Axel Gelfert

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.

Inner speech is a pervasive feature of our conscious mental lives. Yet its function and character remain an issue of philosophical debate. The present paper focuses on the relation between inner speech and natural language and on the cognitive functions that various contributors have ascribed to inner speech. In particular, it is argued that inner speech does not consist of bare, context-free internal presentations of sentential (or subsentential) content, but rather has an ineliminably perspectival element. The proposed model of inner speech, which characterizes inner speech as akin to the testimony of an inner interlocutor, accounts for this perspectival element and, it is argued, is explanatorily superior, insofar as it better explains, amongst other phenomena, the often condensed character of inner speech.

In recent years, the idea has been gaining ground that our traditional conceptions of knowledge and cognition are unduly limiting, in that they privilege what goes on inside the ‘skin and skull’ of an individual reasoner. Instead, it has been argued, knowledge and cognition need to be understood as embodied, situated, and extended. Whether these various interrelations and dependencies are ‘merely’ causal, or are in a more fundamental sense constitutive of knowledge and cognition, is as much a matter of controversy as the degree to which they pose a challenge to ‘traditional’ conceptions of cognition, knowledge and the mind. In this paper we argue that when the idea of ‘extendedness’ is applied to a core concept in epistemology and the philosophy of science—namely, scientific evidence—things appear to be on a much surer footing. The evidential status of data gathered through extended processes—including its utility as justification or warrant—do not seem to be weakened by virtue of being extended, but instead are often strengthened because of it. Indeed, it is often precisely by virtue of this extendedness that scientific evidence grounds knowledge claims, which individuals may subsequently ascribe to themselves. The functional equivalence between machine-based gathering, filtering, and processing of data and human interpretation and assessment is the crucial factor in deciding whether evidence has been gathered, rather than the distinction between intra- and extracranial processes or individual and social processes. To prioritize biological processes here, and to assert the superiority of human cognitive capacities seems both arbitrary and unwarranted with respect to gathering evidence, and ultimately would lead to an unattractive skepticism about many of the methods used in science to gather evidence. In other words, conceiving of scientific evidence as ‘impersonal’ not only better captures the character of evidence-gathering in practice, but also makes sense of a large amount of evidence-gathering that ‘personal’ accounts fail to either acknowledge or accurately describe. Whilst we suggest it is likely that all internally-distributed evidence-gathering processes are merely contingently internal processes, a significant number of externally-distributed evidence-gathering processes are necessarily externally-distributed. Some evidence can only be gathered by extended epistemic agents

Contemporary epistemology of peer disagreement has largely focused on our immediate normative response to prima facie instances of disagreement. Whereas some philosophers demand that we should withhold judgment (or moderate our credences) in such cases, others argue that, unless new evidence becomes available, disagreement at best gives us reason to demote our interlocutor from his peer status. But what makes someone an epistemic peer in the first place? This question has not received the attention it deserves. I begin by surveying different notions of ‘epistemic peer’ that have been peddled in the contemporary literature, arguing that they tend to build normative assumptions about the correct response to disagreement into the notion of peerhood. Instead, I argue, epistemic peerhood needs to be taken seriously in its own right. Importantly, for epistemic agents to count as peers, they should exhibit a comparable degree of reflective awareness of the character and limitations of their own knowledge.

This short paper grew out of an observation—made in the course of a larger research project—of a surprising convergence between, on the one hand, certain themes in the work of Mary Hesse and Nelson Goodman in the 1950/60s and, on the other hand, recent work on the representational resources of science, in particular regarding model-based representation. The convergence between these more recent accounts of representation in science and the earlier proposals by Hesse and Goodman consists in the recognition that, in order to secure successful representation in science, collective representational resources must be available. Such resources may take the form of (amongst others) mathematical formalisms, diagrammatic methods, notational rules, or—in the case of material models—conventions regarding the use and manipulation of the constituent parts. More often than not, an abstract characterization of such resources tells only half the story, as they are constituted equally by the pattern of (practical and theoretical) activities—such as instances of manipulation or inference—of the researchers who deploy them. In other words, representational resources need to be sustained by a social practice; this is what renders them collective representational resources in the first place.

