Volume 27, Issue 3, September 2024, Page 280-297.

There are two distinct approaches to Bayesian modelling in cognitive science. Black-box approaches use Bayesian theory to model the relationship between the inputs and outputs of a cognitive system without reference to the mediating causal processes; while mechanistic approaches make claims about the neural mechanisms which generate the outputs from the inputs. This paper concerns the relationship between these two approaches. We argue that the dominant trend in the philosophical literature, which characterizes the relationship between black-box and (...) mechanistic approaches to Bayesian cognitive science in terms of the dichotomy between instrumentalism and realism, is misguided. We propose that the two distinctions are orthogonal: black-box and mechanistic approaches to Bayesian modelling can each be given either an instrumentalist or a realist interpretation. We argue that the current tendency to conflate black-box approaches with instrumentalism and mechanistic approaches with realism stems from unwarranted assumptions about the nature of scientific explanation, the ontological commitments of scientific theories, and the role of abstraction and idealization in scientific models. We challenge each of these assumptions to reframe the debates over Bayesian modelling in cognitive science. (shrink)

Given the fundamental role that concepts play in theories of cognition, philosophers and cognitive scientists have a common interest in concepts. Nonetheless, there is a great deal of controversy regarding what kinds of things concepts are, how they are structured, and how they are acquired. This chapter offers a detailed high-level overview and critical evaluation of the main theories of concepts and their motivations. Taking into account the various challenges that each theory faces, the chapter also presents a novel (...) approach to concepts that is organized around two ideas. The first is a pluralistic view of differing types of conceptual structure. The second is a model that treats concepts as atomic representations that are linked to various types of conceptual structures. (shrink)

Cognitive science has always included multiple methodologies and theoretical commitments. The philosophy of cognitive science should embrace, or at least acknowledge, this diversity. Bechtel’s (2009a) proposed philosophy of cognitive science, however, applies only to representationalist and mechanist cognitive science, ignoring the substantial minority of dynamically oriented cognitive scientists. As an example of nonrepresentational, dynamical cognitive science, we describe strong anticipation as a model for circadian systems (Stepp & Turvey, 2009). (...) We then propose a philosophy of science appropriate to nonrepresentational, dynamical cognitive science. (shrink)

Stanley and Williamson have defended the intellectualist thesis that knowing-how is a subspecies of knowing-that by appeal to the syntax and semantics of ascriptions of knowing-how. Critics have objected that this way of defending intellectualism places undue weight on linguistic considerations and fails to give sufficient attention to empirical considerations from the scientific study of the mind. In this paper, I examine and reject Stanley's recent attempt to answer the critics.

Within contemporary science, it is common practice to compare data points to the average, i.e., to the statistical mean. Because this practice is so familiar, it might at first appear not to be the sort of thing that requires explanation. But recent research in cognitive science and in the history of science gives us reason to adopt the opposite perspective. Cognitive science research on the ways people ordinarily make sense of the world suggests that, (...) instead of using a purely statistical notion of the average, people tend to use a value-laden notion of the normal. Similarly, historical research on the scientific practices used in other time periods indicates that, prior to the nineteenth century, scientists tended to make use of a notion of the normal that was overtly value-laden. These findings give us reason to rethink certain familiar facts about scientific practice. In particular, they suggest that the fact that scientists so often make use of the statistical average should be seen as a highly surprising fact, the sort of thing that calls out for explanation. (shrink)

This book demonstrates for the first time how the work of Ludwig Wittgenstein can transform 4E Cognitive Science. In particular, it shows how insights from Wittgenstein can empower those within 4E to reject the long held view that our minds must involve representations inside our heads. The book begins by showing how proponents of 4E are divided amongst themselves. Proponents of Extended Mind insist that internal representations are always needed to explain the human mind. However, proponents of Enacted (...) Mind reject this claim. Using insights from Ludwig Wittgenstein, the book introduces and defends a new theoretical framework called Structural Enacted or Extended Mins (STEEM). (shrink)

