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 Then I argue that early formulations of these reasons are outdated.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 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. (shrink)

The assumption that psychological states and processes are computational in character pervades much of cognitive science, what many call the computational theory of mind. In addition to occupying a central place in cognitive science, the computational theory of mind has also had a second life supporting “individualism”, the view that psychological states should be taxonomized so as to supervene only on the intrinsic, physical properties of individuals. One response to individualism has been to raise the prospect of “wide computational systems”, (...) in which some computational units are instantiated outside the individual. “Wide computationalism” attempts to sever the link between individualism and computational psychology by enlarging the concept of computation. However, in spite of its potential interest to cognitive science, wide computationalism has received little attention in philosophy of mind and cognitive science. This paper aims to revisit the prospect of wide computationalism. It is argued that by appropriating a mechanistic conception of computation wide computationalism can overcome several issues that plague initial formulations. The aim is to show that cognitive science has overlooked an important and viable option in computational psychology. The paper marshals empirical support and responds to possible objections. (shrink)

'Computationalism' is a relatively vague term used to describe attempts to apply Turing's model of computation to phenomena outside its original purview: in modelling the human mind, in physics, mathematics, etc. Early versions of computationalism faced strong objections from many (and varied) quarters, from philosophers to practitioners of the aforementioned disciplines. Here we will not address the fundamental question of whether computational models are appropriate for describing some or all of the wide range of processes that they have (...) been applied to, but will focus instead on whether `renovated' versions of the \textit{new computationalism} shed any new light on or resolve previous tensions between proponents and skeptics. We find this, however, not to be the case, because the 'new computationalism' falls short by using limited versions of "traditional computation", or proposing computational models that easily fall within the scope of Turing's original model, or else proffering versions of hypercomputation with its many pitfalls. (shrink)

This paper argues for a noncognitiveist computationalism in the philosophy of mind. It further argues that both humans and computers have intentionality, that is, their mental states are semantical -- they are about things in their worlds.

Since the early eighties, computationalism in the study of the mind has been “under attack” by several critics of the so-called “classic” or “symbolic” approaches in AI and cognitive science. Computationalism was generically identified with such approaches. For example, it was identified with both Allen Newell and Herbert Simon’s Physical Symbol System Hypothesis and Jerry Fodor’s theory of Language of Thought, usually without taking into account the fact ,that such approaches are very different as to their methods and (...) aims. Zenon Pylyshyn, in his influential book Computation and Cognition, claimed that both Newell and Fodor deeply influenced his ideas on cognition as computation. This probably added to the confusion, as many people still consider Pylyshyn’s book as paradigmatic of the computational approach in the study of the mind. Since then, cognitive scientists, AI researchers and also philosophers of the mind have been asked to take sides on different “paradigms” that have from time to time been proposed as opponents of (classic or symbolic) computationalism. Examples of such oppositions are: -/- computationalism vs. connectionism, computationalism vs. dynamical systems, computationalism vs. situated and embodied cognition, computationalism vs. behavioural and evolutionary robotics. -/- Our preliminary claim in section 1 is that computationalism should not be identified with what we would call the “paradigm (based on the metaphor) of the computer” (in the following, PoC). PoC is the (rather vague) statement that the mind functions “as a digital computer”. Actually, PoC is a restrictive version of computationalism, and nobody ever seriously upheld it, except in some rough versions of the computational approach and in some popular discussions about it. Usually, PoC is used as a straw man in many arguments against computationalism. In section 1 we look in some detail at PoC’s claims and argue that computationalism cannot be identified with PoC. In section 2 we point out that certain anticomputationalist arguments are based on this misleading identification. In section 3 we suggest that the view of the levels of explanation proposed by David Marr could clarify certain points of the debate on computationalism. In section 4 we touch on a controversial issue, namely the possibility of developing a notion of analog computation, similar to the notion of digital computation. A short conclusion follows in section 5. (shrink)

In this paper, the Author reviewed the typical objections against the claim that brains are computers, or, to be more precise, information-processing mechanisms. By showing that practically all the popular objections are based on uncharitable interpretations of the claim, he argues that the claim is likely to be true, relevant to contemporary cognitive science, and non-trivial.