Immanuel Kant is often regarded as an exponent of the ‘individualist’ tradition in epistemology, according to which testimony is not a fundamental source of knowledge. The present paper argues that this view is far from accurate. Kant devotes ample space to discussions of testimony and, in his lectures on logic, arrives at a distinct and stable philosophical position regarding testimony. Important elements of this position consist in (a) acknowledging the ineliminability of testimony; (b) realizing that testimony can establish empirical knowledge with certainty; (c) establishing a presumptive principle regarding the acceptance of testimony; (d) arguing for a symmetry between knowledge based on experience and knowledge based on testimony. Rejecting testimony as a fundamental source of knowledge merely on the basis that no theoretically necessary ground for its truth can be given, would, as Kant puts it, indicate ‘a lack of moral interest’. Such ‘incredulity’ would be a form of ‘logical egoism’: it demonstrates an unwillingness or inability to think oneself in the place of others, yet this we must do if we are to trust our own judgements. While Kant strongly endorses testimony as a source of empirical knowledge, he does, however, make one important restriction: ‘Propositions of reason’ (Vernunftwahrheiten), such as universal moral principles, may not be adopted on the basis of testimony. I argue that this distinction, between testimonial knowledge of empirical matters of fact and individual knowledge of propositions of reason, is an important element of Kant’s epistemology of testimony, as it explains how his strong endorsement of testimony as a source of knowledge can be squared with his equally strong demand for intellectual autonomy. Finally, I comment on the overall implications of this account for Kant’s discussion, elsewhere in his work, of the public nature of communication.

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 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.

This paper argues that the problem of expertise calls for a rapprochement between social epistemology and argumentation theory. Social epistemology has tended to emphasise the role of expert testimony, neglecting the argumentative function of appeals to expert opinion by non-experts. The first half of the paper discusses parallels and contrasts between the two cases of direct expert testimony and appeals to expert opinion by our epistemic peers, respectively. Importantly, appeals to expert opinion need to be advertised as such, if they are to sway an epistemic peer. The second half of the paper sketches a theoretical framework for thinking about assessments of expertise in a unified way, via a ‘default and challenge’ model that emphasises the need for a version of conversational scorekeeping. It is through such scorekeeping that interlocutors can track and coordinate their differences in epistemic outlook. The paper concludes with a genealogical perspective on the function of (attributions of) expertise: acceptance of another’s appeal to expert opinion may be construed as tacit agreement that inquiry, for now, has been taken far enough

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

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. Hume's overall position is more amenable to testimonial acceptance 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.

The present paper contributes to a growing body of philosophical, sociological, and historical analyses of recent nanoscale science and technology. Through a close examination of the origins of contemporary nanotech efforts, their ambitions, and strategic uses, it also aims to provide the basis for a critical theory of emerging technologies more generally, in particular in relation to their alleged convergence in terms of goals and outcomes. The emergence, allure, and implications of nanotechnology, it is argued, can only be fully appreciated if one looks beyond its immediate technical and scientific payoffs to its infrastructural and ideological aspects. While nanotechnology aims to reshape the world 'atom by atom', its most tangible result so far has been the profound effect it has had on the organization of science-at-large, not least as the result of a thorough reshaping of the 'soft' funding infrastructure that places signifi cant constraints on the pursuit of long-term scientific research programmes. The paper concludes by noting a persistent, and perhaps deepening, gap between the utopian visions of some of nanotechnology's most vocal proponents and the realities of contemporary nanotechnological practice, which continue to be marked by global inequities.

This paper contrasts and compares strategies of model-building in condensed matter physics and biology, with respect to their alleged unequal susceptibility to trade-offs between different theoretical desiderata. It challenges the view, often expressed in the philosophical literature on trade-offs in population biology, that the existence of systematic trade-offs is a feature that is specific to biological models, since unlike physics, biology studies evolved systems that exhibit considerable natural variability. By contrast, I argue that the development of ever more sophisticated experimental, theoretical, and computational methods in physics is beginning to erode this contrast, since condensed matter physics is now in a position to measure, describe, model, and manipulate sample-specific features of individual systems – for example at the mesoscopic level – in a way that accounts for their contingency and heterogeneity. Model-building in certain areas of physics thus turns out to be more akin to modeling in biology than has been supposed and, indeed, has traditionally been the case.

