Inferentialists about scientific representation hold that an apparatus’s representing a target system consists in the apparatus allowing “surrogative inferences” about the target. I argue that a serious problem for inferentialism arises from the fact that many scientific theories and models contain internal inconsistencies. Inferentialism, left unamended, implies that inconsistent scientific models have unlimited representational power, since an inconsistency permits any conclusion to be inferred. I consider a number of ways that inferentialists can respond to this challenge before (...) suggesting my own solution. I develop an analogy to exploitable glitches in a game. Even though inconsistent representational apparatuses may in some sense allow for contradictions to be generated within them, doing so violates the intended function of the apparatus’s parts and hence violates representational “gameplay.”. (shrink)

Idealizing conditions are scapegoats for scientific hypotheses, too often blamed for falsehood better attributed to less obvious sources. But while the tendency to blame idealizations is common among both philosophers of science and scientists themselves, the blame is misplaced. Attention to the nature of idealizing conditions, the content of idealized hypotheses, and scientists’ attitudes toward those hypotheses shows that idealizing conditions are blameless when hypotheses misrepresent. These conditions help to determine the content of idealized hypotheses, and they do (...) so in a way that prevents those hypotheses from being false by virtue of their constituent idealizations. (shrink)

In this paper, I first outline the view developed in my recent book on the role of idealization in scientific understanding. I discuss how this view leads to the recognition of a number of kinds of variability among scientific representations, including variability introduced by the many different aims of scientific projects. I then argue that the role of idealization in securing understanding distances understanding from truth, but that this understanding nonetheless gives rise to scientific knowledge. This (...) discussion will clarify how my view relates to three other recent books on understanding by Henk de Regt, Catherine Elgin, and Kareem Khalifa. (shrink)

Elgin offers an influential and far-reaching challenge to veritism. She takes scientific understanding to be non-factive and maintains that there are epistemically useful falsehoods that figure ineliminably in scientific understanding and whose falsehood is no epistemic defect. Veritism, she argues, cannot account for these facts. This paper argues that while Elgin rightly draws attention to several features of epistemic practices frequently neglected by veritists, veritists have numerous plausible ways of responding to her arguments. In particular, it is not (...) clear that false propositional commitments figure ineliminably in understanding in the manner supposed by Elgin. Moreover, even if scientific understanding were non-factive and false propositional commitments did figure ineliminably in understanding, the veritist can account for this in several ways without thereby abandoning veritism. (shrink)

Are mathematical objects affected by their historicity? Do they simply lose their identity and their validity in the course of history? If not, how can they always be accessible in their ideality regardless of their transmission in the course of time? Husserl and Foucault have raised this question and offered accounts, both of which, albeit different in their originality, are equally provocative. Both acknowledge that a scientific object like a geometrical theorem or a chemical equation has a history because (...) it is only constituted in and transmitted through history. But they see that history as a part of its ideality, so that, although historical, a scientific object retains its identity as one and the same object. (shrink)

The majority of analyses investigating the professionalisation of scientific domains tend to assume the linear and general features of this transformation. These studies focus on the shift from a non-professionalised state to a professionalised state. This dual approach, however, crucially lacks some other aspects of the process of professionalisation. This issue is discussed within the context of the growth of prehistoric archaeology in France from the 1940s, by observing scientific societies, national research organisations and their social networks. Looking (...) at the scale of Georges Laplace’s career and that of his research group, which studied the typologie analytique method, this article demonstrates the benefits of a ternary model which also encompasses the modes of refusal of professionalisation. (shrink)

Scientific models typically contain idealizations, or assumptions that are known not to be true. Philosophers have long questioned the nature of idealizations: Are they heuristic tools that will be abandoned? Or rather fictional representations of reality? And how can we reconcile them with realism about knowledge of nature? Immanuel Kant developed an account of scientific investigation that can inspire a new approach to the contemporary debate. Kant argued that scientific investigation is possible only if guided (...) by ideal assumptions—what he calls “regulative ideas”. These ideas are not true of objects of nature, and yet they are not heuristic tools or fictional represen- tations. They are necessary rules governing the construction and assessment of scientific explanations. In this paper, I suggest that some idealizations can be interpreted as having necessary regulative value and as being compatible with scientific realism. I first analyze the puzzle of the nature of idealization and present the main approaches to this topic in the literature. Second, I reconsider the puzzle vis-a-vis a restricted, Kantian definition of idealization and a novel characterization of the relation between idealization and truth. Finally, I discuss in detail an example of idealization (the Hardy-Weinberg equilibrium) along the suggested Kantian lines. (shrink)

The debate between scientific realism and anti-realism remains at a stalemate, making reconciliation seem hopeless. Yet, important work remains: exploring a common ground, even if only to uncover deeper points of disagreement and, ideally, to benefit both sides of the debate. I propose such a common ground. Specifically, many anti-realists, such as instrumentalists, have yet to seriously engage with Sober's call to justify their preferred version of Ockham's razor through a positive account. Meanwhile, realists face a similar challenge: providing (...) a non-circular explanation of how their version of Ockham's razor connects to truth. The common ground I propose addresses these challenges for both sides; the key is to leverage the idea that everyone values some truths and to draw on insights from scientific fields that study scientific inference—namely, statistics and machine learning. This common ground also isolates a distinctively epistemic root of the irreconcilability in the realism debate. (shrink)

