Very plausibly, nothing can be a genuine computing system unless it meets an input-sensitivity requirement. Otherwise all sorts of objects, such as rocks or pails of water, can count as performing computations, even such as might suffice for mentality—thus threatening computationalism about the mind with panpsychism. Maudlin in J Philos 86:407–432, ( 1989 ) and Bishop ( 2002a , b ) have argued, however, that such a requirement creates difficulties for computationalism about conscious experience, putting it in conflict with the (...) very intuitive thesis that conscious experience supervenes on physical activity. Klein in Synthese 165:141–153, ( 2008 ) proposes a way for computationalists about experience to avoid panpsychism while still respecting the supervenience of experience on activity. I argue that his attempt to save computational theories of experience from Maudlin’s and Bishop’s critique fails. (shrink)

The paper is a commentary on the target article by Christine A. Skarda & Walter J. Freeman, “How brains make chaos in order to make sense of the world”, in the same issue of the journal, pp.161–195. -/- I confine my comments largely to some philosophical claims that Skarda & Freeman make and to the relationship of their model to connectionism. Some of the comments hinge on what symbols are and how they might sit in neural systems.

Recent research in computational neuroscience has demonstrated that we now possess the ability to simulate neural systems in significant detail and on a large scale. Simulations on the scale of a human brain have recently been reported. The ability to simulate entire brains (or significant portions thereof) would be a revolutionary scientific advance, with substantial benefits for brain science. However, the prospect of whole-brain simulation comes with a set of new and unique ethical questions. In the present paper, we briefly (...) outline certain of those problems and emphasize the need to begin considering the ethical aspects of computational neuroscience. (shrink)

The rapid development of natural language processing in the last three decades has drastically changed the way professional translators do their work. Nowadays most of them use computer-assisted translation or translation memory tools whose evolution has been overshadowed by the much more sensational development of machine translation systems, with which TM tools are sometimes confused. These two language technologies now interact in mutually enhancing ways, and their increasing role in human translation has become a subject of behavioral studies. Philosophers and (...) linguists, however, have been slow in coming to grips with these important developments. The present paper seeks to fill in this lacuna. I focus on the semantic aspects of the highly distributed human–computer interaction in the CAT process which presents an interesting case of an extended cognitive system involving a human translator, a TM tool, an MT engine, and sometimes other human translators or editors. Considered as a whole, such a system is engaged in representing the linguistic meaning of the source document in the target language. But the roles played by its various components, natural as well as artificial, are far from trivial, and the division of linguistic labor between them throws new light on the familiar notions that were initially inspired by rather different phenomena in the philosophy of language, mind, and cognitive science. (shrink)

There is a deluge of AI-assisted decision-making systems, where our data serve as proxy to our actions, suggested by AI. The closer we investigate our data (raw input, or their learned representations, or the suggested actions), we begin to discover “bugs”. Outside of their test, controlled environments, AI systems may encounter situations investigated primarily by those in other disciplines, but experts in those fields are typically excluded from the design process and are only invited to attest to the ethical features (...) of the resulting system or to comment on demonstrations of intelligence and aspects of craftmanship after the fact. This communicative impasse must be overcome. Our idea is that philosophical and engineering considerations interact and can be fruitfully combined in the AI design process from the very beginning. We embody this idea in the role of a philosopher engineer. We discuss the role of philosopher engineers in the three main design stages of an AI system: deployment management (what is the system’s intended use, in what environment?); objective setting (what should the system be trained to do, and how?); and training (what model should be used, and why?). We then exemplify the need for philosopher engineers with an illustrative example, investigating how the future decisions of an AI-based hiring system can be fairer than those contained in the biased input data on which it is trained; and we briefly sketch the kind of interdisciplinary education that we envision will help to bring about better AI. (shrink)

Empirical research on human–robot interaction has demonstrated how humans tend to react to social robots with empathic responses and moral behavior. How should we ethically evaluate such responses to robots? Are people wrong to treat non-sentient artefacts as moral patients since this rests on anthropomorphism and ‘over-identification’ —or correct since spontaneous moral intuition and behavior toward nonhumans is indicative for moral patienthood, such that social robots become our ‘Others’?. In this research paper, I weave extant HRI studies that demonstrate empathic (...) responses toward robots with the recent debate on moral status for robots, on which the ethical evaluation of moral behavior toward them is dependent. Patienthood for robots has standardly been thought to obtain on some intrinsic ground, such as being sentient, conscious, or having interest. But since these attempts neglect moral experience and are curbed by epistemic difficulties, I take inspiration from Coeckelbergh and Gunkel’s ‘relational approach’ to explore an alternative way of accounting for robot patienthood based on extrinsic premises. Based on the ethics of Danish theologian K. E. Løgstrup I argue that empathic responses can be interpreted as sovereign expressions of life and that these expressions benefit human subjects—even if they emerge from social interaction afforded by robots we have anthropomorphized. I ultimately develop an argument in defense of treating robots as moral patients. (shrink)

