There is a general conception of levels in philosophy which says that the world is arrayed into a hierarchy of levels and that there are different modes of analysis that correspond to each level of this hierarchy, what can be labelled the ‘Hierarchical Correspondence View of Levels” (or HCL). The trouble is that despite its considerable lineage and general status in philosophy of science and metaphysics the HCL has largely escaped analysis in specific domains of inquiry. The goal of this (...) paper is to take up a recent call to domain-specificity by examining the role of the HCL in cognitive science. I argue that the HCL is, in fact, a conception of levels that has been employed in cognitive science and that cognitive scientists should avoid its use where possible. The argument is that the HCL is problematic when applied to cognitive science specifically because it fails to distinguish two important kinds of shifts used when analysing information processing systems: shifts in grain and shifts in analysis. I conclude by proposing a revised version of the HCL which accommodates the distinction. (shrink)

There are different ways to present a Presidential Address to the APA; the one I have chosen is simply to report on work that I am doing right now, on work in progress. I am going to present some of my further explorations into the computational model of the mind.\**.

The central mission of cognitive science is to reveal the real nature of the mind, however familiar or foreign that nature may be to naive preconceptions. The existence of naive conceptions is also important, however. Prescientific thought and language contain concepts of the mental, and these concepts deserve attention from cognitive science. Just as scientific psychology studies folk physics (McCloskey 1983, Hayes 1985), viz., the common understanding (or misunderstanding) of physical phenomena, so it must study folk psychology, the common understanding (...) of mental states. This subfield of scientific psychology is what I mean by the phrase 'the psychology of folk psychology'. (shrink)

"Rationality: Contexts and Constraints" is an interdisciplinary reappraisal of the nature of rationality. In method, it is pluralistic, drawing upon the analytic approaches of philosophy, linguistics, neuroscience, and more. These methods guide exploration of the intersection between traditional scholarship and cutting-edge philosophical or scientific research. In this way, the book contributes to development of a suitably revised, comprehensive understanding of rationality, one that befits the 21st century, one that is adequately informed by recent investigations of science, pathology, non-human thought, emotion, (...) and even enigmatic Chinese texts that might previously have seemed to be expressions of irrationalism. Addresses recent challenges and Identifies a direction for future research on rationalityInvestigates the relationship between rationality and mental disorders, such as delusion and depressionAssesses reasoning in artificial intelligence and nonhuman animalsReflects on ancient Chinese Philosophy and possible cultural differences in human psychology Employs philosophical reflection, along with linguistic, probabilistic, and logical techniques. (shrink)

Cognitive modules are internal mental structures. Some theorists and empirical researchers hypothesize that the human mind is either partially or massively comprised of structures that are modular in nature. Modules are also invoked to explain cognitive capacities associated with the performance of specific functional tasks. Jerry Fodor (1983) considered that modules are useful only for explaining relatively low-level systems (input systems). These are the systems involved in capacities like perception and language. For Fodor, the central (high-level) systems of mind — (...) those involved in capacities like judgment (the “fixation of belief” in Fodor’s jargon), planning (practical reasoning), decision-making, and so forth — are not explainable in terms of modular mechanisms. However, some other philosophers as well as proponents and practitioners of evolutionary psychology consider that it is sensible — and even necessary — to invoke modules for explaining these systems, too. Indeed, the debate over modularity is mainly a debate over the modularity of central systems (high-level cognitive capacities). Admittedly, it is also possible to raise doubts about the modularity of peripheral systems (Prinz, 2006), but this kind of skepticism is not widespread in the literature. In contrast, both the empirical and the theoretical (a priori) cases in favor of central modularity are usually contested on multiple fronts and in tough terms. The case for the modularity of central systems is the core of the case for the massive modularity of mind hypothesis (viz. the hypothesis that consists in asserting that both the peripheral and the central systems of human mind are largely composed of modules). Granted, the massive modularity of mind hypothesis is an empirical statement and, as such, its truth should be ultimately decided in an empirical way, not a priori (Sperber, 1994, 2001). Nonetheless, much of the debate over massive modularity has taken place on theoretical grounds. This is due to an alleged underdetermination of the hypotheses regarding the modularity of central systems by data. In such conditions, the remaining open option has been to advance theoretical considerations in favor of the plausibility — and not directly in favor of the empirical truth or truthlikeness — of the massive modularity of mind generally, and of the modularity of some central systems in particular. These theoretical considerations are mostly based on an adaptationist view of evolution cum a classical computationalist approach to mind. They include arguments about the nature and evolution of hierarchically ordered complex systems (the evolvability of complexity argument), a presumption of optimality expressed in the apparent design of phenotypic traits shaped by natural selection (the task-specificity argument) and dismissing nonmodular mental architectures as computationally intractable (the tractability argument). Is the massive modularity of mind hypothesis a cogent view about the ontological nature of human mind or is it, rather, an effective/ineffective adaptationist discovery heuristic for generating predictively successful hypothesis about both heretofore unknown psychological traits and unknown properties of already identified psychological traits? Considering the inadequacies of the case in favor of massive modularity as an ontological hypothesis, I suggest approaching and valuing massive modularity as an adaptationist discovery heuristic. (shrink)