This paper argues that a successful philosophical analysis of models and simulations must accommodate an account of mathematically rigorous results. Such rigorous results may be thought of as genuinely model-specific contributions, which can neither be deduced from fundamental theory nor inferred from empirical data. Rigorous results provide new indirect ways of assessing the success of models and simulations and are crucial to understanding the connections between different models. This is most obvious in cases where rigorous results map different models on to one another. Not only does this put constraints on the extent to which performance in specific empirical contexts may be regarded as the main touchstone of success in scientific modelling, it also allows for the transfer of warrant across different models. Mathematically rigorous results can thus come to be seen as not only strengthening the cohesion between scientific strategies of modelling and simulation, but also as offering new ways of indirect confirmation

The first book since Coady's 1992 'Testimony: A Philosophical Study' to offer a thorough survey and a philosophical introduction to testimony and its epistemological problems, while at the same time advancing a novel view that proposes independent justificatory pathways for the acceptance and rejection of testimony, respectively. // Table of Contents: // Introduction / 1. What is Testimony? / 2. The Testimonial Conundrum / 3. Testimony, Perception, Memory, and Inference / 4. Testimony and Evidence / 5. Reductionism and Anti-Reductionism / 6. Hybrid Theories of Testimony / 7. Testimonial Knowledge: Transmission and Generation / 8. Trust and Assurance / 9. Expert Testimony / 10. Pathologies of Testimony / 11. Testimony and the Value of Knowledge / Glossary / Bibliography / Index

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

Hume concludes Book II of his Treatise of Human Nature with a section on the passion of curiosity, ‘that love of truth, which was the first source of all our enquiries’. At first sight, this characterisation of curiosity – as the motivating factor in that specifically human activity that is the pursuit of knowledge – may seem unoriginal. However, when Hume speaks of the ‘source of all our enquiries’, he is referring both to the universal human pursuit of knowledge and to his own philosophical project. Seen in this light, his discussion of curiosity takes on a new significance, as it weaves together elements of his systematic account of human nature – notably, his theory of cognition and motivation – with observations about the pursuit of philosophy as well as the progress of the arts and sciences. In the present paper, I offer a reconstruction of Hume’s view on curiosity and its role in cognition and inquiry.

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.

When it comes to the public debate about the challenge of global climate change, moral questions are inextricably intertwined with epistemological ones. This manifests itself in at least two distinct ways. First, for a fixed set of epistemic standards, it may be irresponsible to delay policy-making until everyone agrees that such standards have been met. This has been extensively discussed in the literature on the precautionary principle. Second, key actors in the public debate may – for strategic reasons, or out of simple carelessness – engage in the selective variation of epistemic standards in response to evidence that would threaten to undermine their core beliefs, effectively leading to epistemic double standards that make rational agreement impossible. The latter scenario is aptly described as an instance of what Stephen Gardiner calls ‘epistemic corruption’. In the present paper, I aim to give an explanation of the cognitive basis of epistemic corruption and discuss its place within the moral landscape of the debate. In particular, I argue that epistemic corruption often reflects an agent’s attempt to reduce dissonance between incoming scientific evidence and the agent’s ideological core commitments. By selectively discounting the former, agents may attempt to preserve the coherence of the latter, yet in doing so they threaten to damage the integrity of evidence-based deliberation.

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.

The present paper argues for a more complete integration between recent “genealogical” approaches to the problem of knowledge and evolutionary accounts of the development of human cognitive capacities and practices. A structural tension is pointed out between, on the one hand, the fact that theexplicandumof genealogical stories is a specifically human trait and, on the other hand, the tacit acknowledgment, shared by all contributors to the debate, that human beings have evolved from non-human beings. Since humans differ from their predecessors in more ways than just the lack of a particular concept or cognitive ability, this casts doubt on the widely shared assumption (the “Constancy Assumption”) that, when constructing a genealogical narrative for a particular concept (e.g., our contemporary concept of knowledge), it is permissible to hold all other factors (e.g., individual “on-board” cognitive capacities) fixed. What is needed instead, I argue, is an ecological perspective that views knowledge as an adaptive response to an evolutionary constellation that allows for a diversity of selective pressures. Several examples of specific conceptual pressures at different stages in human evolution are discussed.