Some may find an oxymoron in my title. But, my use of “instrumental” is to focus attention on the real instruments of science-pumps, dynamos and cyclotrons-and not the view that scientific theories are best understood as instruments. In what follows I characterize and argue for a kind of realism strongly wedded to what we do with scientific instruments, and divorced from what our theories may say about the entities manipulated by these instruments. My discussion owes much to Ian Hacking’s “Experimental (...) Argument for Realism” (Hacking 1983, ch. 16).The following fantasy might help give some idea of the view I am interested in. Suppose that the diskettes, which many people use in conjunction with a small computer, do not store information magnetically; in fact they store it “radioactively,” exactly how, is not relevant. IBM decided that many people in their target personal computer market would be put off by “nuclear diskettes.”. (shrink)

Some strange cases have gripped philosophers of mind. They have been deployed against materialism about human persons, functionalism about mentality, the possibility of artificial intelligence, and more. In this paper, I cry “foul”. It’s not hard to think that there’s something wrong with the cases. But what? My proposal: their proponents ignore questions about composition. And ignoring composition is a mistake. Indeed, materialists about human persons, functionalists about mentality, and believers in the possibility of artificial intelligence can plausibly deploy moderate (...) theories of composition in defense of their views. And as it turns out, these strange cases are an interesting source of evidence for moderate theories of composition. (shrink)

The representational nature of human cognition and thought in general has been a source of controversies. This is particularly so in the context of studies of unconscious cognition, in which representations tend to be ontologically and structurally segregated with regard to their conscious status. However, it appears evolutionarily and developmentally unwarranted to posit such segregations, as,otherwise, artifact structures and ontologies must be concocted to explain them from the viewpoint of the human cognitive architecture. Here, from a by-and-large Classical cognitivist viewpoint, (...) I show why this segregation is wrong, and elaborate on the need to postulate an ontological and structural continuity between unconscious and conscious representations. Specifically, I hypothesize that this continuity is to be found in the symbolic-based interplay between the syntax and the semantics of thought, and I propose a model of human information processing characterized by the integration of syntactic and semantic representations. (shrink)

Can autonomous systems replace humans in the performance of their activities? How does the answer to this question inform the design of autonomous systems? The study of technical systems and their features should be preceded by the study of the activities in which they play roles. Each activity can be described by its overall goals, governing norms and the intermediate steps which are taken to achieve the goals and to follow the norms. This paper uses the activity realist approach to (...) conceptualize autonomous systems in the context of human activities. By doing so, it first argues for epistemic and logical conditions that illustrate the limitations of autonomous systems in tasks which they can and cannot perform, and then, it discusses the ramifications of the limitations of system autonomy on the design of autonomous systems. (shrink)

The main purpose of this dissertation is to examine critically and discuss the role of imagination in science and religion, with particular emphasis on its possible epistemic, creative, and meaning-making functions. In order to answer my research questions, I apply theories and concepts from contemporary philosophy of mind on scientific and religious practices. This framework allows me to explore the mental state of imagination, not as an isolated phenomenon but, rather, as one of many mental states that co-exist and interplay (...) in our cogntive architecture. Based on the philosophical discourse of philosophy of mind, four types of imagination are indentified and conceptualized: sensory, propositional, experiential, and creative imagination. These categories are then employed on five phenomena that can be found in scientific and religious environments: metaphors, models, thought experiments, aspect perception, and - in the religious case - rituals. In relation to the concept of religious "seeing" I consider how imaginings may influence visionary experiences and visualization, and compare these phenomena with cases of scientific visualization and eureka experiences. In regard to scientific and religious models, a distinction is made between, on the one hand, two notions of truth and, on the other hand, truth-independent meaning-making. In light of these categories, I differentiate between, and critically discuss, the use of imagination in doxastic, non-doxastic and fictionalist accounts. In light of this investigation, I formulate and defend the position of interactivism, which acknowledges a constant interplay between different attitudes and mental states. In my examination of rituals and scientific and religious thought experiments, special attention is given to the mental capacity to recreate the experiences that are entailed in an imagined scenario. At the end of the investigation, I consider the possible impact that my study might have on how we view science and religion as well as the dialogue bewteen these two fields. (shrink)