Philosophical Issues, Volume 30, Issue 1, Page 273-292, October 2020.

This paper aims to offer a new view of the role of connectionist models in the study of human cognition through the conceptualization of the history of connectionism – from the simplest perceptrons to convolutional neural nets based on deep learning techniques, as well as through the interpretation of criticism coming from symbolic cognitive science. Namely, the connectionist approach in cognitive science was the target of sharp criticism from the symbolists, which on several occasions caused its marginalization and almost complete (...) abandonment of its assumptions in the study of cognition. Criticisms have mostly pointed to its explanatory inadequacy as a theory of cognition or to its biological implausibility as a theory of implementation, and critics often focused on specific shortcomings of some connectionist models and argued that they apply to connectionism in general. In this paper, we want to show that both types of critique are based on the assumption that the only valid explanations in cognitive science are instances of homuncular functionalism and that by removing this assumption and by adopting an alternative methodology – exploratory mechanistic strategy, we can reject most objections to connectionism as irrelevant, explain the progress of connectionist models despite their shortcomings and sketch the trajectory of their future development. By adopting mechanistic explanations and by criticizing functionalism, we will reject the objections of explanatory inadequacy, by characterizing connectionist models as generic rather than concrete mechanisms, we will reject the objections of biological implausibility, and by attributing the exploratory character to connectionist models we will show that practice of generalizing current to general failures of connectionism is unjustified. (shrink)

Linguistic representations are taken by some to be representations of something, specifically of Standard Linguistic Entities, such as phonemes, clauses, noun phrases etc. This perspective takes them to be intentional. Rey (2021) further argues that the SLEs themselves are inexistent. Here I argue that linguistic representations are simply structures, abstractions of brain states, and hence not intentional, and show how they nevertheless connect to the systems that use them.

The central aim of this paper is to shed light on the nature of explanation in computational neuroscience. I argue that computational models in this domain possess explanatory force to the extent that they describe the mechanisms responsible for producing a given phenomenon—paralleling how other mechanistic models explain. Conceiving computational explanation as a species of mechanistic explanation affords an important distinction between computational models that play genuine explanatory roles and those that merely provide accurate descriptions or predictions of phenomena. It (...) also serves to clarify the pattern of model refinement and elaboration undertaken by computational neuroscientists. (shrink)

Eliminativism is a position most readily associated with the eliminative materialism of the Churchlands, denying that there are such things as propositional states. This position has created much controversy, despite the fact that intentionality has long been seen as perhaps the core problem for naturalistic philosophy. There is a more radical interpretation of eliminativism, however, denying not only mental states, such as beliefs and desires, but also intentionality (i.e., aboutness) on a global level. This position traces its contemporary origin back (...) to Quine, but has generally been assumed to undermine naturalism or, worse, to be incoherent by the majority of philosophers who maintain that there clearly are things or mental states that are about others. In a recent paper, Hutto and Satne (2015a) offer an update that tries to revive John Haugeland’s baseball analogy from his influential 1990 review paper The Intentionality All-Stars on the state of the game to argue that the failure of Neo-Cartesians, Neo- Behaviorists, and Neo-Pragmatists should urge us to make them work together to naturalize content and “win the game.” But Hutto and Satne misunderstand what the game is ultimately about. The goal of the Intentionality All-Stars is not to naturalize content against eliminativism but to defend a naturalist “thirdperson” view of the problem against first-person phenomenalists. For this goal, a naturalist defense of global content eliminativism would equally enable them to emerge victorious. Revisiting Haugeland, I will offer my own analysis of the current state of play to argue that global content eliminativism has not received sufficient attention and deserves a more prominent place in the debate than it currently occupies. (shrink)