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. Theion Problem claims that causal interaction between concrete physical processes and abstract computational properties is problematic. We argue that these a... (shrink)

In this paper we will demonstrate that a computational system can meet the criteria for autonomy laid down by classical enactivism. The two criteria that we will focus on are operational closure and structural determinism, and we will show that both can be applied to a basic example of a physically instantiated Turing machine. We will also address the question of precariousness, and briefly suggest that a precarious Turing machine could be designed. Our aim in this paper is to challenge (...) the assumption that computational systems are necessarily heteronomous systems, to try and motivate in enactivism a more nuanced and less rigid conception of computational systems, and to demonstrate to computational theorists that they might find some interesting material within the enactivist tradition, despite its historical hostility towards computationalism. (shrink)

This essay is divided into two parts. In the first part (§2), I introduce the idea of practical meaning by looking at a certain kind of procedural systems — the motor system — that play a central role in computational explanations of motor behavior. I argue that in order to give a satisfactory account of the content of the representations computed by motor systems (motor commands), we need to appeal to a distinctively practical kind of meaning. Defending the explanatory relevance (...) of semantic properties in a computationalist explanation of motor behavior, my argument concludes that practical meanings play a central role in an adequate psychological theory of motor skill. In the second part of this essay (§3), I generalize and clarify the notion of practical meaning, and I defend the intelligibility of practical meanings against an important objection. (shrink)

In this reply to James H. Fetzer’s “Minds and Machines: Limits to Simulations of Thought and Action”, I argue that computationalism should not be the view that (human) cognition is computation, but that it should be the view that cognition (simpliciter) is computable. It follows that computationalism can be true even if (human) cognition is not the result of computations in the brain. I also argue that, if semiotic systems are systems that interpret signs, then both humans and (...) computers are semiotic systems. Finally, I suggest that minds can be considered as virtual machines implemented in certain semiotic systems, primarily the brain, but also AI computers. In doing so, I take issue with Fetzer’s arguments to the contrary. (shrink)

It is shown that the Fodor's interpretation of the frame problem is the central indication that his version of the Modularity Thesis is incompatible with computationalism. Since computationalism is far more plausible than this thesis, the latter should be rejected.

Ita La recensione presenta la prospettiva enattivista difesa da Alva Noë, e ne discute alcuni aspetti specifici. Il pensiero, la coscienza e la cognizione non sono pienamente comprensibili, secondo l’enattivismo di Noë, senza un’adeguata considerazione del ruolo ricoperto dal corpo e dall’ambiente. Sarebbe quindi sbagliato continuare a pensare che il cervello da solo sia responsabile dei processi cognitivi umani: il programma che ricerca i correlati neurali della coscienza sarebbe quindi destinato al fallimento dal principio, perché tralascia in partenza corpo e (...) ambiente; i programmi di ricerca nel campo dell’intelligenza artificiale sarebbero ugualmente compromessi, non solo con una concezione computazionalista della cognizione, ma anche con la vecchia idea che un cervello artificiale sia sufficiente alla cognizione quanto un cervello naturale. Di seguito si prendono in esame due prospettive sperimentali su cui Noë fa grande affidamento: gli studi sulla plasticità neurale dei furetti svolti da Mriganka Sur e altri, e la realizzazione di un sistema di sostituzione visuo-tattile da parte di Paul Bach-Y-Rita. Per Noë si tratta di elementi cruciali in supporto alla propria prospettiva: in realtà, come emerge dalla breve analisi, l’attribuire loro un significato così chiaro e univoco pro-enattivismo è qualcosa di molto meno scontato. Infine, segue un breve bilancio del libro di Noë, dove gli elementi d’interesse del volume sono presentati insieme all’individuazione di alcuni punti deboli, che il testo condivide con la gran parte degli studi che in vario modo fanno leva sull’intuizione legata all’embodiement: da un lato una difficoltà strutturale riguarda la possibilità di identificare con chiarezza gli elementi costitutivi del mentale; dall’altro lato, il riferimento a forme di esternalismo radicale sembra ugualmente comportare diversi problemi. -/- Abstract Eng The review presents Alva Noë’s enactivist view, and aims at discussing some of its ideas. Thought, consciousness, and cognition are not understandable, Noë claims, without taking into proper consideration the role played by the body and the environment. It would be wrong indeed to go on thinking that our brain alone is responsible for human cognitive processes: the program searching for the neural correlates of consciousness is hopeless in principle, because it neglects from the beginning the body and the environment; research programs in artificial intelligence are as well compromised, not only with a computationalist view of cognition, but also with the old idea that an artificial brain will suffice for cognition just like a natural one. Thereafter, two experimental perspectives, that Noë uses to support his view, are examined: Mriganka Sur’s studies on neural plasticity of ferrets, and Paul Bach-Y-Rita’s tactile-visual substitution system. Noë argues that these results are crucial in supporting his view, but, as the discussion highlights, their pro-enactivism meaning is not so clear and unambiguous. Finally, a balance of the book follows, where the many elements of interest are presented together with the acknowledgment of some weak points, that the book shares with the majority of the proposals that deal with the embodiment’s insight: on the one hand, a structural difficulty concerns the possibility to identify clearly the constitutive elements of the mental; on the other hand, the reference to radical versions of externalism seems to entail many difficulties as well. (shrink)