Two critical questions spun the web of the Turing test debate. First, can an appropriately programmed machine pass the Turing test? Second, is passing the test by such a machine, ipso facto, considered proof that it is intelligent and hence “minded”? While the first question is technological, the second is purely philosophical. Focusing on the second question, this article interrogates the implication of John Searle’s Chinese room denial of machine intelligence. The thrust of Searle’s argument is that a machine lacks (...) intentionality, so it can only simulate intelligence, not duplicate it. In his thinking, whatever a machine inputs to generate an intelligent output has no bearing on humanlike intelligence. Incidentally, Searle did not classify such a machine’s output as simulated and non-intelligent, nor did he explain how this output is actualised with mere simulation. The connection between “unintelligent machine’s input” and “intelligent machine’s output” is at this point shrouded in mystery. Consequently, the more Searle attempts a denial of machine intelligence in the Chinese room, the more he mystifies it. Using the method of critical analysis, this article advances three fundamental arguments to prove a machines’ obscurity in the Chinese room thought experiment. On the ground of Searle’s conviction, the first argument queries the absurdity in bypassing intentionality to produce intelligence; the second points out the obfuscation in generating intelligence with mere computation, and the third draws attention to the dilemma of classifying a machine’s output either as real-life intelligent behaviour or simulated intelligent behaviour. (shrink)

This article argues that existing approaches to programming ethical AI fail to resolve a serious moral-semantic trilemma, generating interpretations of ethical requirements that are either too semantically strict, too semantically flexible, or overly unpredictable. This paper then illustrates the trilemma utilizing a recently proposed ‘general ethical dilemma analyzer,’ GenEth. Finally, it uses empirical evidence to argue that human beings resolve the semantic trilemma using general cognitive and motivational processes involving ‘mental time-travel,’ whereby we simulate different possible pasts and futures. I (...) demonstrate how mental time-travel psychology leads us to resolve the semantic trilemma through a six-step process of interpersonal negotiation and renegotiation, and then conclude by showing how comparative advantages in processing power would plausibly cause AI to use similar processes to solve the semantic trilemma more reliably than we do, leading AI to make better moral-semantic choices than humans do by our very own lights. (shrink)

This article argues that if panpsychism is true, then there are grounds for thinking that digitally-based artificial intelligence may be incapable of having coherent macrophenomenal conscious experiences. Section 1 briefly surveys research indicating that neural function and phenomenal consciousness may be both analog in nature. We show that physical and phenomenal magnitudes—such as rates of neural firing and the phenomenally experienced loudness of sounds—appear to covary monotonically with the physical stimuli they represent, forming the basis for an analog relationship between (...) the three. Section 2 then argues that if this is true and micropsychism—the panpsychist view that phenomenal consciousness or its precursors exist at a microphysical level of reality—is also true, then human brains must somehow manipulate fundamental microphysical-phenomenal magnitudes in an analog manner that renders them phenomenally coherent at a macro level. However, Sect. 3 argues that because digital computation abstracts away from microphysical-phenomenal magnitudes—representing cognitive functions non-monotonically in terms of digits—digital computation may be inherently incapable of realizing coherent macroconscious experience. Thus, if panpsychism is true, digital AI may be incapable of achieving phenomenal coherence. Finally, Sect. 4 briefly examines our argument’s implications for Tononi’s Integrated Information Theory theory of consciousness, which we contend may need to be supplanted by a theory of macroconsciousness as analog microphysical-phenomenal information integration. (shrink)

Logical theories for representing knowledge are often plagued by the so-called Logical Omniscience Problem. The problem stems from the clash between the desire to model rational agents, which should be capable of simple logical inferences, and the fact that any logical inference, however complex, almost inevitably consists of inference steps that are simple enough. This contradiction points to the fruitlessness of trying to solve the Logical Omniscience Problem qualitatively if the rationality of agents is to be maintained. We provide a (...) quantitative solution to the problem compatible with the two important facets of the reasoning agent: rationality and resource boundedness. More precisely, we provide a test for the logical omniscience problem in a given formal theory of knowledge. The quantitative measures we use are inspired by the complexity theory. We illustrate our framework with a number of examples ranging from the traditional implicit representation of knowledge in modal logic to the language of justification logic, which is capable of spelling out the internal inference process. We use these examples to divide representations of knowledge into logically omniscient and not logically omniscient, thus trying to determine how much information about the reasoning process needs to be present in a theory to avoid logical omniscience. (shrink)

