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The mind represents abstract magnitude information, including time, space, and number, but in what format is this information stored? We show support for the bipartite format of perceptual magnitudes, in which the measured value on a dimension is scaled to the dynamic range of the input, leading to a privileged status for values at the lowest and highest end of the range. In six experiments with college undergraduates, we show that observers are faster and more accurate to find the endpoints (i.e., the minimum and maximum) than any of the inner values, even as the number of items increases beyond visual short-term memory limits. Our results show that length, size, and number are represented in a dynamic format that allows for comparison-free sorting, with endpoints represented with an immediately accessible status, consistent with the bipartite model of perceptual magnitudes. We discuss the implications for theories of visual search and ensemble perception. [ABSTRACT FROM AUTHOR]

Theory of Mind (ToM) highlights the social-cognitive ability of the individual to communicate and interact effectively with the members of each social group. Essentially, it is the cornerstone of social knowledge that allows the recognition and understanding of the thoughts, intentions, and feelings of all involved, promoting social interaction and engagement. Metacognition (MC) is a higher mental ability of the biological mind and is characterized by the observation, control, evaluation, differentiation, and readjustment of the cognitive mechanism, aiming at its optimal performance and maintaining the homeostasis of mental, social, and emotional becoming of an organism. The rapid development of technology in recent decades has promoted the development of Artificial Intelligence (AI) intertwined with the need to integrate ToM and MC capabilities, enriching human communication. This paper investigates how the above-described human cognitive functions are involved in the conception and development of an artificial agent and their influence on human society. The conclusions suggest the importance of being able to read beliefs, emotions, and other factors, but also introspection by an intelligent system for social benefit, including the necessary ethical constraints.

The 'Language of thought' (LoT) hypothesis advanced by the philosopher Jerry Fodor posits that mental representations are compositional and productive. Thought is symbolic and new complex thoughts are constructed from more basic concepts. The neurocognitive feasibility of the LoT has been challenged in light of the lack of demonstrable neural correlates. We demonstrate that the key ingredients needed for a neural implementation of the LoT are indeed available, using the example of the parahippocampal spatial navigation system in rodents. The classical notion of a 'language of thought' (LoT), advanced prominently by the philosopher Jerry Fodor, is an influential position in cognitive science whereby the mental representations underpinning thought are considered to be compositional and productive, enabling the construction of new complex thoughts from more primitive symbolic concepts. LoT theory has been challenged because a neural implementation has been deemed implausible. We disagree. Examples of critical computational ingredients needed for a neural implementation of a LoT have in fact been demonstrated, in particular in the hippocampal spatial navigation system of rodents. Here, we show that cell types found in spatial navigation (border cells, object cells, head-direction cells, etc.) provide key types of representation and computation required for the LoT, underscoring its neurobiological viability. [ABSTRACT FROM AUTHOR]

Copyright of Revista Electrónica de Enseñanza de las Ciencias is the property of Revista Electronica de Ensenanza de las Ciencias and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Research into the cognitive psychology of proportionality —here, the familiar idea that the severity of the punishment should reflect the severity of the crime—can enrich the study of US criminal sentencing and identify new connections between research in law, psychology and philosophy. This article presents a cognitive-psychological model of proportionality and shows how the model helps to illuminate the behaviour of a range of sentencing decision makers. According to this model, the way in which people tend to mentally represent and compute proportionality means that the latter has at least two behaviourally important features: it is both cognitively intuitive and difficult non-arbitrarily to apply to prison sentences , in well-defined senses of those terms. The interaction between these two features helps to account for data points such as the following: (i) why the original US Sentencing Commission tried to, but did not, base the US Sentencing Guidelines on a retributivist rationale; (ii) why sentencing decision makers are likely to have political-rhetorical flexibility in deciding whether to use the concept of proportionality; and (iii) why several federal judges have observed that sentencing decision makers are susceptible to anchoring. Attending to the psychology of proportionality also yields normative implications and suggestions for future research. [ABSTRACT FROM AUTHOR]

The main purpose of this reflection paper is to present a critical analysis of some of the most prominent epistemological and philosophical ideas developed by contemporary transhumanism in relation to the anatomical-functional activity of the brain and the nature of consciousness. From this point of view, this paper considers whether the technologicalinstrumental hermeneutic model promoted by the transhumanist movement is an alternative, comprehensive variant to elucidate the onto-epistemological complexity of consciousness. To this end, this paper explores the way in which transhumanism has focused on certain techno-scientific fields in order to develop a concrete prospective associated with the cognitive potentialities of the human being. In this sense, it discusses certain specific advances in cuttingedge neurotechnology and artificial neuromodulation (neural implants, neuromorphic devices, neuronal reprogramming, controlled laboratory culture of cerebroids, etc.), as well as artificial intelligence. This analysis results in deep scepticism as to whether the transhumanist approach offers a promising model for successfully tackling the age-old problem of the mind-brain relationship because, despite the appeal of some of its boldest speculations about the bioanthropological condition of man and the ontology of the real, it has chosen to update a reductionist and physicalist view of the human mind. [ABSTRACT FROM AUTHOR]