Bird argues that scientific progress consists in increasing knowledge. Dellsén objects that increasing knowledge is neither necessary nor sufficient for scientific progress, and argues that scientific progress rather consists in increasing understanding. Dellsén also contends that unlike Bird’s view, his view can account for the scientific practices of using idealizations and of choosing simple theories over complex ones. I argue that Dellsén’s criticisms against Bird’s view fail, and that increasing understanding cannot account for scientific (...) progress, if acceptance, as opposed to belief, is required for scientific understanding. (shrink)

What is scientific progress? On Alexander Bird’s epistemic account of scientific progress, an episode in science is progressive precisely when there is more scientific knowledge at the end of the episode than at the beginning. Using Bird’s epistemic account as a foil, this paper develops an alternative understanding-based account on which an episode in science is progressive precisely when scientists grasp how to correctly explain or predict more aspects of the world at the end of the episode (...) than at the beginning. This account is shown to be superior to the epistemic account by examining cases in which knowledge and understanding come apart. In these cases, it is argued that scientific progress matches increases in scientific understanding rather than accumulations of knowledge. In addition, considerations having to do with minimalist idealizations, pragmatic virtues, and epistemic value all favor this understanding-based account over its epistemic counterpart. (shrink)

Explainable AI (xAI) methods are important for establishing trust in using black-box models. However, recent criticism has mounted against current xAI methods that they disagree, are necessarily false, and can be manipulated, which has started to undermine the deployment of black-box models. Rudin (2019) goes so far as to say that we should stop using black-box models altogether in high-stakes cases because xAI explanations ‘must be wrong’. However, strict fidelity to the truth is historically not a desideratum in science. (...) class='Hi'>Idealizations – the intentional distortions introduced to scientific theories and models – are commonplace in the natural sciences and are seen as a successful scientific tool. Thus, it is not falsehood qua falsehood that is the issue. In this paper, I outline the need for xAI research to engage in idealization evaluation. Drawing on the use of idealizations in the natural sciences and philosophy of science, I introduce a novel framework for evaluating whether xAI methods engage in successful idealizations or deceptive explanations (SIDEs). SIDEs evaluates whether the limitations of xAI methods, and the distortions that they introduce, can be part of a successful idealization or are indeed deceptive distortions as critics suggest. I discuss the role that existing research can play in idealization evaluation and where innovation is necessary. Through a qualitative analysis we find that leading feature importance methods and counterfactual explanations are subject to idealization failure and suggest remedies for ameliorating idealization failure. (shrink)

What does it take to understand a phenomenon ideally, or to the highest conceivable extent? In this paper, we answer this question by arguing for five necessary conditions for ideal understanding: (i) representational accuracy, (ii) intelligibility, (iii) truth, (iv) reasonable endorsement, and (v) fitting. Even if one disagrees that there is some form of ideal understanding, these five conditions can be regarded as sufficient conditions for a particularly deep level of understanding. We then argue that grasping, novel predictions, and transparency (...) are not reasonable conditions for ideal understanding. (shrink)

This paper will analyze three historical cases (Francis Bacon, Galileo Galilei and Margaret Cavendish) that exemplify the complexity of the interaction between science and religion in the Scientific Revolution and confirm the interpretation of J. H. Brooke, according to which, in this historical context –rather than a separation- a differentiation took hold between them. We will hold that although these authors agreed in proposing the separation of science and religion as an ideal, each in their own way made an (...) articulation between the two that in the long run prevented a complete separation. This articulation was due to both epistemic and extra-epistemic reasons and manifests a tension that was characteristic of the Scientific Revolution. (shrink)

The focus in the literature on scientific explanation has shifted in recent years towards modelbased approaches. The idea that there are simple and true laws of nature has met with objections from philosophers such as Nancy Cartwright (1983) and Paul Teller (2001), and this has made a strictly Hempelian D-N style explanation largely irrelevant to the explanatory practices of science (Hempel & Oppenheim, 1948). Much of science does not involve subsuming particular events under laws of nature. It is increasingly (...) recognized that science across the disciplines is to some degree a patchwork of scientific models, with different methods, strategies, and with varying degrees of successful prediction and explanation. And so accounts of scientific explanation have reflected this change of perspective and model-based approaches have flourished in the explanation literature (Batterman, 2002b; Bokulich, 2008; Craver, 2006; Woodward, 2003). (shrink)

The boundaries of social categories are frequently altered to serve normative projects, such as social reform. Griffiths and Khalidi argue that the value-driven modification of categories diminishes the epistemic value of social categories. I argue that concerns over value-modified categories stem from problematic assumptions of the value-free ideal of science. Contrary to those concerns, non-epistemic value considerations can contribute to the epistemic improvement of a scientific category. For example, the early history of the category infantile autism shows how non-epistemic (...) value considerations can contribute to delimiting and establishing infantile autism as a distinct category in mainstream psychiatry. In the case of infantile autism, non-epistemic considerations have led to a new interpretation of existing data, the expansion of research to include biology, and the creation of diagnostic criteria that further contribute to collecting relevant data. Given this case study, it can be argued that non-epistemic values can improve our knowledge of scientific categories. (shrink)

Scientific explanations must bear the proper relationship to the world: they must depict what, out in the world, is responsible for the explanandum. But explanations must also bear the proper relationship to their audience: they must be able to create human understanding. With few exceptions, philosophical accounts of explanation either ignore entirely the relationship between explanations and their audience or else demote this consideration to an ancillary role. In contrast, I argue that considering an explanation’s communicative role is crucial (...) to any satisfactory account of explanation. (shrink)