What is the primary function of consciousness in the nervous system? The answer to this question remains enigmatic, not so much because of a lack of relevant data, but because of the lack of a conceptual framework with which to interpret the data. To this end, we have developed Passive Frame Theory, an internally coherent framework that, from an action-based perspective, synthesizes empirically supported hypotheses from diverse fields of investigation. The theory proposes that the primary function of consciousness is well-circumscribed, (...) serving the 'somatic nervous system[. For this system, consciousness serves as a frame that constrains and directs skeletal muscle output, thereby yielding adaptive behavior. The mechanism by which consciousness achieves this is more counterintuitive, passive, and “low level” than the kinds of functions that theorists have previously attributed to consciousness. Passive frame theory begins to illuminate (a) what consciousness contributes to nervous function, (b) how consciousness achieves this function, and (c) the neuroanatomical substrates of conscious processes. Our untraditional, action-based perspective focuses on olfaction instead of on vision and is 'descriptive' (describing the products of nature as they evolved to be) rather than 'normative' (construing processes in terms of how they should function). Passive frame theory begins to isolate the neuroanatomical, cognitive-mechanistic, and representational (e.g., conscious contents) processes associated with consciousness. (shrink)

Expertise is a cognitive achievement that clearly involves experience and learning, and often requires explicit, time-consuming training specific to the relevant domain. It is also intuitive that this kind of achievement is, in a rich sense, genuinely perceptual. Many experts—be they radiologists, bird watchers, or fingerprint examiners—are better perceivers in the domain(s) of their expertise. The goal of this paper is to motivate three related claims, by substantial appeal to recent empirical research on perceptual expertise: Perceptual expertise is genuinely perceptual (...) and genuinely cognitive, and this phenomenon reveals how we can become epistemically better perceivers. These claims are defended against sceptical opponents that deny significant top-down or cognitive effects on perception, and opponents who maintain that any such effects on perception are epistemically pernicious. (shrink)

This book contains a representationalist theory of self-consciousness and of the phenomenal first-person perspective. It draws on empirical data from the cognitive and neurosciences.

Interdisciplinary investigations marry the methods and concerns of different fields. Computer science is the study of precise descriptions of finite processes; semantics is the study of meaning in language. Thus, computational semantics embraces any project that approaches the phenomenon of meaning by way of tasks that can be performed by following definite sets of mechanical instructions. So understood, computational semantics revels in applying semantics, by creating intelligent devices whose broader behavior fits the meanings of utterances, and not just their form. (...) IBM’s Watson (Ferrucci, Brown, Chu-Carroll, Fan, Gondek, Kalyanpur, Lally, Murdock, Nyberg, Prager, Schlaefer & Welty 2010) is a harbinger of the excitement and potential of this technology. (shrink)

The aim of this paper is to give an account of what it is to internalize a rule. I claim that internalization is the process of redistributing the burden of instruction from the teacher to the student. The process is complete when instruction is no longer needed, and the rule has reshaped perceptual classification of the circumstances in which it applies. Teaching a rule is the initiation of this process. We internalize rules by simulating instruction coming from someone else. Running (...) these simulations enables us to toggle between the perspective of the instructor and our own perspective. By doing this we coordinate our perspectives with that of the teacher. The account given here provides a deeper explanation of why internalizing a rule involves the dispositions and reactive attitudes proponents of Rule Consequentialism often say it does, why moral reflection is variably demanding, how intergenerational moral progress is made possible by our cognitive architectures, and why the adoption of a rule should be understood in terms of teaching that rule. (shrink)

This is an amended version of material that first appeared in A. Clark, Microcognition: Philosophy, Cognitive Science, and Parallel Distributed Processing (MIT Press, Cambridge, MA, 1989), Ch. 1, 2, and 6. It appears in German translation in Metzinger,T (Ed) DAS LEIB-SEELE-PROBLEM IN DER ZWEITEN HELFTE DES 20 JAHRHUNDERTS (Frankfurt am Main: Suhrkamp. 1999).

