the model of a quantum nose in research on olfaction. Notably the public narrative of this controversy rests on a distorted perspective on measures of empirical success. (shrink)

In this paper I examine the problem of inconsistency toleration in the context of scientific pluralism. I argue that, first of all, the notion of inconsistency toleration has to be qualified with respect to the evaluative attitude that one takes towards a given scientific theory or theories. Second, I show which types of inconsistency toleration are compatible with two major approaches to scientific pluralism, the so-called modest and the radical one. In view of this I suggest some points of demarcation (...) between these two approaches. (shrink)

There is a demand to nurture scientific creativity in science education. This paper proposes that the relevant conceptual infrastructure with which to teach scientific creativity is often already included in philosophy of science courses, even those that do not cover scientific creativity explicitly. More precisely, it is shown how paradigm theory can serve as a framework with which to introduce the differences between combinational, exploratory, and transformational creativity in science. Moreover, the types of components given in Kuhn’s disciplinary matrix are (...) argued to indicate a further subdivision within transformational creativity that makes explicit that this most radical type of creativity that aims to go beyond and thus to transform the current paradigm can take many different directions. More generally, it is argued that there are several synergies between the topic of scientific creativity and paradigm theory that can be utilized in most philosophy of science courses at relative ease. Doing so should promote the understanding of scientific creativity among students, provide another way to signify the relevance of paradigm theory, and more strategically be a way of reinforcing the place of philosophy of science in science education. (shrink)

The paper locates, appreciates, and extends several dimensions of Simon’s work in the direction of more recent contributions by people such as Gigerenzer and Dennett. The author’s “crowbar model of method” is compared to Simon’s scissors metaphor. Against an evolutionary background, both support a pragmatic rather than strong realist approach to theoretically deep and complex problems. The importance of implicit knowledge is emphasized, for humans, as well as nonhuman animals. Although Simon was a realist in some respects, his work on (...) bounded rationality, satisficing, problem solving, heuristics, models, and scientific discovery mark him as a pragmatist. Indeed, he should be regarded as one of the great American pragmatists, alongside Peirce, James, Dewey, and a few others. (shrink)

In this paper, I argue that analyzing pursuitworthiness in science requires that we study possible futures of science. The merits of different criteria of pursuitworthiness need to be assessed against scenarios of the future of science. Different criteria recognize and ignore different scenarios. As a consequence, different criteria enable us to manage different future possibilities. While it might be impossible to predict the future of science, there are still many interesting things we can say about the possible futures of science. (...) We can construct scenarios of the future of science on the basis of philosophical accounts of science. I point out that the topic of pursuitworthiness is not the only topic that can be approached by connecting philosophy of science with the construction of scenarios. (shrink)

Philosophers of science have in recent years become increasingly interested in the notion of interdisciplinarity. One important form interdisciplinarity can take is that of a dynamic exchange of problems and solutions between disciplines—what has recently been called problem-feeding. On this model problems arising within specific disciplines are sometimes solved more effectively by, or in collaboration with, other disciplines. In this paper we explore this model as a framework for thinking about, and actively structuring, interdisciplinary research. We point to the applicability (...) of the problem-feeding model, and to some of the prerequisites of problem-feeding interdisciplinarity, highlighting in particular the harmonisation of goals and the establishment of mutual trust between disciplines. (shrink)

In this paper, I explore the possibilities for arriving at a useful conception of methodological reductionism. Some participants in the debate talk about methodological reductionism as a research program. I argue that the concept of a research program, at least in Lakatos’ sense, cannot account for the diverse nature of methodological reductionism. I then present my own concept of a research directive as a useful alternative and elaborate on this by drawing on Hasok Chang’s theory of ontological principles and epistemic (...) activities. According to my view, the reductionist research directive can be characterized as consisting of the principles fundamental ontological homogeneity, part-whole asymmetry, and orderliness, together with the corresponding activities construction of identities, decomposition, and unification. I suggest that looking at reductionism in this way enables us to understand it as a gradual concept and thus go beyond the simplistic yes-or-no-questions that dominate many current debates on this topic. (shrink)