Intuitively, science progresses from truth to truth. A glance at history quickly reveals that this idea is mistaken. We often learn from scientific theories that turned out to be false. This chapter focuses on a different challenge: Idealisations are deliberately and ubiquitously used in science. Scientists thus work with assumptions that are known to be false. Any account of scientific progress needs to account for this widely accepted scientific practice. It is examined how the four dominant accounts—the (...) problem-solving account, the truthlikeness account, the epistemic account, and the noetic account—can cope with the challenge from idealisation, with an eye on indispensable idealisations. One upshot is that, on all accounts, idealisations can promote progress. Only some accounts allow them to constitute progress. (shrink)

In a recent revision (chapter 4 of Nowakowa and Nowak 2000) of an older article Leszek Nowak (1992) has attempted to rebut Niiniluoto’s 1990 critical suggestion that proponents of the Poznań idealizational approach to the sciences have committed a rather elementary logical error in the formal machinery that they advocate for use in the analysis of scientific methodology. In this paper I criticize Nowak’s responses to Niiniluoto’s suggestion, and, subsequently, work out some of the consequences of that criticism for (...) understanding the role that idealization plays in scientific methodology. (shrink)

Scientific realism is a thesis about the success of science. Most traditionally: science has been so successful at prediction and guiding action because its best theories are true (or approximately true or increasing in their degree of truth). If science is in the business of doing its best to generate true theories, then we should turn to those theories for explanatory knowledge, predictions, and guidance of our actions and decisions. Views that are popular in contemporary philosophy of science about (...) scientific modeling and the centrality of idealization create several challenges for this traditional form of scientific realism. Yet the basic idea behind scientific realism that science has been and will continue to be epistemically successful is deeply appealing. This chapter explores the challenges posed by idealization and scientific modeling to motivate a scientific realism fully divorced from the idea that science is in the business of generating true theories. On the resulting view, the objects of scientific knowledge are causal patterns, so this knowledge only ever provides partial, simplified accounts of a complex reality. This variety of selective realism better accommodates the nature of our present-day scientific successes and offers an interpretation of scientific progress that resists the antirealist’s pessimism. (shrink)

What makes science trustworthy to the public? This chapter examines one proposed answer: the trustworthiness of science is based at least in part on its independence from the idiosyncratic values, interests, and ideas of individual scientists. That is, science is trustworthy to the extent that following the scientific process would result in the same conclusions, regardless of the particular scientists involved. We analyze this "idiosyncrasy-free ideal" for science by looking at philosophical debates about inductive risk, focusing on two recent (...) proposals which offer different methods of avoiding idiosyncrasy: the high epistemic standards proposal and the democratic values proposal. (shrink)

Fictionalism plays a significant role in philosophy today, with defenses spanning mathematics, morality, ordinary objects, truth, modality, and more.1 Fictionalism in the philosophy of science is also gaining attention, due in particular to the revival of Hans Vaihinger’s work from the early twentieth century and to heightened interest in idealization in scientific practice.2 Vaihinger maintains that there is a ubiquity of fictions in science and, among other things, argues that Nietzsche supports the position. Yet, while contemporary commentators have focused (...) on fictionalism in Nietzsche’s moral philosophy, his view of fictions in science has remained largely unexamined.3 In this article, I begin... (shrink)

In this article, we explore the impact of non-epistemic factors, such as social identity and cultural biases, on the formation and revision of beliefs. This type of impact is evident in contexts of opinion polarisation where the acceptance of scientific theses by groups of non-experts is at stake. Im these contexts digital media and social networks often play a central role. To analyse the impact of non-epistemic factors from an epistemological perspective, we employ a non-ideal approach to epistemology that (...) takes into account some key non-epistemic factors through the concept of epistemic filter. By means of this concept we explain the selective acceptance of information, and we show how background assumptions and social values which are deeply rooted in an inquiring subject influence the selection and evaluation of evidence and sources of information. Through this non-ideal approach, we analyse the dynamics of scientific denialism, framing it as an epistemic phenomenon in which social and cultural influences shape and distort epistemic practices. We conclude that understanding these underlying mechanisms is crucial to addressing the challenges posed by misinformation and the deep social divisions that result from it. (shrink)

This article explains Kant’s claim that sciences must take, at least as their ideal, the form of a ‘system’. I argue that Kant’s notion of systematicity can be understood against the background of de Jong & Betti’s Classical Model of Science (2010) and the writings of Georg Friedrich Meier and Johann Heinrich Lambert. According to my interpretation, Meier, Lambert, and Kant accepted an axiomatic idea of science, articulated by the Classical Model, which elucidates their conceptions of systematicity. I show that (...) Kant’s critique of the mathematical method is compatible with his adherence to this axiomatic conception of science. I further show that systematicity furthers traditionally accepted logical ideals of scientific knowledge, which explains why Meier and Kant think that sciences must be ‘systematic’. (shrink)