The idea of the present Issue originated in a workshop held at the University of Urbino, Italy, in June 2014, and subsequently developed into an independent editorial project by including contributions that were not initially presented at the workshop. The eight essays that follow authored by young and emerging philosophers as well as fully accomplished ones—touch upon various aspects of the most recent debate surrounding TEs, closely engaging with many influential proposals that have been put forward over the last few (...) years. They can be organised around three main areas of concern. The first group deals with general issues raised by the use of TEs, such as the possibility of drawing a principled distinction between scientific and philosophical TEs (Marco Buzzoni), the role played by intuitions within philosophical TEs (Julia Langkau), and the different ways in which the intended conclusion of a TE can be resisted (Roy Sorensen). The second group focuses on the logical form of philosophical TEs (Sören Häggqvist; Daniele Sgaravatti), and on the kind of access to modal knowledge they are standardly taken to provide (Vittorio Morato). The third and last group explores the virtues and limits of TEs used in two specific philosophical areas, namely the philosophy of science (Margherita Benzi), and the philosophy of mind (Elizabeth Schier). (shrink)

In the past few years, the subject of AI rights—the thesis that AIs, robots, and other artefacts (hereafter, simply ‘AIs’) ought to be included in the sphere of moral concern—has started to receive serious attention from scholars. In this paper, I argue that the AI rights research program is beset by an epistemic problem that threatens to impede its progress—namely, a lack of a solution to the ‘Hard Problem’ of consciousness: the problem of explaining why certain brain states give rise (...) to experience. To motivate this claim, I consider three ways in which to ground AI rights—namely: superintelligence, empathy, and a capacity for consciousness. I argue that appeals to superintelligence and empathy are problematic, and that consciousness should be our central focus, as in the case of animal rights. However, I also argue that AI rights is disanalogous from animal rights in an important respect: animal rights can proceed without a solution to the ‘Hard Problem’ of consciousness. Not so with AI rights, I argue. There we cannot make the same kinds of assumptions that we do about animal consciousness, since we still do not understand why brain states give rise to conscious mental states in humans. (shrink)

Over the past 15 years, there have been two increasingly popular approaches to the study of meaning in cognitive science. One, based on theories of embodied cognition, treats meaning as a simulation of perceptual and motor states. An alternative approach treats meaning as a consequence of the statistical distribution of words across spoken and written language. On the surface, these appear to be opposing scientific paradigms. In this review, we aim to show how recent cross-disciplinary developments have done much to (...) reconcile these two approaches. The foundation to these developments has been the recognition that intralinguistic distributional and sensory-motor data are interdependent. We describe recent work in philosophy, psychology, cognitive neuroscience, and computational modeling that are all based on or consistent with this conclusion. We conclude by considering some possible directions for future research that arise as a consequence of these developments. (shrink)

Machine learning, and more broadly artificial intelligence (AI), is a fascinating technology and can be considered as the closest approximation to the Cartesian “thinking thing” that humans have ever created. Just as the industrial revolution required a new ethos, the age of intelligent machines will create its own, challenging the established moral, economic, and political presuppositions. This paper discusses the relationship between AI and society; it presents several thought experiments to explore the complexity of the relationship and highlights the insufficiency (...) of the current normative paradigm in addressing technological expansion. I argue that many of the externalities, such as security risks, loss of privacy, and economic instability will result from trying to fit the emerging technologies into the existing frame of efficiency and utility, by redefining the notions of human value, identity, autonomy, purity, and truth, among others. The age of the intelligent machine is elevating alienation to new levels, treating the individual as mere patterns in data—its primary commodity. I further argue that while the possibility of unintended consequences, due to the potential misuse of AI is ever present, the intelligent machine per se is unlikely to engage in a zero-sum game for power on its own initiative. I question whether singularity is at all attainable and argue that technology will forever remain a proxy for human interests. I conclude by posing questions for charting the path forward. Through this analysis, I aim to provide a more nuanced understanding of the complex relationship between the AI and humans. (shrink)