The theory that all processes in the universe are computational is attractive in its promise to provide an understandable theory of everything. I want to suggest here that this pancomputationalism is not sufficiently clear on which problem it is trying to solve, and how. I propose two interpretations of pancomputationalism as a theory: I) the world is a computer and II) the world can be described as a computer. The first implies a thesis of supervenience of the physical over computation (...) and is thus reduced ad absurdum. The second is underdetermined by the world, and thus equally unsuccessful as theory. Finally, I suggest that pancomputationalism as metaphor can be useful. – At the Paderborn workshop in 2008, this paper was presented as a commentary to the relevant paper by Gordana Dodig-Crnkovic " Info-Computationalism and Philosophical Aspects of Research in Information Sciences". (shrink)

The dialogue develops arguments for and against a broad new world system - info-computationalist naturalism - that is supposed to overcome the traditional mechanistic view. It would make the older mechanistic view into a special case of the new general info-computationalist framework (rather like Euclidian geometry remains valid inside a broader notion of geometry). We primarily discuss what the info-computational paradigm would mean, especially its pancomputationalist component. This includes the requirements for a the new generalized notion of computing that would (...) include sub-symbolic information processing. We investigate whether pancomputationalism can provide the basic causal structure to the world and whether the overall research program of info-computationalist naturalism appears productive, especially when it comes to new approaches to the living world, including computationalism in the philosophy of mind. (shrink)

I review a widely accepted argument to the conclusion that the contents of our beliefs, desires and other mental states cannot be causally efficacious in a classical computational model of the mind. I reply that this argument rests essentially on an assumption about the nature of neural structure that we have no good scientific reason to accept. I conclude that computationalism is compatible with wide semantic causal efficacy, and suggest how the computational model might be modified to accommodate this (...) possibility. (shrink)

John Searle and Roger Penrose are two staunch critics of computationalism who nonetheless believe that with the right framework the mind can be naturalized. While they may be successful in showing the shortcomings of computationalism, I argue that their alternative non-computational frameworks equally fail to carry out the project to naturalize the mind. The main reason is their failure to resolve some fundamental incompatibilities between mind and science. Searle tries to resolve the incompatibility between the subjectivity of consciousness (...) and the objectivity of science by means of conceptual clarification. He, however, fails to deal with the concepts crucial to this incompatibility, namely, the publicness of scientific knowledge and the privacy of psychological knowledge. Penrose tries to resolve the incompatibility between the non-computationality of psychological process and the computationality of scientific process by expanding the scope of science through some radical changes in quantum physics. His strategy, however, has the danger of trivializing the distinction between science and non-science thereby putting into question the very value of the project to naturalize the mind. In addition, the feasibility of this strategy remains dubious in light of the mysteries that still surround quantum physics. (shrink)