We introduce the notion of complexity, first at an intuitive level and then in relatively more concrete terms, explaining the various characteristic features of complex systems with examples. There exists a vast literature on complexity, and our exposition is intended to be an elementary introduction, meant for a broad audience. -/- Briefly, a complex system is one whose description involves a hierarchy of levels, where each level is made of a large number of components interacting among themselves. The time evolution (...) of such a system is of a complex nature, depending on the interactions among subsystems in the next level below the one under consideration and, at the same time, conditioned by the level above, where the latter sets the context for the evolution. Generally speaking, the interactions among the constituents of the various levels lead to a dynamics characterized by numerous characteristic scales, each level having its own set of scales. What is more, a level commonly exhibits ‘emergent properties’ that cannot be derived from considerations relating to its component systems taken in isolation or to those in a different contextual setting. In the dynamic evolution of some particular level, there occurs a self-organized emergence of a higher level and the process is repeated at still higher levels. -/- The interaction and self-organization of the components of a complex system follow the principle commonly expressed by saying that the ‘whole is different from the sum of the parts’. In the case of systems whose behavior can be expressed mathematically in terms of differential equations this means that the interactions are nonlinear in nature. -/- While all of the above features are not universally exhibited by complex systems, these are nevertheless indicative of a broad commonness relative to which individual systems can be described and analyzed. There exist measures of complexity which, once again, are not of universal applicability, being more heuristic than exact. The present state of knowledge and understanding of complex systems is itself an emerging one. Still, a large number of results on various systems can be related to their complex character, making complexity an immensely fertile concept in the study of natural, biological, and social phenomena. -/- All this puts a very definite limitation on the complete description of a complex system as a whole since such a system can be precisely described only contextually, relative to some particular level, where emergent properties rule out an exact description of more than one levels within a common framework. -/- We discuss the implications of these observations in the context of our conception of the so-called noumenal reality that has a mind-independent existence and is perceived by us in the form of the phenomenal reality. The latter is derived from the former by means of our perceptions and interpretations, and our efforts at sorting out and making sense of the bewildering complexity of reality takes the form of incessant processes of inference that lead to theories. Strictly speaking, theories apply to models that are constructed as idealized versions of parts of reality, within which inferences and abstractions can be carried out meaningfully, enabling us to construct the theories. -/- There exists a correspondence between the phenomenal and the noumenal realities in terms of events and their correlations, where these are experienced as the complex behavior of systems or entities of various descriptions. The infinite diversity of behavior of systems in the phenomenal world are explained within specified contexts by theories. The latter are constructs generated in our ceaseless attempts at interpreting the world, and the question arises as to whether these are reflections of `laws of nature' residing in the noumenal world. This is a fundamental concern of scientific realism, within the fold of which there exists a trend towards the assumption that theories express truths about the noumenal reality. We examine this assumption (referred to as a ‘point of view’ in the present essay) closely and indicate that an alternative point of view is also consistent within the broad framework of scientific realism. This is the view that theories are domain-specific and contextual, and that these are arrived at by independent processes of inference and abstractions in the various domains of experience. Theories in contiguous domains of experience dovetail and interpenetrate with one another, and bear the responsibility of correctly explaining our observations within these domains. -/- With accumulating experience, theories get revised and the network of our theories of the world acquires a complex structure, exhibiting a complex evolution. There exists a tendency within the fold of scientific realism of interpreting this complex evolution in rather simple terms, where one assumes (this, again, is a point of view) that theories tend more and more closely to truths about Nature and, what is more, progress towards an all-embracing ‘ultimate theory’ -- a foundational one in respect of all our inquiries into nature. We examine this point of view closely and outline the alternative view -- one broadly consistent with scientific realism -- that there is no ‘ultimate’ law of nature, that theories do not correspond to truths inherent in reality, and that successive revisions in theory do not lead monotonically to some ultimate truth. Instead, the theories generated in succession are incommensurate with each other, testifying to the fact that a theory gives us a perspective view of some part of reality, arrived at contextually. Instead of resembling a monotonically converging series successive theories are analogous to asymptotic series. -/- Before we summarize all the above considerations, we briefly address the issue of the complexity of the {\it human mind} -- one as pervasive as the complexity of Nature at large. The complexity of the mind is related to the complexity of the underlying neuronal organization in the brain, which operates within a larger biological context, its activities being modulated by other physiological systems, notably the one involving a host of chemical messengers. The mind, with no materiality of its own, is nevertheless emergent from the activity of interacting neuronal assemblies in the brain. As in the case of reality at large, there can be no ultimate theory of the mind, from which one can explain and predict the entire spectrum of human behavior, which is an infinitely rich and diverse one. (shrink)

According to Popper's rationality principle, agents act in the most adequate way according to the objective situation. I propose a new interpretation of the rationality principle as consisting of an idealization and two abstractions. Based on this new interpretation, I critically discuss the privileged status that Popper ascribes to it as an integral part of all social scientific models. I argue that as an idealization, the rationality principle may play an important role in the social sciences, but it also (...) has inherent limitations that inhibit it from having the privileged status that Popper ascribes to it in all cases. (shrink)

Even if the “value-free ideal of science” (VFI) were an unattainable goal, one could ask: can it be a useful fiction, one that is beneficial for the research community and society? This question is particularly crucial for scholars and institutions concerned with research integrity (RI), as one cannot offer normative guidance to researchers without making some assumptions about what ideal scientific research looks like. Despite the insofar little interaction between scholars studying RI and those working on values in science, (...) the overlap of topics and interests make collaboration between the two fields promising for understanding research and its ethics. Here, we identify—for the use of RI scholars—the non-epistemic reasons (societal, political, professional) for and against the VFI considered in the literature. All of these are concerned with the beneficial or detrimental consequences that endorsing the VFI would have on society, policy-making, or the scientific community, with some authors appealing to the same principles to argue for opposite positions. Though most of the reviewed articles do not endorse the VFI, it is generally agreed that some constraints have to be put on the use of non-epistemic values. Disagreement on the utility of the VFI lies both on the different epistemic-descriptive positions taken by different authors, and on the scarcity of relevant empirical studies. Engaging critically with the reasons here identified and more in general with the values in science debate will help the RI community decide whether the VFI should be included in future codes of conduct. (shrink)