In this paper, I will propose a classification of analogies based on their internal structure. Selecting the criteria used in that classification first requires discussing the minimal constitutive parts of any analogy. Accordingly, I will discuss the differences between analogy and similarity and between analogy and “synalogy,” and I will stress the importance of the analogy of operations and procedures. Finally, I will set forth a classification of the different types of analogies, which lends itself to a further understanding of (...) the differences between certain modulations of the general idea of analogy, such as archetypes, prototypes, models, simulations, parables, paradigms, canons, maps, thought experiments, myths, utopias, dystopias and fables. (shrink)

Philosophy and science have always striven to make sense of the world, continuously influencing each other in the process. Their interplay paved the way for neurophilosophy, which harnesses neuroscientific insights to address traditionally philosophical questions. Given the rapid neuroscientific and technological advances in recent years, this paper argues that philosophers who wish to tackle intractable philosophical problems and influence public discourse and policies should engage in neuro-techno-philosophy. This novel type of inquiry describes the transdisciplinary endeavor of philosophers, (neuro)scientists, and others (...) to anticipate the societal implications of the impending transformations of subjects and theorizers. While human enhancement is likely to irreversibly change what it means to be human, disruptive technologies might lead to the emergence of artificial intelligent agents and human-machine hybrids. The paper predicts that neuro-techno-philosophy will be indispensable to understanding and engaging with these game-changing innovations and thus play a pivotal role in the future of philosophy. (shrink)

Extended Cognition (EC) hypothesizes that there are parts of the world outside the head serving as cognitive vehicles. One criticism of this controversial view is the problem of “cognitive bloat” which says that EC is too permissive and fails to provide an adequate necessary criterion for cognition. It cannot, for instance, distinguish genuine cognitive vehicles from mere supports (e.g. the Yellow Pages). In response, Andy Clark and Mark Rowlands have independently suggested that genuine cognitive vehicles are distinguished from supports in (...) that the former have been “recruited,” i.e. they are either artifacts, or, products of evolution. I argue against this proposal. There are counter examples to the claim that “Teleological” EC is either necessary or sufficient for cognition. Teleological EC conflates different types of scientific projects, and inherits content externalism’s alienation from historically impartial cognitive science. (shrink)

Cognitive ethologists are in need of a good theoretical framework for attributing intentional states. Heyes and Dickinson (1990) present criteria that they claim are necessary for an intentional explanation of behavior to be justified. They suggest that questions of intentionality can only be investigated under controlled laboratory conditions and they apply their criteria to laboratory experiments to argue that the common behavior of approaching food is not intentional in most animals. We dispute the details of their argument and interpretation of (...) the laboratory experiments. While criteria such as those suggested have a role to play in comparative studies of cognition, both laboratory and field studies are important for assessing the applicability of intentional explanations across different taxa. (shrink)

In the period between Turing’s 1950 “Computing Machinery and Intelligence” and the current considerable public exposure to the term “artificial intelligence ”, Turing’s question “Can a machine think?” has become a topic of daily debate in the media, the home, and, indeed, the pub. However, “Can a machine think?” is sliding towards a more controversial issue: “Can a machine be conscious?” Of course, the two issues are linked. It is held here that consciousness is a pre-requisite to thought. In Turing’s (...) imitation game, a conscious human player is replaced by a machine, which, in the first place, is assumed not to be conscious, and which may fool an interlocutor, as consciousness cannot be perceived from an individual’s speech or action. Here, the developing paradigm of machine consciousness is examined and combined with an extant analysis of living consciousness to argue that a conscious machine is feasible, and capable of thinking. The route to this utilizes learning in a “neural state machine”, which brings into play Turing’s view of neural “unorganized” machines. The conclusion is that a machine of the “unorganized” kind could have an artificial form of consciousness that resembles the natural form and that throws some light on its nature. (shrink)

Epistemologists have debated at length whether scientific discovery is a rational and logical process. If it is, according to the Artificial Intelligence hypothesis, it should be possible to write computer programs able to discover laws or theories; and if such programs were written, this would definitely prove the existence of a logic of discovery. Attempts in this direction, however, have been unsuccessful: the programs written by Simon's group, indeed, infer famous laws of physics and chemistry; but having found no new (...) law, they cannot properly be considered discovery machines. The programs written in the Turing tradition, instead, produced new and useful empirical generalization, but no theoretical discovery, thus failing to prove the logical character of the most significant kind of discoveries. A new cognitivist and connectionist approach by Holland, Holyoak, Nisbett and Thagard, looks more promising. Reflection on their proposals helps to understand the complex character of discovery processes, the abandonment of belief in the logic of discovery by logical positivists, and the necessity of a realist interpretation of scientific research. (shrink)