Copyright of Kultura i Wychowanie is the property of Akademii Humanistyczno-Ekonomicznej and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Technological advances in computer science have secured the computer metaphor status of a heuristic methodological toolused to answer the question about the nature of mind. Nevertheless, some philosophers strongly support opposite opinions.Anti-computationalism in the philosophy of mind is a methodological program that uses extremely heterogeneous grounds for argumentation, deserving analysis and discussion. This article provides an overview and interpretation of the traditional criticismof the computational theory of mind (computationalism); its basic theses have been formed in Western philosophy in the last quarterof the 20th century. The main goal is to reveal the content of the arguments of typical anti-computationalist programs and expandtheir application to the framework of the semantic problems of the Classic Computational Theory of Mind. The main fault of the symbolic approach in the classical computationalism is the absence of a full-fledged theory of semantic properties. The relevance of considering these seemingly outdated problems is justified by the fact that the problem of meaning (and generalproblems of semantics) remains in the core of the latest developments in various areas of AI and the principles of human-computerinteraction.

Neuroclassicism is the view that cognition is explained by "classical" computing mechanisms in the nervous system that exhibit a clear demarcation between processing machinery and read–write memory. The psychologist C. R. Gallistel has mounted a sophisticated defense of neuroclassicism by drawing from ethology and computability theory to argue that animal brains necessarily contain read–write memory mechanisms. This argument threatens to undermine the "connectionist" orthodoxy in contemporary neuroscience, which does not seem to recognize any such mechanisms. In this paper I argue that the neuroclassicist critique rests on a misunderstanding of how computability theory constrains theorizing about natural computing mechanisms. [ABSTRACT FROM AUTHOR]

In this paper, I review the objections against the claim thatbrains are computers, or, to be precise, information-processing mechanisms. By showing that practically all thepopular objections are based on uncharitable (or simplyincorrect) interpretations of the claim, I argue that the claim islikely to be true, relevant to contemporary cognitive(neuro)science, and non-trivial.

Dynamical models of cognition have played a central role in recent cognitive science. In this paper, we consider a common strategy by which dynamical models describe their target systems neither as purely static nor as purely dynamic, but rather using a hybrid approach. This hybridity reveals how dynamical models involve representational choices that are important for understanding the relationship between dynamical and non-dynamical representations of a system. [ABSTRACT FROM AUTHOR]

“The physics of representation” (Poldrack, 2020) aims to (1) define the word “representation” as used in the neurosciences, (2) argue that such representations as described in neuroscience are related to and usefully illuminated by the representations generated by modern neural networks, and (3) establish that these entities are “representations in good standing”. We suggest that Poldrack succeeds in (1), exposes some tensions between the broad use of the term in neuroscience and the narrower class of entities that he identifies in the end, and between the meaning of “representation” in neuroscience and in psychology in (2), and fails in (3). This results in some hard choices: give up on the broad scope of the term in neuroscience (and thereby potentially opening a gap between psychology and neuroscience) or continue to embrace the broad, psychologically inflected sense of the term, and deny the entities generated by neural nets (and the brain) are representations in the relevant sense. [ABSTRACT FROM AUTHOR]

The original computers were people using algorithms to get mathematical results such as rocket trajectories. After the invention of the digital computer, brains have been widely understood through analogies with computers and now artificial neural networks, which have strengths and drawbacks. We define and examine a new kind of computation better adapted to biological systems, called biological computation, a natural adaptation of mechanistic physical computation. Nervous systems are of course biological computers, and we focus on some edge cases of biological computing, hearts and flytraps. The heart has about the computing power of a slug, and much of its computing happens outside of its forty thousand neurons. The flytrap has about the computing power of a lobster ganglion. This account advances fundamental debates in neuroscience by illustrating ways that classical computability theory can miss complexities of biology. By this reframing of computation, we make way for resolving the disconnect between human and machine learning. [ABSTRACT FROM AUTHOR]