Multiple realizability (MR) is traditionally conceived of as the feature of computational systems, and has been used to argue for irreducibility of higher-level theories. I will show that there are several ways a computational system may be seen to display MR. These ways correspond to (at least) five ways one can conceive of the function of the physical computational system. However, they do not match common intuitions about MR. I show that MR is deeply interest-related, and for this reason, difficult (...) to pin down exactly. I claim that MR is of little importance for defending computationalism, and argue that it should rather appeal to organizational invariance or substrate neutrality of computation, which are much more intuitive but cannot support strong antireductionist arguments. (shrink)

The most cursory examination of the history of artificial intelligence highlights numerous egregious claims of its researchers, especially in relation to a populist form of ‘strong’ computationalism which holds that any suitably programmed computer instantiates genuine conscious mental states purely in virtue of carrying out a specific series of computations. The argument presented herein is a simple development of that originally presented in Putnam’s (Representation & Reality, Bradford Books, Cambridge in 1988 ) monograph, “Representation & Reality”, which if correct, (...) has important implications for turing machine functionalism and the prospect of ‘conscious’ machines. In the paper, instead of seeking to develop Putnam’s claim that, “everything implements every finite state automata”, I will try to establish the weaker result that, “everything implements the specific machine Q on a particular input set ( x )”. Then, equating Q ( x ) to any putative AI program, I will show that conceding the ‘strong AI’ thesis for Q (crediting it with mental states and consciousness) opens the door to a vicious form of panpsychism whereby all open systems, (e.g. grass, rocks etc.), must instantiate conscious experience and hence that disembodied minds lurk everywhere. (shrink)

ABSTRACT. Thought experiments about de se attitudes and Jackson’s original Knowledge Argument are compared with each other and discussed from the perspective of a computational theory of mind. It is argued that internal knowledge, i.e. knowledge formed on the basis of signals that encode aspects of their own processing rather than being intentionally directed towards external objects, suffices for explaining the seminal puzzles without resorting to acquaintance or phenomenal character as primitive notions. Since computationalism is ontologically neutral, the account (...) also explains why neither Lewis’s two gods nor Mary’s surprise in the Knowledge Argument violate physicalism. (shrink)

The paper presents a paradoxical feature of computational systems that suggests that computationalism cannot explain symbol grounding. If the mind is a digital computer, as computationalism claims, then it can be computing either over meaningful symbols or over meaningless symbols. If it is computing over meaningful symbols its functioning presupposes the existence of meaningful symbols in the system, i.e. it implies semantic nativism. If the mind is computing over meaningless symbols, no intentional cognitive processes are available prior to (...) symbol grounding. In this case, no symbol grounding could take place since any grounding presupposes intentional cognitive processes. So, whether computing in the mind is over meaningless or over meaningful symbols, computationalism implies semantic nativism. (shrink)

For many years now, Harnad has argued that transduction is special among cognitive capacities -- special enough to block Searle's Chinese Room Argument. His arguments (as well as Searle's) have been important and useful, but not correct, it seems to me. Their arguments have provided the modern impetus for getting clear about computationalism and the nature of computing. This task has proven to be quite difficult. Which is simply to say that dealing with Harnad's arguments (as well as Searle's) (...) has been difficult. Turing, it turns out, only got us started. But Harnad's (and Searle's) arguments ultimately fail. Turing, it turns out, was on the right track. (shrink)

Materialism, reductionism, behaviorism, functionalism, dynamic systems theory and computationalism are popular views, but they were shown by Wittgenstein to be incoherent. The study of behavior encompasses all of human life but behavior is largely automatic and unconscious and even the conscious part, mostly expressed in language (which Wittgenstein equates with the mind), is not perspicuous, so it is critical to have a framework which Searle calls the Logical Structure of Rationality (LSR) and I call the Descriptive Psychology of Higher (...) Order Thought (DPHOT). After summarizing the framework worked out by Wittgenstein and Searle, as extended by modern reasoning research, I comment on this first book in a trilogy on Human Nature by the leading authority on Wittgenstein. -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my article The Logical Structure of Philosophy, Psychology, Mind and Language as Revealed in Wittgenstein and Searle 59p(2016). For all my articles on Wittgenstein and Searle see my e-book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Wittgenstein and Searle 367p (2016). Those interested in all my writings in their most recent versions may consult my e-book Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2016 662p (2016). -/- All of my papers and books have now been published in revised versions both in ebooks and in printed books. -/- Talking Monkeys: Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet - Articles and Reviews 2006-2017 (2017) https://www.amazon.com/dp/B071HVC7YP. -/- The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle--Articles and Reviews 2006-2016 (2017) https://www.amazon.com/dp/B071P1RP1B. -/- Suicidal Utopian Delusions in the 21st century: Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2017 (2017) https://www.amazon.com/dp/B0711R5LGX . (shrink)