Cognitive science is unusual in that cognitive scientists have dramatic disagreements about the extension of their object of study, cognition. This paper defends a novel analysis of the scientific concept of cognition: that cognition is the sensitive management of an agent’s behavior. This analysis is “modular,” so that its extension varies depending on how one interprets certain of its constituent terms. I argue that these variations correspond to extant disagreements between cognitive scientists. This correspondence is evidence that the proposed analysis (...) models the contemporary understanding of cognition among scientists, without artificially resolving questions that are currently considered open. (shrink)

In ‘‘The Myth of Original Intentionality,’’ Daniel Dennett appears to want to argue for four claims involving the familiar distinction between original (or underived) and derived intentionality.

In ‘‘The Myth of Original Intentionality,’’ Daniel Dennett appears to want to argue for four claims involving the familiar distinction between original (or underived) and derived intentionality. 1. Humans lack original intentionality. 2. Humans have derived intentionality only. 3. There is no distinction between original and derived intentionality. 4. There is no such thing as original intentionality. We argue that Dennett’s discussion fails to secure any of these conclusions for the contents of thoughts.

In a paper in this journal, Neil Levy challenges Nicholas Agar’s argument for the irrationality of mind-uploading. Mind-uploading is a futuristic process that involves scanning brains and recording relevant information which is then transferred into a computer. Its advocates suppose that mind-uploading transfers both human minds and identities from biological brains into computers. According to Agar’s original argument, mind-uploading is prudentially irrational. Success relies on the soundness of the program of Strong AI—the view that it may someday be possible to (...) build a computer that is capable of thought. Strong AI may in fact be false, an eventuality with dire consequences for mind-uploading. Levy argues that Agar’s argument relies on mistakes about the probability of failed mind-uploading and underestimates what is to be gained from successfully mind-uploading. This paper clarifies Agar’s original claims about the likelihood of mind-uploading failure and offers further defense of a pessimistic evaluation of success. (shrink)

This paper offers practical advice about how to interact with machines that we have reason to believe could have minds. I argue that we should approach these interactions by assigning credences to judgements about whether the machines in question can think. We should treat the premises of philosophical arguments about whether these machines can think as offering evidence that may increase or reduce these credences. I describe two cases in which you should refrain from doing as your favored philosophical view (...) about thinking machines suggests. Even if you believe that machines are mindless, you should acknowledge that treating them as if they are mindless risks wronging them. Suppose your considered philosophical view that a machine has a mind leads you to consider dating it. You may have reason to regret that decision should these dates lead on to a life-long relationship with a mindless machine. In the paper’s final section, I suggest that building a machine that is capable of performing all intelligent human behavior should produce a general increase in confidence that machines can think. Any reasonable judge should count this feat as evidence in favor of machines having minds. This rational nudge could lead to broad acceptance of the idea that machines can think. (shrink)

I argue that the Oxford school Everett interpretation is internally incoherent, because we cannot claim that in an Everettian universe the kinds of reasoning we have used to arrive at our beliefs about quantum mechanics would lead us to form true beliefs. I show that in an Everettian context, the experimental evidence that we have available could not provide empirical confirmation for quantum mechanics, and moreover that we would not even be able to establish reference to the theoretical entities of (...) quantum mechanics. I then consider a range of existing Everettian approaches to the probability problem and show that they do not succeed in overcoming this incoherence. (shrink)

Questions about the relationship between linguistic competence and expertise will be examined in the paper. Harry Collins and others distinguish between ubiquitous and esoteric expertise. Collins places considerable weight on the argument that ordinary linguistic competence and related phenomena exhibit a high degree of expertise. His position and ones which share close affinities are methodologically problematic. These difficulties matter because there is continued and systematic disagreement over appropriate methodologies for the empirical study of expertise. Against Collins, it will be argued (...) that the term ‘expertise’ should be reserved for expertise (esoteric experts) and exclude everyday performance (ubiquitous experts). Wittgensteinian ideas will be employed to maintain that it is mistaken and misleading to derive substantive conclusions about the epistemology of expertise from ordinary linguistic competence and vice versa. Significant attention will be devoted to the notion of following a rule with particular reference to the intelligibility of tacit rule following. A satisfactory theoretical approach to expertise should not involve making important claims about ordinary linguistic competence. (shrink)