Technological advances in computer science have secured the computer metaphor status of a heuristic methodological tool used to answer the question about the nature of mind. Nevertheless, some philosophers strongly support opposite opinions. Anti-computationalism in the philosophy of mind is a methodological program that uses extremely heterogeneous grounds for argumentation, deserving analysis and discussion. This article provides an overview and interpretation of the traditional criticism of the computational theory of mind (computationalism); its basic theses have been formed in Western philosophy in the last quarter of the 20th century. The main goal is to reveal the content of the arguments of typical anti-computationalist programs and expand their application to the framework of the semantic problems of the Classic Computational Theory of Mind. The main fault of the symbolic approach in the classical computationalism is the absence of a full-fledged theory of semantic properties. The relevance of considering these seemingly outdated problems is justified by the fact that the problem of meaning (and general problems of semantics) remains in the core of the latest developments in various areas of AI and the principles of human-computer interaction. [ABSTRACT FROM AUTHOR]

Fodor’s view of the mind is thoroughly computational. This means that the basic kind of mental entity is a “discursive” mental representation and operations over this kind of mental representation have broad architectural scope, extending out to the edges of perception and the motor system. However, in multiple epochs of his work, Fodor attempted to define a functional role for non-discursive, imagistic representation. I describe and critique his two considered proposals. The first view says that images play a particular kind of functional role in certain types of deliberative tasks. The second says that images are solely restricted to the borders of perception, and act as a sort of medium for the fixing of conceptual reference. I argue, against the first proposal, that a broad-scope computationalism such as Fodor’s renders images in principle functionally redundant. I argue, against the second proposal, that empirical evidence suggests that non-discursive representations are learned through perceptual learning, and directly inform category judgments. In each case, I point out extant debates for which the arguments are relevant. The upshot is that there is motivation for limited scope computationalism, in which some, but not all, mental processes operate on discursive mental representations.

In this paper, I argue that enactivism and computationalism—two seemingly incompatible research traditions in modern cognitive science—can be fruitfully reconciled under the framework of the free energy principle (FEP). FEP holds that cognitive systems encode generative models of their niches and cognition can be understood in terms of minimizing the free energy of these models. There are two philosophical interpretations of this picture. A computationalist will argue that as FEP claims that Bayesian inference underpins both perception and action, it entails a concept of cognition as a computational process. An enactivist, on the other hand, will point out that FEP explains cognitive systems as constantly self-organizing to non-equilibrium steady-state. My claim is that these two interpretations are both true at the same time and that they enlighten each other. [ABSTRACT FROM AUTHOR]

There has been debate between those who maintain that indexical expressions are not essential and those who maintain that such indexicals cannot be dispensed with without an important loss of content. This version of the essentialist view holds that thoughts must also have indexical elements. Indexical thoughts appear to be in tension with the computational theory of mind (CTM). In this case we have the following inconsistent triad:(i) De se thoughts are essential.(ii) De se thoughts are indexical, they have a (Kaplanian) character.(iii) Computations can only take the syntactic type into account, they cannot take tokens into account.If (iii) is correct, then it seems we cannot make sense of a thought which uses a character such that its referent could vary from tokening to tokening. I argue that (iii) need not cause a problem, while maintaining the CTM. I claim that computations need not be sensitive to the features of a tokened symbol in the way that character demands. This job may be performed by a non‐modular part of the mind. Resolving the triad in this way provides a reason to accept that indexicals in thought are possible. [ABSTRACT FROM AUTHOR]

In the 70 years since Alan Turing's 'Computing Machinery and Intelligence' appeared in Mind, there have been two widely-accepted interpretations of the Turing test: the canonical behaviourist interpretation and the rival inductive or epistemic interpretation. These readings are based on Turing's Mind paper; few seem aware that Turing described two other versions of the imitation game. I have argued that both readings are inconsistent with Turing's 1948 and 1952 statements about intelligence, and fail to explain the design of his game. I argue instead for a response-dependence interpretation (Proudfoot 2013). This interpretation has implications for Turing's view of free will: I argue that Turing's writings suggest a new form of free will compatibilism, which I call response-dependence compatibilism (Proudfoot 2017a). The philosophical implications of rethinking Turing's test go yet further. It is assumed by numerous theorists that Turing anticipated the computational theory of mind. On the contrary, I argue, his remarks on intelligence and free will lead to a new objection to computationalism. [ABSTRACT FROM AUTHOR]

DOI: http://doi.org/10.26333/sts.xxxiv1.09 Gödel’s first incompleteness theorem is sometimes said to refute mechanism about the mind. §1 contains a discussion of mechanism. We look into its origins, motivations and commitments, both in general and with regard to the human mind, and ask about the place of modern computers and modern cognitive science within the general mechanistic paradigm. In §2 we give a sharp formulation of a mechanistic thesis about the mind in terms of the mathematical notion of computability. We present the argument from Gödel’s theorem against mechanism in terms of this formulation and raise two objections, one of which is known but is here given a more precise formulation, and the other is new and based on the discussion in §1.