Aquinas’s process of abstraction of the particular thing into a universal concept is of pivotal importance for grounding his philosophy and theology in a natural framework. Much has been said and written regarding Aquinas’s doctrine of abstraction, yet recent studies still consider it to be ‘nothing more than a kind of magic.’ This problematic claim is not without foundation, for in trying to understand exactly how this process works, we are constantly faced with an unbridgeable abyss and the repeated vague (...) explanations made by Aquinas. The plain truth is that Aquinas explains what abstraction ought to do and yet, most of the time, he does not explain how it is to be done. This paper intends to show that although Aquinas does not present us with a mechanism for the theory of abstraction, we are nevertheless able to construct a viable mechanism which accords with Aquinas’s guidelines. The aim of constructing a working mechanism that corresponds to what Aquinas demands of the process of abstraction is twofold: First, it attempts to extricate Aquinas’s doctrine of abstraction from the claims of being a quasi-natural doctrine. Second, a viable process of abstraction which is derived from Aquinian-Aristotelian sources can approach contemporary cognitive problems from a fresh point of view. (shrink)

This commentary is divided into two parts. The first considers a possible role for Gray's predictor plus comparator mechanism in human episodic recognition memory. It draws on the computational specifications of recognition outlined in Humphreys et al. to demonstrate how the logically necessary components of recognition tasks might be mapped onto the mechanism. The second part demonstrates how the mechanism outlined by Gray might be implicated in a form of imitative learning suitable for the acquisition of complex tasks.

Gray mistakenly thinks I have rejected the sort of theoretical enterprise he is undertaking, because, according to him, I think that "more data" is all that is needed to resolve all the issues. Not at all. My stalking horse was the bizarre (often pathetic) claim that no amount of empirical, "third-person point-of-view" science (data plus theory) could ever reduce the residue of mystery about consciousness to zero. This "New Mysterianism" (Flanagan, 1991) is one that he should want to combat as (...) vigorously as I have done. (shrink)

The following paper presents a characterization of three distinctions fundamental to computationalism, viz., the distinction between analog and digital machines, representation and nonrepresentation-using systems, and direct and indirect perceptual processes. Each distinction is shown to rest on nothing more than the methodological principles which justify the explanatory framework of the special sciences.

This article deals with the links between the enaction paradigm and artificial intelligence. Enaction is considered a metaphor for artificial intelligence, as a number of the notions which it deals with are deemed incompatible with the phenomenal field of the virtual. After explaining this stance, we shall review previous works regarding this issue in terms of artificial life and robotics. We shall focus on the lack of recognition of co-evolution at the heart of these approaches. We propose to explicitly integrate (...) the evolution of the environment into our approach in order to refine the ontogenesis of the artificial system, and to compare it with the enaction paradigm. The growing complexity of the ontogenetic mechanisms to be activated can therefore be compensated by an interactive guidance system emanating from the environment. This proposition does not however, resolve that of the relevance of the meaning created by the machine (sense-making). Such reflections lead us to integrate human interaction into this environment in order to construct relevant meaning in terms of participative artificial intelligence. This raises a number of questions with regards to setting up an enactive interaction. The article concludes by exploring a number of issues, thereby enabling us to associate current approaches with the principles of morphogenesis, guidance, the phenomenology of interactions and the use of minimal enactive interfaces in setting up experiments which will deal with the problem of artificial intelligence in a variety of enaction-based ways. (shrink)

This review essay critically discusses Andre Kukla's Methods of theoretical psychology. It is argued that Kukla mistakenly tries to build his case for theorizing in psychology as a separate discipline on a dubious distinction between theory and observation. He then argues that the demise of empiricism implies a return of some form of rationalism, which entails an autonomous role for theorizing in psychology. Having shown how this theory-observation dichotomy goes back to traditional and largely abandoned ideas in epistemology, an alternative (...) is presented in the guise of the pragmatist or functionalist tradition, where the interdependence of theory, observation and action is emphasized and the positivist dichotomy of pure observations and pure theory is rejected. Furthermore, we show how recent work on "active" perception supports the functionalist approach. Although the authors agree with Kukla that theory has a legitimate place in psychology, it is suggested that he needlessly limits its scope to autonomous domain-neutral theorizing, and that broadening its perspective to analyzing the presuppositions and implications of empirical work is a more fruitful approach. In fact, the attempt to find the epistemological and philosophical implications of empirical work in perception that is sketched in this review essay is, in the authors' view, a case of theorizing in psychology. (shrink)

The philosophy of emotion has long been divided over the cognitive nature of emotion. In this paper I argue that this debate suffers from deep confusion over the meaning of “cognition” itself. This confusion has in turn obscured critical substantive agreement between the debate’s principal opponents. Capturing this agreement and remedying this confusion requires re-conceptualizing “the cognitive” as it functions in first-order theories of emotion. Correspondingly, a sketch for a new account of cognitivity is offered. However, I also argue that (...) this new account, despite tacit acceptance by all major theories of emotion, in fact rules out some of the most fundamental and controversial claims of one side of the nature-of-emotion debate, emotional cognitivism. (shrink)