In this paper we present a new framework of idealization in biology. We characterize idealizations as a network of counterfactual and hypothetical conditionals that can exhibit different “degrees of contingency”. We use this idea to say that, in departing more or less from the actual world, idealizations can serve numerous epistemic, methodological or heuristic purposes within scientific research. We defend that, in part, this structure explains why idealizations, despite being deformations of reality, are so successful in (...) scientific practice. For illustrative purposes, we provide an example from population genetics, the Wright-Fisher Model. (shrink)

Appeals to intersectionality serve to remind us that social categories like race and gender cannot be adequately understood independently from each other. But what, exactly, is the intersectional thesis a thesis about? Answers to this question are remarkably diverse. Intersectionality is variously understood as a claim about the nature of social kinds, oppression, or experience ; about the limits of antidiscrimination law or identity politics ; or about the importance of fuzzy sets, multifactor analysis, or causal modeling in social science.

This paper explores the integration of Michael Strevens' concept of idealizations with my previous framework of similarity spaces and context-dependence to develop a comprehensive account of ideal explanations in scientific practice. Idealizations, which involve deliberate falsifications, play a crucial role in distinguishing between causally relevant and irrelevant factors in scientific models. Context-dependent mapping provides a structured approach to handling complementarities and context-dependent phenomena by mapping different observational contexts to distinct sets of physical laws. By combining these (...) two ideas, I will construct an idealized context-dependent mapping structure and discuss how ideal similarity spaces within the framework of context-dependent mapping can enhance our understanding of complex scientific phenomena, especially those involving wave-particle duality and black hole complementarity. I also aim to discuss the types of idealizations that may exist within explanation and examine their relations to the mapping. (shrink)

The move from respecting science to scientism, i.e., the idealization of science and scientific method, is simple: We go from acknowledging the sciences as fruitful human activities to oversimplifying the ways they work, and accepting a fuzzy belief that Science and Scientific Method, will give us a direct pathway to the true making of the world, all included. The idealization of science is partly the reason why we feel we need to impose the so-called scientific terminologies and (...) methodologies to all aspects of our lives, education too. Under this rationale, educational policies today prioritize science, not only in curriculum design, but also as a method for educational practice. One might expect that, under the scientistic rationale, science education would thrive. Contrariwise, I will argue that scientism disallows science education to give an accurate image of the sciences. More importantly, I suggest that scientism prevents one of science education’s most crucial goals: help students think. Many of my arguments will borrow the findings and insights of science education research. In the last part of this paper, I will turn to some of the most influential science education research proposals and comment on their limits. If I am right, and science education today does not satisfy our most important reasons for teaching science, perhaps we should change not just our teaching strategies, but also our scientistic rationale. But that may be a difficult task. (shrink)

This article is intended as a contribution to the current debates about the relationship between politics and the philosophy of science in the Vienna Circle. I reconsider this issue by shifting the focus from philosophy of science as theory to philosophy of science as practice. From this perspective I take as a starting point the Vienna Circle’s scientific world-conception and emphasize its practical nature: I reinterpret its tenets as a set of recommendations that express the particular epistemological attitude in (...) which both the Vienna Circle’s (doing) philosophy of science and its political engagement were rooted. -/- Regarding politics, and referring to new primary sources, I reconstruct how the scientific world-conception placed the Vienna Circle within a neoliberal-socialist political network that pursued concrete political aims. In light of my reconstruction I shall argue that neither the Vienna Circle’s alleged ethical noncognitivism nor its alleged adhesion to the Weberian ideal of a value-free science rules out the possibility of ascribing to the Vienna Circle a politically engaged philosophy of science: the case of the Vienna Circle shows how philosophy of science, as a public activity, can itself become a form of political engagement, even without necessarily entailing a theory of objective values. (shrink)

Straightening the current ‘value-laden turn’ (VLT) in the philosophical literature on values in science, and reviving the legacy of the value-free ideal of science (VFI), this paper argues that the influence of extra-scientific values should be minimised—not excluded—in the core phase of scientific inquiry where claims are accepted or rejected. Noting that the original arguments for the VFI (ensuring the truth of scientific knowledge, respecting the autonomy of science results users, preserving public trust in science) have not (...) been satisfactorily addressed by proponents of the VLT, it proposes four prerequisites which any model for values in the acceptance/rejection phase of scientific inquiry should respect, coming from the fundamental requirement to distinguish between facts and values: (1) the truth of scientific knowledge must be ensured; (2) the uncertainties associated with scientific claims must be stated clearly; (3) claims accepted into the scientific corpus must be distinguished from claims taken as a basis for action. An additional prerequisite of (4) simplicity and systematicity is desirable, if the model is to be applicable. Methodological documents from international institutions and regulation agencies are used to illustrate the prerequisites. A model combining Betz’s conception (stating uncertainties associated with scientific claims) and Hansson’s corpus model (ensuring the truth of the scientific corpus and distinguishing it from other claims taken as a basis for action) is proposed. Additional prerequisites are finally suggested for future research, stemming from the requirement for philosophy of science to self-reflect on its own values: (5) any model for values in science must be descriptively and normatively relevant; and (6) its consequences must be thoroughly assessed. (shrink)

This paper analyzes Immanuel Kant’s views on mechanical explanation on the basis of Christian Wolff’s idea of scientific demonstration. Kant takes mechanical explanations to explain properties of wholes in terms of their parts. I reconstruct the nature of such explanations by showing how part-whole conceptualizations in Wolff’s logic and metaphysics shape the ideal of a proper and explanatory scientific demonstration. This logico-philosophical background elucidates why Kant construes mechanical explanations as ideal explanations of nature.