Gödel's first incompleteness theorem is sometimes said to refute mechanism about the mind. §1 contains a discussion of mechanism. We look into its origins, motivations and commitments, both in general and with regard to the human mind, and ask about the place of modern computers and modern cognitive science within the general mechanistic paradigm. In §2 we give a sharp formulation of a mechanistic thesis about the mind in terms of the mathematical notion of computability. We present the argument from Gödel's theorem against mechanism in terms of this formulation and raise two objections, one of which is known but is here given a more precise formulation, and the other is new and based on the discussion in §1. [ABSTRACT FROM AUTHOR]

The philosophical-psychological Lvov-Warsaw School, derived from the philosophical tradition of Franz Brentano, developed his concept of intentionality for many years in an original way. This is particularly evident in Kazimierz Twardowski's theory of actions and products and Tadeusz Tomaszewski's theory of action. Kazimierz Ajdukiewicz's semantic epistemology is also an important yet unfinished achievement (though less related to the issue of intentionality), in the light of which cognitive processes are organically embedded in cultural artefacts and, more specifically, in language. Despite the extraordinary wealth of the Lvov-Warsaw School's achievements, the theoretical findings of Twardowski and his disciples allow for the extraction of relatively consistent conclusions regarding the specifics of human cognition. Achievements of the Polish school of psychology seem to be important in the long ongoing discussion on the topic of the nature of cognitive processes and the mind. [ABSTRACT FROM AUTHOR]

Opponents of the computational theory of mind (CTM) have held that the theory is devoid of explanatory content, since whatever computational procedures are said to account for our cognitive attributes will also be realized by a host of other 'deviant' physical systems, such as buckets of water and possibly even stones. Such 'triviality' claims rely on a simple mapping account (SMA) of physical implementation. Hence defenders of CTM traditionally attempt to block the trivialization critique by advocating additional constraints on the implementation relation. However, instead of attempting to 'save' CTM by constraining the account of physical implementation, I argue that the general form of the triviality argument is invalid. I provide a counterexample scenario, and show that SMA is in fact consistent with empirically rich and theoretically plausible versions of CTM. This move requires rejection of the computational sufficiency thesis, which I argue is scientifically unjustified in any case. By shifting the 'burden of explanatory force' away from the concept of physical implementation, and instead placing it on salient aspects of the target phenomenon to be explained, it's possible to retain a maximally liberal and unfettered view of physical implementation, and at the same time defuse the triviality arguments that have motivated defenders of CTM to impose various theory-laden constraints on SMA. [ABSTRACT FROM AUTHOR]

Triviality arguments against the computational theory of mind claim that computational implementation is trivial and thus does not serve as an adequate metaphysical basis for mental states. It is common to take computational implementation to consist in a mapping from physical states to abstract computational states. In this paper, I propose a novel constraint on the kinds of physical states that can implement computational states, which helps to specify what it is for two physical states to non-trivially implement the same computational state. [ABSTRACT FROM AUTHOR]

In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of working memory to show how modeling has progressed over the years. The methodological assumptions of new modeling work are best understood in the mechanistic framework, which is evidenced by the way in which models are empirically validated. Moreover, the methodological and theoretical progress in computational neuroscience vindicates the new mechanistic approach to explanation, which, at the same time, justifies the best practices of computational modeling. Overall, computational modeling is deservedly successful in cognitive (neuro)science. Its successes are related to deep conceptual connections between cognition and computation. Computationalism is not only here to stay, it becomes stronger every year. [ABSTRACT FROM AUTHOR]