Materialism, reductionism, behaviorism, functionalism, dynamic systems theory and computationalism are popular views, but they were shown by Wittgenstein to be incoherent. The study of behavior encompasses all of human life but behavior is largely automatic and unconscious and even the conscious part, mostly expressed in language (which Wittgenstein equates with the mind), is not perspicuous, so it is critical to have a framework which Searle calls the Logical Structure of Rationality (LSR) and I call the Descriptive Psychology of Higher (...) Order Thought (DPHOT). After summarizing the framework worked out by Wittgenstein and Searle, as extended by modern reasoning research, I show the inadequacies in Carruther’s views, which pervade most discussions of behavior including contemporary behavioral sciences. I maintain that his book is an amalgam of two books, one a summary of cognitive psychology and the other a summary of the standard philosophical confusions on the mind with some new jargon added. I suggest that the latter should be regarded as incoherent or as a cartoon view of life and that taking Wittgenstein at his word, we can practice successful self therapy by regarding the mind/body issue as a language/body issue. -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my article The Logical Structure of Philosophy, Psychology, Mind and Language as Revealed in Wittgenstein and Searle 59p(2016). For all my articles on Wittgenstein and Searle see my e-book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Wittgenstein and Searle 367p (2016). Those interested in all my writings in their most recent versions may consult my e-book Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2016 662p (2016). -/- All of my papers and books have now been published in revised versions both in ebooks and in printed books. -/- Talking Monkeys: Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet - Articles and Reviews 2006-2017 (2017) https://www.amazon.com/dp/B071HVC7YP. -/- The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle--Articles and Reviews 2006-2016 (2017) https://www.amazon.com/dp/B071P1RP1B. -/- Suicidal Utopian Delusions in the 21st century: Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2017 (2017) https://www.amazon.com/dp/B0711R5LGX . (shrink)

In this paper, I review the objections against the claim that brains are computers, or, to be precise, information-processing mechanisms. By showing that practically all the popular objections are either based on uncharitable interpretation of the claim, or simply wrong, I argue that the claim is likely to be true, relevant to contemporary cognitive (neuro)science, and non-trivial.

The contribution of the body to cognition and control in natural and artificial agents is increasingly described as “off-loading computation from the brain to the body”, where the body is said to perform “morphological computation”. Our investigation of four characteristic cases of morphological computation in animals and robots shows that the ‘off-loading’ perspective is misleading. Actually, the contribution of body morphology to cognition and control is rarely computational, in any useful sense of the word. We thus distinguish (1) morphology that (...) facilitates control, (2) morphology that facilitates perception and the rare cases of (3) morphological computation proper, such as ‘reservoir computing.’ where the body is actually used for computation. This result contributes to the understanding of the relation between embodiment and computation: The question for robot design and cognitive science is not whether computation is offloaded to the body, but to what extent the body facilitates cognition and control – how it contributes to the overall ‘orchestration’ of intelligent behaviour. (shrink)

This chapter describes the conceptual foundations of cognitive science during its establishment as a science in the 20th century. It is organized around the core ideas of individual agency as its basic explanans and information-processing as its basic explanandum. The latter consists of a package of ideas that provide a mathematico-engineering framework for the philosophical theory of materialism.