Good chefs know the importance of maintaining sharp knives in the kitchen. What’s their secret? A well-worn Taoist allegory offers some advice. The king asks about his butcher’s impressive knifework. “Ordinary butchers,” he replied “hack their way through the animal. Thus their knife always needs sharpening. My father taught me the Taoist way. I merely lay the knife by the natural openings and let it find its own way through. Thus it never needs sharpening” (Kahn 1995, vii; see also Watson (...) 2003, 46). Plato famously employed this image as an analogy for the reality of his Forms (Phaedrus, 265e). Just like an animal, the world comes pre-divided for us. Ideally, our best theories will be those which “carve nature at its joints”. While Plato employed the “carving” metaphor to convey his views about the reality of his celebrated Forms, its most common contemporary use involves the success of science -- particularly, its success in identifying distinct kinds of things. Scientists often report discovering new kinds of things -- a new species of mammal or novel kind of fundamental particle, for example -- or uncovering more information about already familiar kinds. Moreover, we often notice considerable overlap in different approaches to classification. As Ernst Mayr put it: No naturalist would question the reality of the species he may find in his garden, whether it is a catbird, chickadee, robin, or starling. And the same is true for trees or flowering plants. Species at a given locality are almost invariably separated from each other by a distinct gap. Nothing convinced me so fully of the reality of species as the observation . . . that the Stone Age natives in the mountains of New Guinea recognize as species exactly the same entities of nature as a western scientist. (Mayr 1987, 146) Such agreement is certainly suggestive. It suggests that taxonomies are discoveries rather than mere inventions. Couple this with their utility in scientific inference and explanation and we have compelling reason for accepting the objective, independent reality of many different natural kinds of things.. (shrink)

Scientific hedges are communicative devices used to qualify and weaken scientific claims. Gregor Betz has argued—unconvincingly, we think—that hedging can rescue the value-free ideal for science. Nevertheless, Betz is onto something when he suggests there are political principles that recommend scientists hedge public-facing claims. In this article, we recast this suggestion using the notion of public justification. We formulate and reject a Rawlsian argument that locates the justification for hedging in its ability to forge consensus. On our alternative (...) proposal, hedging is often justified because it renders scientific claims as publicly accessible reasons. (shrink)

Nietzsche sometimes praises the drive to order—to simplify, organize, and draw clear boundaries—as expressive of a vital "classical" style, or an Apollonian artistic drive to calmly contemplate forms displaying "epic definiteness and clarity." But he also sometimes harshly criticizes order, as in the pathological dialectics or "logical schematism" that he associates paradigmatically with Socrates. I challenge a tradition that interprets Socratism as an especially one-sided expression of, or restricted form of attention to, the Apollonian: they are more radically disparate. Beyond (...) strengthening the case for this basic point, I develop a distinctive account of what, exactly, distinguishes the Apollonian-classical and Socratic forms of order. To this end, I advance interrelated interpretations of Apollonian-classical simplicity and the "cold" calm that it elicits, by contrast to superficially similar Socratic phenomena. This illuminates Nietzsche's broader ambivalence toward science, in part by clarifying the nature and value of an idealized Apollonian science. (shrink)

The aim of this article is to argue that ontological choices in scientific practice undermine common formulations of the value-free ideal in science. First, I argue that the truth values of scientific statements depend on ontological choices. For example, statements about entities such as species, race, memory, intelligence, depression, or obesity are true or false relative to the choice of a biological, psychological, or medical ontology. Second, I show that ontological choices often depend on non-epistemic values. On the (...) basis of these premises, I argue that it is often neither possible nor desirable to evaluate scientific statements independently of non-epistemic values. Finally, I suggest that considerations of ontological choices do not only challenge the value-free ideal but also help to specify positive roles of non-epistemic values in an often neglected area of scientific practice. (shrink)

In this chapter, I argue that scientific practice in the neurosciences of cognition is not conducive to the discovery of natural kinds of cognitive capacities. The “neurosciences of cognition” include cognitive neuroscience and cognitive neurobiology, two research areas that aim to understand how the brain gives rise to cognition and behavior. Some philosophers of neuroscience have claimed that explanatory progress in these research areas ultimately will result in the discovery of the underlying mechanisms of cognitive capacities. Once such mechanistic (...) understanding is achieved, cognitive capacities purportedly will be relegated into natural kind categories that correspond to real divisions in the causal structure of the world. I provide reasons here, however, in support of the claim that the neurosciences of cognition currently are not on a trajectory for discovering natural kinds. As I explain, this has to do with how mechanistic explanations of cognitive capacities are developed. Mechanistic explanations and the kinds they explain are abstract representational byproducts of the conceptual, experimental and integrative practices of neuroscientists. If these practices are not coordinated towards developing mechanistic explanations that mirror the causal structure of the world, then natural kinds of cognitive capacities will not be discovered. I provide reasons to think that such coordination is currently lacking in the neurosciences of cognition and indicate where changes in these practices appropriate to the natural kinds ideal would be required if achieving this ideal is indeed the goal. However, I suggest that an evaluation of current practices in these research areas is suggestive that discovering natural kinds of cognitive capacities is not the goal. (shrink)