Copyright of Annals of Philosophy / Roczniki Filozoficzne is the property of John Paul II Catholic University of Lublin, Faculty of Philosophy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper argues that deciding on whether the cognitive sciences need a Representational Theory of Mind matters. Far from being merely semantic or inconsequential, the answer we give to the RTM-question makes a difference to how we conceive of minds. How we answer determines which theoretical framework the sciences of mind ought to embrace. The structure of this paper is as follows. Section 1 outlines Rowlands’s (2017) argument that the RTM-question is a bad question and that attempts to answer it, one way or another, have neither practical nor theoretical import. Rowlands concludes this because, on his analysis, there is no non-arbitrary fact of the matter about which properties something must possess in order to qualify as a mental representation. By way of reply, we admit that Rowlands’s analysis succeeds in revealing why attempts to answer the RTM-question simpliciter are pointless. Nevertheless, we show that if specific formulations of the RTM-question are stipulated, then it is possible, conduct substantive RTM debates that do not collapse into merely verbal disagreements. Combined, Sections 2 and 3 demonstrate how, by employing specifying stipulations, we can get around Rowlands’s arbitrariness challenge. Section 2 reveals why RTM, as canonically construed in terms of mental states exhibiting intensional (with-an-s) properties, has been deemed a valuable explanatory hypothesis in the cognitive sciences. Targeting the canonical notion of mental representations, Section 3 articulates a rival nonrepresentational hypothesis that, we propose, can do all the relevant explanatory work at much lower theoretical cost. Taken together, Sections 2 and 3 show what can be at stake in the RTM debate when it is framed by appeal to the canonical notion of mental representation and why engaging in it matters. Section 4 extends the argument for thinking that RTM debates matter. It provides reasons for thinking that, far from making no practical or theoretical difference to the sciences of the mind, deciding to abandon RTM would constitute a revolutionary conceptual shift in those sciences. [ABSTRACT FROM AUTHOR]

We analyse Hutto & Myin's three arguments against computationalism [Hutto, D., E. Myin, A. Peeters, and F. Zahnoun. Forthcoming. “The Cognitive Basis of Computation: Putting Computation In Its Place.” In The Routledge Handbook of the Computational Mind, edited by M. Sprevak, and M. Colombo. London: Routledge.; Hutto, D., and E. Myin. 2012. Radicalizing Enactivism: Basic Minds Without Content. Cambridge, MA: MIT Press; Hutto, D., and E. Myin. 2017. Evolving Enactivism: Basic Minds Meet Content. Cambridge, MA: MIT Press]. The Hard Problem of Content targets computationalism that relies on semantic notion of computation, claiming that it cannot account for the natural origins of content. The Intentionality Problem is targeted against computationalism using non-semantic accounts of computation, arguing that it fails in explaining intentionality. The Abstraction Problem claims that causal interaction between concrete physical processes and abstract computational properties is problematic. We argue that these arguments are flawed and are not enough to rule out computationalism. [ABSTRACT FROM AUTHOR]

We analyse Hutto & Myin's three arguments against computationalism [Hutto, D., E. Myin, A. Peeters, and F. Zahnoun. Forthcoming. “The Cognitive Basis of Computation: Putting Computation In Its Place.” In The Routledge Handbook of the Computational Mind, edited by M. Sprevak, and M. Colombo. London: Routledge.; Hutto, D., and E. Myin. 2012. Radicalizing Enactivism: Basic Minds Without Content. Cambridge, MA: MIT Press; Hutto, D., and E. Myin. 2017. Evolving Enactivism: Basic Minds Meet Content. Cambridge, MA: MIT Press]. The Hard Problem of Content targets computationalism that relies on semantic notion of computation, claiming that it cannot account for the natural origins of content. The Intentionality Problem is targeted against computationalism using non-semantic accounts of computation, arguing that it fails in explaining intentionality. The Abstraction Problem claims that causal interaction between concrete physical processes and abstract computational properties is problematic. We argue that these arguments are flawed and are not enough to rule out computationalism. [ABSTRACT FROM AUTHOR]

The 'Mind-Upload' hypothesis (MU), a radical version of the Brain-in-a-Vat thought experiment, asserts that a whole mind can safely be transferred from a brain to a digital device, after being exactly encoded into substrate independent informational patterns. Prima facie, MU seems the philosophical archenemy of the Embodied Mind theory (EM), which understands embodiment as a necessary and constitutive condition for the existence of a mind and its functions. In truth, whether and why MU and EM are ultimately incompatible is unobvious. This paper, which aims to answer both questions, will not simply confirm that MU and EM actually are incompatible. It will also show the true reason of their incompatibility: while EM implies that a mind's individual identity is contingent upon the details of its physical constituents, MU presupposes that minds can be relocated from one material vessel to another. A systematic comparison between these conflicting assumptions reveals that the real shortcoming of MU is not the one usually discussed by the philosophical literature: it has nothing to do with MU's functionalist or computationalist prerequisites, and is only secondarily related to the artificial implementability of consciousness; the real problem is that MU presupposes that minds could still be individuated and numerically identified while being reduced to immaterial formal patterns. EM seems committed to refute this assumption, but does it have sufficient resources to succeed? [ABSTRACT FROM AUTHOR]

Copyright of Universum is the property of Instituto de Estudios Humanisticos Juan Ignacio Molina, Universidad de Talca and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)