Philosophy of science is positioned to make distinctive contributions to cognitive science by providing perspective on its conceptual foundations and by advancing normative recommendations. The philosophy of science I embrace is naturalistic in that it is grounded in the study of actual science. Focusing on explanation, I describe the recent development of a mechanistic philosophy of science from which I draw three normative consequences for cognitive science. First, insofar as cognitive mechanisms (...) are information-processing mechanisms, cognitive science needs an account of how the representations invoked in cognitive mechanisms carry information about contents, and I suggest that control theory offers the needed perspective on the relation of representations to contents. Second, I argue that cognitive science requires, but is still in search of, a catalog of cognitive operations that researchers can draw upon in explaining cognitive mechanisms. Last, I provide a new perspective on the relation of cognitive science to brain sciences, one which embraces both reductive research on neural components that figure in cognitive mechanisms and a concern with recomposing higher-level mechanisms from their components and situating them in their environments. (shrink)

Thirty years after the publication of Marr's seminal book Vision the papers in this topic consider the contemporary status of his influential conception of three distinct levels of analysis for information-processing systems, and in particular the role of the algorithmic and representational level with its cognitive-level concepts. This level has been downplayed or eliminated both by reductionist neuroscience approaches from below that seek to account for behavior from the implementation level and by Bayesian approaches from above that seek to (...) account for behavior in purely computational-level terms. (shrink)

`Folk Psychology' - our everyday talk of beliefs, desires and mental events - has long been compared with the technical language of `Cognitive Science'. Does folk psychology provide a correct account of the mental causes of our behaviour, or must our everyday terms ultimately be replaced by a language developed from computational models and neurobiology? This broad-ranging book addresses these questions, which lie at the heart of psychology and philosophy. Providing a critical overview of the key literature in (...) the field, including the seminal work of Fodor and Churchland, the author explores the classic `Frame Problem' and assesses the future prospects of cognitive science. The scope of the frame problem, touching on connec. (shrink)

Cognitive Science, Literature, and the Arts is the first student-friendly introduction to the uses of cognitive science in the study of literature, written specifically for the non-scientist. Patrick Colm Hogan guides the reader through all of the major theories of cognitive science, focusing on those areas that are most important to fostering a new understanding of the production and reception of literature. This accessible volume provides a strong foundation of the basic principles of (...) class='Hi'>cognitive science, and allows us to begin to understand how the brain works and makes us feel as we read. (shrink)

The so-called ‘cognitive revolution’ (Gardner, 1985) in American psychology owed much to developments in adjacent disciplines, especially theoretical linguistics and computer science. Indeed, the cognitive revolution brought forth, not only a change in the conception of psychology, but also an inter-disciplinary approach to understanding the mind, involving philosophy, anthropology and neuroscience along with computer science, linguistics and psychology. Many commentators agree in dating the conception of this inter-disciplinary approach, cognitive science, to 11 September 1956, (...) the second day of a symposium on information theory held at MIT (Miller, 2003). Over the next twenty years or so, cognitive science developed an institutional presence through research centres, conferences, journals, and a substantial infusion of funds from the Alfred P. Sloan Foundation. (shrink)

This essay examines the relevance of dynamical ideas for cognitive science. On its own, the mere mathematical idea of a dynamical system is too weak to serve as a scientific theory of anything, and dynamical approaches within cognitive science are too rich and varied to be subsumed under a single “dynamical hypothesis.” Instead, after first attempting to dissect the different notions of “dynamics” and “cognition” at play, a more specific theoretical framework for cognitive science (...) broadly construed is sketched. This framework draws upon not only dynamical ideas, but also such contemporaneous perspectives as situatedness, embodiment, ecological psychology, enaction, neuroethology/neuroscience, artificial life, and biogenic approaches. The paper ends with some methodological suggestions for pursuing this theoretical framework. (shrink)

What role do linguistic cues on a surface and contextual level have in identifying the intention behind an utterance? Drawing on the wealth of studies and corpora from the computational task of dialog act classification, we studied this question from a cognitive science perspective. We first reviewed the role of linguistic cues in dialog act classification studies that evaluated model performance on three of the most commonly used English dialog act corpora. Findings show that frequency‐based, machine learning, and (...) deep learning methods all yield similar performance. Classification accuracies, moreover, generally do not explain which specific cues yield high performance. Using a cognitive science approach, in two analyses, we systematically investigated the role of cues in the surface structure of the utterance and cues of the surrounding context individually and combined. By comparing the explained variance, rather than the prediction accuracy of these cues in a logistic regression model, we found that (1) while surface and contextual linguistic cues can complement each other, surface linguistic cues form the backbone in human dialog act identification, (2) with word frequency statistics being particularly important for the dialog act, and (3) the similar trends across corpora, despite differences in the type of dialog, corpus setup, and dialog act tagset. The importance of surface linguistic cues in dialog act classification sheds light on how both computers and humans take advantage of these cues in speech act recognition. (shrink)