This paper investigates the prospects of Rodney Brooks’ proposal for AI without representation. It turns out that the supposedly characteristic features of “new AI” (embodiment, situatedness, absence of reasoning, and absence of representation) are all present in conventional systems: “New AI” is just like old AI. Brooks proposal boils down to the architectural rejection of central control in intelligent agents—Which, however, turns out to be crucial. Some of more recent cognitive science suggests that we might do well to dispose of (...) the image of intelligent agents as central representation processors. If this paradigm shift is achieved, Brooks’ proposal for cognition without representation appears promising for full-blown intelligent agents—Though not for conscious agents. (shrink)

Extended cognition holds that cognitive processes sometimes leak into the world (Dawson, 2013). A recent trend among proponents of extended cognition has been to put pressure on phenomena thought to be safe havens for internalists (Sneddon, 2011; Wilson, 2010; Wilson & Lenart, 2014). This paper attempts to continue this trend by arguing that music perception is an extended phenomenon. It is claimed that because music perception involves the detection of musical invariants within an “acoustic array”, the interaction between the auditory (...) system and the musical invariants can be characterized as an extended computational cognitive system. In articulating this view, the work of J. J. Gibson (1966, 1986) and Robert Wilson (1994, 1995, 2004) is drawn on. The view is defended from several objections and its implications outlined. The paper concludes with a comparison to Krueger’s (2014) view of the “musically extended emotional mind”. (shrink)

I want to suggest that the major influence of classical arguments for embodiment like "The Embodied Mind" by Varela, Thomson & Rosch (1991) has been a changing of positions rather than a refutation: Cognitivism has found ways to retreat and regroup at positions that have better fortification, especially when it concerns theses about artificial intelligence or artificial cognitive systems. For example: a) Agent-based cognitivism' that understands humans as taking in representations of the world, doing rule-based processing and then acting on (...) them (sense-plan-act) is often limited to conscious decision processes; and b) Purely syntactic cognition is compatible with embodiment, or supplemented by embodiment (e.g. for 'grounding'). While the empirical thesis of embodied cognition ('embodied cognitive science') is true and the practical engineering thesis ('morphological computation', 'cheap design') is often true, the conceptual thesis ('embodiment is necessary for cognition') is likely false - syntax is often enough for cognition, unless grounding is really necessary. I conclude that it has become more sensible to integrate embodiment with traditional approaches rather than "fight for embodiment" or "against cognitivism". (shrink)

Wittgenstein's arguments about rule-following and private language turn both on interpretation and what he called our 'pictures' of the mind. His remarks about these can be understood in terms of the conceptual metaphor of the mind as a container, and enable us to give a better account of physicalism.

In The Innocent Eye, Nico Orlandi argues that vision is not a cognitive process. In particular, she argues that forming subject-level visual representations that are available for reasoning should not itself be understood as a process of inference. This comes to the claim that vision (properly so-called) is a process that produces representations but is not best understood as a process that uses representations.

Conventional approaches to consciousness assume that our current science tells us within tolerable limits what physical nature is. Because nature so understood cannot explain consciousness as we seem to experience it ourselves, explaining consciousness becomes a problem. One solution is to rethink what consciousness is so that it becomes the sort of thing our current natural science could in principle explain. Whitehead takes the opposite approach, using the existence of consciousness as a clue to what nature must be if it (...) can generate something like consciousness. The justification for this approach can be found in Whitehead’s implicit indictment of descriptive phenomenology. According to Whitehead, the seemingly insoluble problem of explaining consciousness naturalistically is an artifact created by the assumption that consciousness faithfully samples the world, when in fact it obscures the very aspects of nature that are indispensable to understanding how anything, including consciousness itself, could emerge through a physical process. (shrink)

Il lavoro esamina criticamente i presupposti di cinque differenti approcci alla Scienza Cognitiva, (simbolico, connessionista, dinamico, della cognizione incarnata e della vita artificiale) e sostiene che tutti e cinque condividono tacitamente un’ipotesi metodologica molto generale. Tale ipotesi, che propongo di chiamare simulazionismo , postula che i fenomeni cognitivi di un qualunque sistema reale possono essere adeguatamente spiegati sulla base di opportuni modelli di simulazione del sistema stesso. Tuttavia, a causa della loro costituzione, i modelli di simulazione hanno forti limitazioni, sia (...) al livello descrittivo che esplicativo. Il limite descrittivo sta nel fatto che la corrispondenza fra i risultati di una simulazione e i dati relativi al fenomeno reale non è diretta e intrinseca ma, al più, indiretta e estrinseca. Il limite esplicativo consiste nel fatto che le spiegazioni supportate dal modello non sono mai compiute e realistiche ma, piuttosto, solo in linea di principio e romanzesche. Queste difficoltà potrebbero essere superate ricorrendo ai modelli Galileiani , costituiti da sistemi dinamici in cui ciascuna componente ha un’interpretazione precisa e definita, in quanto essa corrisponde ad una proprietà misurabile (grandezza) del fenomeno reale che il modello descrive. (shrink)