Computational complexity theory is a subfield of computer science originating in computability theory and the study of algorithms for solving practical mathematical problems. Amongst its aims is classifying problems by their degree of difficulty — i.e., how hard they are to solve computationally. This paper highlights the significance of complexity theory relative to questions traditionally asked by philosophers of mathematics while also attempting to isolate some new ones — e.g., about the notion of feasibility in mathematics, the $\mathbf{P} \neq \mathbf{NP}$ (...) problem and why it has proven hard to resolve, and the role of non-classical modes of computation and proof. (shrink)

Robust theories concerning the connection between consciousness and brain function should derive not only from empirical evidence but also from a well grounded inind-body ontology. In the case of the comparator hypothesis, Gray develops his ideas relying extensively on empirical evidence, but he bounces irresolutely among logically incompatible metaphysical theses which, in turn, leads him to excessively skeptical conclusions concerning the naturalization of consciousness.

There is widespread belief that connectionist networks are dramatically different from classical or symbolic models. However, connectionists rarely test this belief by interpreting the internal structure of their nets. A new approach to interpreting networks was recently introduced by Berkeley et al. (1995). The current paper examines two implications of applying this method: (1) that the internal structure of a connectionist network can have a very classical appearance, and (2) that this interpretation can provide a cognitive theory that cannot be (...) dismissed as a mere implementation. (shrink)

This paper critically examines the claim that parallel distributed processing (PDP) networks are autonomous learning systems. A PDP model of a simple distributed associative memory is considered. It is shown that the 'generic' PDP architecture cannot implement the computations required by this memory system without the aid of external control. In other words, the model is not autonomous. Two specific problems are highlighted: (i) simultaneous learning and recall are not permitted to occur as would be required of an autonomous system; (...) (ii) connections between processing units cannot simultaneously represent current and previous network activation as would be required if learning is to occur. Similar problems exist for more sophisticated networks constructed from the generic PDP architecture. We argue that this is because these models are not adequately constrained by the properties of the functional architecture assumed by PDP modelers. It is also argued that without such constraints, PDP researchers cannot claim to have developed an architecture radically different from that proposed by the Classical approach in cognitive science. (shrink)

I challenge the dominant understanding of what it means to say two thoughts are associated. The two views that dominate the current literature treat association as a kind of mechanism that drives sequences of thought. The first, which I call reductive associationism, treats association as a kind of neural mechanism. The second treats association as a feature of the kind of psychological mechanism associative processing. Both of these views are inadequate. I argue that association should instead be seen as a (...) highly abstract filler term, standing in for causal relations between representational states in a system. Associations, so viewed, could be implemented by many different mechanisms. I outline the role that this view gives associative models as part of a top-down characterization of psychological processes of any kind and of any complexity. (shrink)

We outline a theory of one puzzling aspect of human cognition: a tendency to exaggerate the degree to which agency is manifested in the world. We call this over‐coherent thinking. We use Pylyshyn's idea of cognitive penetrability to help characterize this notion. We argue that this kind of thinking is essentially narrative in form rather than theoretical. We develop a theory of the relation between the degree of narrativity in a representation and its aptness to represent, and to express, mind. (...) We review the prospects for several theories about how over‐coherent thinking gains a purchase on motivation. We argue that progress in this difficult area may require the abandonment of a categorical belief/imagination distinction in favour of vaguely specified clusterings in a many‐dimensional cognitive space. We conclude with the idea that an error‐prone system for the retention of ideas that are low in some of the characteristics generally thought desirable in belief might emerge as a result of an arms‐race between deceivers and deceiver‐detectors. (shrink)

Double dissociations between perceivable colors and physical properties of colored objects have led many philosophers to endorse relationalist accounts of color. I argue that there are analogous double dissociations between attitudes of belief—the beliefs that people attribute to each other in everyday life—and intrinsic cognitive states of belief—the beliefs that some cognitive scientists posit as cogs in cognitive systems—pitched at every level of psychological explanation. These dissociations provide good reason to refrain from conflating attitudes of belief with intrinsic cognitive states (...) of belief. I suggest that interpretivism provides an attractive account of the former. Like colors, attitudes of belief evolved to be ecological signifiers, not cogs in cognitive systems. (shrink)