The present paper examines the role of exact results in the theory of many‐body physics, and specifically the example of the Mermin‐Wagner theorem, a rigorous result concerning the absence of phase transitions in low‐dimensional systems. While the theorem has been shown to hold for a wide range of many‐body models, it is frequently ‘violated’ by results derived from the same models using numerical techniques. This raises the question of how scientists regulate their theoretical commitments in such cases, given that the models, too, are often described as approximations to the underlying ‘full’ many‐body problem.

Local reductionism purports to defend a middle ground in the debate about the epistemic status of testimony-based beliefs. It does so by acknowledging the practical ineliminability of testimony as a source of knowledge, while insisting that such an acknowledgment need not entail a default-acceptance view, according to which there exists an irreducible warrant for accepting testimony. The present paper argues that local reductionism is unsuccessful in its attempt to steer a middle path between reductionism and anti-reductionism about testimonial justification. In particular, it challenges local reductionism 'from within', without appealing to anti-reductionist intuitions. By offering novel arguments to the effect that local reductionism fails by its own standards, the present paper considerably strengthens the case against this version of reductionism. Local reductionism, it is argued, fails for three main reasons. First, it cannot account for the rationality of testimonial rejection in paradigmatic cases, even though the possibility of rational rejection is thought to be of central justificatory importance. Second, it does not provide a sufficiently distinct non-testimonial basis to which testimonial justification can be successfully reduced. Finally, local reductionism is shown to be an intrinsically unstable position, in danger of collapsing into full-fledged 'credulism' of the kind historically associated with Thomas Reid.

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.

According to the "experimenter's regress", disputes about the validity of experimental results cannot be closed by objective facts because no conclusive criteria other than the outcome of the experiment itself exist for deciding whether the experimental apparatus was functioning properly or not. Given the frequent characterization of simulations as "computer experiments", one might worry that an analogous regress arises for computer simulations. The present paper analyzes the most likely scenarios where one might expect such a "simulationist's regress" to surface, and, in doing so, discusses analogies and disanalogies between simulation and experimentation. I conclude that, on a properly broadened understanding of robustness, the practice of simulating mathematical models can be seen to have sufficient internal structure to avoid any special susceptibility to regress-like situations.

The present paper focuses on a particular class of models intended to describe and explain the physical behaviour of systems that consist of a large number of interacting particles. Such many-body models are characterized by a specific Hamiltonian (energy operator) and are frequently employed in condensed matter physics in order to account for such phenomena as magnetism, superconductivity, and other phase transitions. Because of the dual role of many-body models as models of physical sys-tems (with specific physical phenomena as their explananda) as well as mathematical structures, they form an important sub-class of scientific models, from which one can expect to draw general conclusions about the function and functioning of models in science, as well as to gain specific insight into the challenge of modelling complex systems of correlated particles in condensed matter physics. In particular, it is argued that many-body models contribute novel elements to the process of inquiry and open up new avenues of cross-model confirmation and model-based understanding. In contradistinction to phenomenological models, which have received comparatively more philosophical attention, many-body models typically gain their strength not from ‘empirical fit’ per se, but from their being the result of a constructive application of mature formalisms, which frees them from the grip of both ‘fundamental theory’ and an overly narrow conception of ‘empirical success’.

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.

Synthetic biology presents a challenge to traditional accounts of biology: Whereas traditional biology emphasizes the evolvability, variability, and heterogeneity of living organisms, synthetic biology envisions a future of homogeneous, humanly engineered biological systems that may be combined in modular fashion. The present paper approaches this challenge from the perspective of the epistemology of technoscience. In particular, it is argued that synthetic-biological artifacts lend themselves to an analysis in terms of what has been called ‘thing knowledge’. As such, they should neither be regarded as the simple outcome of applying theoretical knowledge and engineering principles to specific technological problems, nor should they be treated as mere sources of new evidence in the general pursuit of scientific understanding. Instead, synthetic-biological artifacts should be viewed as partly autonomous research objects which, qua their material-biological constitution, embody knowledge about the natural world—knowledge that, in turn, can be accessed via continuous experimental interrogation.