Typical puzzles for de se attitudes by Perry and Lewis are laid out and contrasted with the original version of Jackson's Knowledge Argument. It is argued, from an epistemic perspective, that de se attitudes can be explained by looking at the way internal/introspective knowledge is formed without resorting to acquaintance or making assumptions about the Mind/Body problem.

This essay shows the presence of transcendence in the on-going attempt to come up with a purely scientific account of the workings of the human mind. At the center of the developmental stages of this attempt is the computational theory of mind, which regards the human mind as some kind of computer. With Wittgenstein’s analysis of the limits of linguistic representation in the Tractatus as a framework, it is argued that the various difficulties encountered by this attempt are primarily due (...) to the transcendental nature of the human mind, which eludes scientific explanation. (shrink)

In this paper we analyze methodological and philosophical implications of algorithmic aspects of unconventional computation. At first, we describe how the classical algorithmic universe developed and analyze why it became closed in the conventional approach to computation. Then we explain how new models of algorithms turned the classical closed algorithmic universe into the open world of algorithmic constellations, allowing higher flexibility and expressive power, supporting constructivism and creativity in mathematical modeling. As Goedels undecidability theorems demonstrate, the closed algorithmic universe restricts (...) essential forms of mathematical cognition. In contrast, the open algorithmic universe, and even more the open world of algorithmic constellations, remove such restrictions and enable new, richer understanding of computation. (shrink)

The thesis develops solutions to two main problems for mental realism. Mental realism is the theory that mental properties, events, and objects exist, with their own set of characters and causal powers. The first problem comes from the philosophy of science, where Psillos proposes a notion of scientific realism that contradicts mental realism, and consequently, if one is to be a scientific realist in the way Psillos recommends, one must reject mental realism. I propose adaptations to the conception of scientific (...) realism to make it compatible with mental realism. In the process, the thesis defends computational cognitive science from a compelling argument Searle can be seen to endorse but has not put forth in an organized logical manner. A new conception of scientific realism emerges out of this inquiry, integrating the mental into the rest of nature. The second problem for mental realism arises out of non-reductive physicalism- the view that higher-level properties, and in particular mental properties, are irreducible, physically realized, and that physical properties are sufficient non-overdetermining causes of any effect. Kim’s Problem of Causal Exclusion aims to show that the mental, if unreduced, does no causal work. Consequently, given that we should not believe in the existence of properties that do not participate in causation, we would be forced to drop mental realism. A solution is needed. The thesis examines various positions relevant to the debate. Several doctrines of physicalism are explored, rejected, and one is proposed; the thesis shows the way in which Kim’s reductionist position has been constantly inconsistent throughout the years of debate; the thesis argues that trope theory does not compete with a universalist conception of properties to provide a solution; and shows weakness in the Macdonald’s non-reductive monist position and Pereboom’s constitutional coincidence account of mental causation. The thesis suggests that either the premises of Kim’s argument are consistent, and consequently his reductio is logically invalid, or at least one of the premises is false, and therefore the argument is not sound. Consequently, the Problem of Causal Exclusion that Kim claims emerges out of non-reductive physicalism does not force us to reject mental realism. Mental realism lives on. (shrink)