What should the goals of scientific inquiry be? What questions should scientists investigate, and how should our resources be distributed between different lines of investigation? Philip Kitcher has suggested that we should answer these questions by appealing to an ideal based on the consideration of hypothetical democratic deliberations under ideal circumstances. The paper argues that we have no reason to adopt this ideal. The paper examines both traditional arguments for democracy and Kitcher's own reasons for adopting this ideal, as (...) presented in Kitcher (2001) and in Kitcher (2011b), and argues that none of these supports adoption of Kitcher's proposed ideal. (shrink)

Hermann von Helmholtz allows for not only physiological facts and psychological inferences, but also perspectival reasoning, to influence perceptual experience and knowledge gained from perception. But Helmholtz also defends a version of the view according to which there can be a kind of “perspectival truth” revealed in scientific research and investigation. Helmholtz argues that the relationships between subjective and objective, real and actual, actual and illusory, must be analyzed scientifically, within experience. There is no standpoint outside experience from which (...) we can reason, no extra-sensory knowledge of the constitution of the “ideal subject” or of the properties of “real objects.” In the tradition of psychophysics inherited by Helmholtz, we can arrive at a kind of perspectival analysis of perceptual experience, which embeds an account of that experience within the context of the history and situation of the perceiving subject. That analysis is relative to the perceiving subject, but the perspectival explanations Helmholtz constructs are not thereby relativist: in fact, for Helmholtz, the more squarely the perceiving subject is placed in a scientific, perspectival context, the more facts we are able to learn about her experience and the objects with which she interacts. (shrink)

The Cartesian concept of nature, which has determined modern thinking until the present time, has become obsolete. It shall be shown that Hegel's objective-idealistic conception of nature discloses, in comparison to that of Descartes, new perspectives for the comprehension of nature and that this, in turn, results in possibilities of actualizing Hegel's philosophy of nature. If the argumentation concerning philosophy of nature is intended to catch up with the concrete Being-of-nature and to meet it in its concretion, then this is (...) impossible for the finite spirit in a strictly a priori sense – this is the thesis supported here which is not at all close to Hegel. As the argumentation rather has to consider the conditions of realization concerning the Being-of-nature, too, it is compelled to take up empirical elements – concerning the organism, for instance, system-theoretical aspects, physical and chemical features of the nervous system, etc. With that, on the one hand, empirical-scientific premises are assumed (e.g. the lawlikeness of nature), which on the other hand become (now close to Hegel) possibly able to be founded in the frame of a Hegelian-idealistic conception. In this sense, a double strategy of empirical-scientific concretization and objective-idealistic foundation is followed up, which represents the methodical basic principle of the developed considerations. In the course of the undertaking, the main aspects of the whole Hegelian design concerning the philosophy of nature are considered – space and time, mass and motion, force and law of nature, the organism, the pro-blem of evolution, psychic being – as well as Hegel's basic thesis concerning the philosophy of nature, that therein a tendency toward coherence and idealization manifests itself in the sense of a (categorically) gradually rising succession of nature: from the separateness of space to the ideality of sensation. In the sense of the double strategy of concretization and foundation it is shown that on the one hand possibilities of philosophical penetration concerning actual empirical-scientific results are opened, and on the other hand – in turn – a re-interpretation of Hegel's theorem on the basis of physical, evolution-theoretical and system-theoretical argumentation also becomes possible. In this mutual crossing-over and elucidation of empirical and Hegelian argumentation not only do perspectives of a new comprehension of nature become visible, but also, at the same time – as an essential consequence of this methodical principle – thoughts on the possibilities of actualizing Hegel's philosophy of nature. (shrink)

I develop the anticipatory argument for the view that it is nomologically possible that some non-biological creatures are phenomenally conscious, including conventional, silicon-based AI systems. This argument rests on the general idea that we should make our beliefs conform to the outcomes of an ideal scientific process and that such an ideal scientific process would attribute consciousness to some possible AI systems. This kind of ideal scientific process is an ideal application of the iterative natural kind (INK) (...) strategy, according to which one should investigate consciousness by treating it as a natural kind which iteratively explains observable patterns and correlations between potentially consciousness-relevant features. The relevant AI systems are psychological duplicates. These are hypothetical non-biological creatures which share the coarse-grained functional organization of humans. I argue that an ideal application of the INK strategy would attribute consciousness to psychological duplicates because this gives rise to a simpler and more unifying explanatory account of biological and non-biological cognition. If my argument is sound, then creatures made from the same material as conventional AI systems can be conscious, thus removing one of the main uncertainties for assessing AI consciousness and suggesting that AI consciousness may be a serious near-term concern. (shrink)

O objetivo deste artigo é apontar cinco aspectos do pensamento nietzschiano que podem ser relevantes para os debates da filosofia da ciência em torno da natureza e representação do conhecimento científico. Para tanto, é realizada uma revisão de literatura com o objetivo de selecionar trechos de obras nietzschianas como O nascimento da tragédia, Genealogia da moral, A gaia ciência e outras que permitam interpretar Nietzsche como um filósofo da ciência preocupado com a construção do conhecimento cientifico sobre a realidade física. (...) Como resultado é possível identificar uma proposta epistemológica na perspectiva nietzschiana, cuja representação objetiva do mundo deve apontar para uma estética da vida. -/- The purpose of this article is to point out five aspects of Nietzschean thought that may be relevant to debates in the philosophy of science around the nature and representation of scientific knowledge. To this end, a literature review is carried out with the aim of selecting excerpts from Nietzschean works such as The Birth of Tragedy, Genealogy of Morals, The Gay Science and others that allow us to interpret Nietzsche as a philosopher of science concerned with the construction of scientific knowledge about the physical reality. As a result, it is possible to identify an epistemological proposal in the Nietzschean perspective, whose objective representation of the world should point to an aesthetics of life. (shrink)