This book contains a selection of the papers presented at the Logic, Reasoning and Rationality 2010 conference in Ghent. The conference aimed at stimulating the use of formal frameworks to explicate concrete cases of human reasoning, and conversely, to challenge scholars in formal studies by presenting them with interesting new cases of actual reasoning. According to the members of the Wiener Kreis, there was a strong connection between logic, reasoning, and rationality and that human reasoning is rational in so far (...) as it is based on logic. Later, this belief came under attack and logic was deemed inadequate to explicate actual cases of human reasoning. Today, there is a growing interest in reconnecting logic, reasoning and rationality. A central motor for this change was the development of non-classical logics and non-classical formal frameworks. The book contains contributions in various non-classical formal frameworks, case studies that enhance our apprehension of concrete reasoning patterns, and studies of the philosophical implications for our understanding of the notions of rationality. (shrink)

This is a thesis about interdisciplinarity, scientific integration, and problem solving in sustainability science. Sustainability science is an emerging and highly interdisciplinary field that seeks to integrate vastly differentiated bodies of knowledge in addressing the challenge of transitioning contemporary societies towards sustainability. Interdisciplinarity is paramount. Interdisciplinarity in general, and in the context of sustainability science in particular, has often been associated with solving particular problems and problem solving is one important theme in this thesis. A central idea that is developed (...) is that of problem-feeding. Sometimes problems arise within one discipline that can only be solved with the help of another. This concept, that has predecessors in e.g. the work of Lindley Darden and Nancy Maull, is explored considerably. It is argued that in interdisciplinary contexts—such as sustainability science—where collaboration is sought it is important to maintain cross-boundary problem stability. That is to say, as the problem is transferred from one discipline to another transformations will often be necessary. These transformations then, need to be acceptable to all involved parties to maintain an active interdisciplinary connection. Another topic that is discussed both in the introductory essay and some of the papers included is that of scientific imperialism. Scientific imperialism—the infringement of one discipline upon the domain of another—is here suggested to be primarily a threat to in-terdisciplinary collaborations. A distinction is introduced between imperialist failures of expansionism and failures of replacement. These are labelled type-I and type-II imperialism respectively. Particular attention is devoted to the latter form. Type-II imperialism concerns cases where imperialist infringements fail as the imperial- izing framework replaces viable, or compatible alternatives. Such an error of replacement does, importantly, not imply that the framework or theory should be disregarded completely. This type of imperialist error can both be quite subtle, and damaging. For one, if one directs the attention to specific contexts knowledge is actually lost in the process. This is particularly serious in fields such as sustainability science that are, to such an large extent, aimed at influencing concrete policy. Finally, interdisciplinarity is difficult to achieve and in many cases represents a grand challenge in itself. There are however many different ways in which interdisciplinarity may be accomplished and different forms are suitable in different contexts. In a field such as sustainability science where complexity is such a prevalent feature, an inclusive, pluralist, approach is likely to be appropriate. (shrink)

Economic competitive advantage depends on innovation, which in turn requires pushing back the frontiers of various kinds of knowledge. Although understanding how knowledge grows ought to be a central topic of epistemology, epistemologists and philosophers of science have given it insufficient attention, even deliberately shunning the topic. Traditional confirmation theory and general epistemology offer little help at the frontier, because they are mostly retrospective rather than prospective. Nor have philosophers been highly visible in the science and technology policy realm, despite (...) philosophy’s being a normative discipline. This paper suggests a way to address both deficits. Creative scientists, technologists, business managers, and policy makers face similar problems of decision-making at their respective frontiers of knowledge. These areas should therefore be fertile ground for both epistemologists and philosophers concerned with policy. Here I call attention to the importance of heuristic appraisal for “frontier epistemology” and to policy formation. Evaluation of the comparative promise or expected fertility of available options comprises a cluster of activities that cut across traditional discovery/justification and descriptive/normative distinctions. The study of weak modes of reasoning and evaluation is especially relevant to socio-economic policy. (shrink)

This paper explicates the philosophical and epistemological background of the MIRRORS project, which is the starting point of the various contributions in this issue. Developments in the philosophy of science will be discussed, especially the watershed work of Kuhn, in order to analyze further developments in the sociology of science, particularly starting from the Strong Programme. Finally, it will be shown how a multidisciplinary approach in Science & Technology (S&T) studies, as opposed to an interdisciplinary one, is to be preferred. (...) Specifically, the connection between this approach and the modelling and idealizational approaches to science is stressed and defended as the best available approach for the formation of a conscientious democratic knowledge-based society. (shrink)