The rise of cognitive neuroscience is the most important scientific and intellectual development of the last thirty years. Findings pour forth, and major initiatives for brain research continue. The social sciences have responded to this development slowly--for good reasons. The implications of particular controversial findings, such as the discovery of mirror neurons, have been ambiguous, controversial within neuroscience itself, and difficult to integrate with conventional social science. Yet many of these findings, such as those of experimental neuro-economics, pose (...) very direct challenges to standard social science. At the same time, however, the known facts of social science, for example about linguistic and moral diversity, pose a significant challenge to standard neuroscience approaches, which tend to focus on "universal" aspects of human and animal cognition. A serious encounter between cognitive neuroscience and social science is likely to be challenging, and transformative, for both parties. Although a literature has developed on proposals to integrate neuroscience and social science, these proposals go in divergent directions. None of them has a developed conception of social life. This book surveys these issues, introduces the basic alternative conceptions both of the mental world and the social world, and show how, with sufficient modification, they can be fit together in plausible ways. The book is not a "new theory " of anything, but rather an exploration of the critical issues that relate to the social aspects of cognition which expands the topic from the social neuroscience of immediate interpersonal interaction to the whole range of places where social variation interacts with the cognitive. The focus is on the conceptual problems produced by any attempt to take these issues seriously, and also on the new resources and considerations relevant to doing so. But it is also on the need for a revision of social theoretical concepts in order to utilize these resources. The book points to some conclusions, especially about how the process of what was known as socialization needs to be understood in cognitive science friendly terms. But there is no attempt to resolve the underlying issues within cognitive science, which will doubtless persist. (shrink)

In recent decades, a new scientific approach to understand, explain, and predict many features of religion has emerged. The cognitive science of religion has amassed research on the forces that shape the tendency for humans to be religious and on what forms belief takes. It suggests that religion, like language or music, naturally emerges in humans with tractable similarities. This new approach has profound implications for how we understand religion, including why it appears so easily, and why people (...) are willing to fight-and die for it. Yet it is not without its critics, and some fear that scholars are explaining the ineffable mystery of religion away, or by showing that religion is natural proves or disproves the existence of God. An Introduction to the Cognitive Science of Religion offers students and general readers an accessible introduction to the approach, providing an overview of key findings and the debates that shape it. The volume includes a glossary of key terms, and each chapter includes suggestions for further thought and further reading as well as chapter summaries highlighting key points. This book is an indispensable resource for introductory courses on religion and a much-needed option for advanced courses. (shrink)

Contemporary literature in cognitive science and the philosophy of mind points to the locus of significant unresolved theoretical and methodological issues in political theory and political science, and particularly to the persistently anomalous status of mental concepts. The manner in which political and social theorists have accessed and deployed this literature, however, has been highly selective and conceptually problematical. The purpose has often been to justify prior agendas, and issues relating to how brain processes are involved in (...) an explanation of political phenomena have not been satisfactorily confronted. Cognitive science is itself a highly contested field with indigenous theoretical difficulties, and it is necessary to sort out and analyze the salient positions in this conversation and to begin, at least tentatively, to assess critically its implications for both social theory and empirical research and to suggest a direction for further investigation. (shrink)

Changes in the aims and methods of the philosophy of mind have occurred in recent decades. In particular, computer simulations have emerged as a means of constructing empirically and conceptually defensible theories of mind. This article explores pedagogical innovations that may be necessitated by these changes. One question raised is whether hands‐on teaching of simulation methods should be a standard part of philosophy of mind courses. These courses, because of an increasing empirical orientation, are becoming more interdisciplinary, and certain consequences (...) of this development are elaborated here. (shrink)

There is a growing chorus of voices in the scientific community calling for greater openness in the sharing of raw data that lead to a publication. In this commentary, we discuss the merits of sharing, common concerns that are raised, and practical issues that arise in developing a sharing policy. We suggest that the cognitive science community discuss the topic and establish a data-sharing policy.