Carnap’s Ideal of Explication and Naturalism is the second book on Rudolf Carnap’s philosophy edited by Pierre Wagner for Palgrave Macmillan’s series The History of Analytic Philosophy. The collection of essays is important for several reasons both for philosophers and historians of philosophy, but some parts of it will also be valuable to anyone interested in general scientific methodologies. I shall first survey the theme in order to locate the collection within the recent philosophical discussion then I will consider (...) the volume itself. (shrink)

What is special about the philosophy of history when the history is about science? I shall focus on an impasse between two perspectives — one seeking an ideal of rationality to guide scientific practices, and one stressing the contingency of the practices. They disagree on what this contingency means for scientific norms. Their impasse underlies some fractious relations within History and Philosophy of Science. Since the late 1960s, this interdisciplinary field has been described, variously, as an “intimate relationship (...) or marriage of convenience”, a “marriage for the sake of reason”, a “troubling interaction ”, a “precarious relationship”, or one at risk of “ epistemological derangement”. -/- My paper has three aims. First, I characterise two idealised perspectives in this impasse: the sublimers and subversives. Then I describe a curious dynamic in which each perspective accuses the other of, simultaneously, claiming too little and too much. Subliming is dismissed for being scholastic, and condemned for being imperialist. Subverting is disparaged for being merely sociological, then criticised for being irrational or relativist. Here I draw on and extend the analyses of science studies in Kitcher, Zammito and others. Second, I argue that sublimers and subversives often talk past each other. Their mutual dismissals and condemnations arise partly because each perspective misconstrues the other’s claims. Each fails to see that the other is interested in different problems and interprets concepts differently. Third, I suggest that my analysis clarifies some current disagreements and old debates about contingency in science. It may also apply to debates on the contingency of norms in non- scientific realms. (shrink)

The appearance of consciousness in the universe remains one of the major mysteries unsolved by science or philosophy. Absent an agreed-upon definition of consciousness or even a convenient system to test theories of consciousness, a confusing heterogeneity of theories proliferate. In pursuit of clarifying this complicated discourse, we here interpret various frameworks for the scientific and philosophical study of consciousness through the lens of social insect evolutionary biology. To do so, we first discuss the notion of a forward test (...) versus a reverse test, analogous to the normal and revolutionary phases of the scientific process. Contemporary theories of consciousness are forward tests for consciousness, in that they strive to become a means to classify the level of consciousness of arbitrary states and systems. Yet no such theory of consciousness has earned sufficient confidence such that it might be actually used as a forward test in ambiguous settings. What is needed now is thus a legitimate reverse test for theories of consciousness, to provide internal and external calibration of different frameworks. A reverse test for consciousness would ideally look like a method for referencing theories of consciousness to a tractable model system. We introduce the Ant Colony Test as a rigorous reverse test for consciousness. We show that social insect colonies, though disaggregated collectives, fulfill many of the prerequisites for conscious awareness met by humans and honey bee workers. A long lineage of philosophically-neutral neurobehavioral, evolutionary, and ecological studies on social insect colonies can thus be redeployed for the study of consciousness in general. We suggest that the ACT can provide insight into the nature of consciousness, and highlight the ant colony as a model system for ethically performing clarifying experiments about consciousness. (shrink)

Counterfactuals abound in science, especially when one deals with models. Some models, namely highly idealized models, have assumptions that are metaphysically impossible. This means that in science one has often to deal with counterpossibles. According to the standard semantics for counterfactuals, all counterpossibles are vacuously true. But scientific practice shows that counterpossibles are not always regarded as vacuously true by scientists. To do justice of the use of counterpossibles in science, some authors think that we should adopt a semantics (...) that allows for impossible worlds. It seems difficult to reconcile the role played by highly idealized models in science with scientific realism. Nevertheless, some authors think that it is possible to provide a realist account of highly idealized models. In this view, scientific realism should not be interpreted as the claim that models aim to provide accurate representations of models’ targets, rather it should be interpreted as the claim that models aim to provide true modal information about models’ targets. This variant of scientific realism seems to imply a commitment to some form of modal realism. I develop an objection to that variant of scientific realism by elaborating on some arguments originally developed to show that there are unknowable facts. (shrink)

This chapter gives an overview of the various themes and issues discussed in the volume. It includes summaries of all chapters and places the contributions, some of which are part of a critical conversation format, in the context of the larger literature and debates.

Levins and Lewontin have contributed significantly to our philosophical understanding of the structures, processes, and purposes of biological mathematical theorizing and modeling. Here I explore their separate and joint pleas to avoid making abstract and ideal scientific models ontologically independent by confusing or conflating our scientific models and the world. I differentiate two views of theorizing and modeling, orthodox and dialectical, in order to examine Levins and Lewontin’s, among others, advocacy of the latter view. I compare the positions (...) of these two views with respect to four points regarding ontological assumptions: (1) the origin of ontological assumptions, (2) the relation of such assumptions to the formal models of the same theory, (3) their use in integrating and negotiating different formal models of distinct theories, and (4) their employment in explanatory activity. Dialectical is here used in both its Hegelian–Marxist sense of opposition and tension between alternative positions and in its Platonic sense of dialogue between advocates of distinct theories. I investigate three case studies, from Levins and Lewontin as well as from a recent paper of mine, that show the relevance and power of the dialectical understanding of theorizing and modeling. (shrink)