This paper presents a novel theory of what it is that makes vision a representational affair. Vision is a process of representation; a fact that does not depend on it being "contentfull" or "indirect". Even if it turns out that vision is direct and/or intrinsically "contentless", it is nevertheless defined by features that decisively make it count as a process or representation. The phenomenology of vision is key here: as we see, we are directly presented with aspects of the environment (...) that are at various distances away from us. Through the process of vision, aspects of the environment that would otherwise still be unavailable or “absent”, are made (quasi-)available, or (quasi-)present. This already by itself makes vision deserving of the name ‘representational’, even if those distant aspects of the world are presented to us directly and contentless. In part I, I provide a bit of an overview of the relevant theoretical landscape, and I give my own take on how we may frame and approach some of the issues with respect to mental representation. Then, in part II, I argue that the representational features of vision must primarily be sought at the level of conscious experience. In part III, I elaborate on the two most common theories that are associated with the view that vision is ‘representational’, and proceed to show that there is in fact a third, more direct, way in which vision can be considered as essentially a process of representation. Finally, in part IV, I show that the kind of interaction problems that arise with the more traditional notions of representation also arise with this newer, more direct, notion. (shrink)

Variable quality essays dominated by reductionist nonsense. This is a followup to Hofstadter´s famous Godel, Escher, Bach (1980). Like its predecessor, it is concerned largely with the foundations of artificial intelligence, but it is composed mostly of stories, essays and extracts from a wide range of people, with a few essays by DH and DD and comments to all of the contributions by one or the other of them. For my views on the attempts of D and H to understand (...) behaviour see my review of D's " I am a Strange Loop. " Much of it is very reductionistic in tone (ie, " explains " everything in terms of physics/math and denies " reality " of psychology) but as Hofstadter notes, the quantum field equations of a water molecule are too complex to solve (and so is a vacuum)and nobody has a clue about how to explain the way properties emerge(eg, water properties from H2 and 02) as you go up the scale from the vacuum to the brain, so reductionism, like holism, requires a great deal of faith and in fact is incoherent as one cannot even frame it's arguments without presupposing the coherence of higher order thought. Additional problems for reductionism are the uncertainty principle, chaos (eg, no way to predict how a pile of sand will fall) and the logically necessary incompleteness of math (and all thought). In sum, though there are many interesting comments, like nearly all writing on behavior this work lacks any coherent account of the logical structure of rationality which I give in my more recent writings. -/- Those wishing a comprehensive up to date account of Wittgenstein, Searle and their analysis of behavior from the modern two systems view may consult my article The Logical Structure of Philosophy, Psychology, Mind and Language as Revealed in Wittgenstein and Searle (2016). Those interested in all my writings in their most recent versions may download from this site my e-book ‘Philosophy, Human Nature and the Collapse of Civilization Michael Starks (2016)- Articles and Reviews 2006-2016’ by Michael Starks First Ed. 662p (2016). -/- All of my papers and books have now been published in revised versions both in ebooks and in printed books. -/- Talking Monkeys: Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet - Articles and Reviews 2006-2017 (2017) https://www.amazon.com/dp/B071HVC7YP. -/- The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle--Articles and Reviews 2006-2016 (2017) https://www.amazon.com/dp/B071P1RP1B. -/- Suicidal Utopian Delusions in the 21st century: Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2017 (2017) https://www.amazon.com/dp/B0711R5LGX . (shrink)

This is merely the longish abstract of a talk I gave in 2001, that now seems to make more sense than ever.

Neuroscience investigates how neuronal processing circuits work, but it has problems explaining experiences this way. For example, it hasn’t explained how colour and shape circuits bind together in visual processing, nor why colours and other qualia are experienced so differently yet processed by circuits so similarly, nor how to get from processing circuits to pictorial images spread across inner space. Some theorists turn from these circuits to their electromagnetic fields to deal with such difficulties concerning the mind’s qualia, unity, privacy, (...) and causality. They include Kohler, Libet, Popper, Lindahl, Arhem, Charman, Pockett, John, McFadden, Fingelkurts, Maxwell, and Jones. They’re classifiable as computationalist, reductionist, dualist, realist, interactionist, epiphenomenalist, globalist, and localist. However, they’ve never been analysed together as a whole, which hinders evaluations of them. This article tries to rectify this. It concludes that while field theories face challenges, they aren’t easily dismissed, for they draw on considerable evidence and may avoid serious problems in neuroscience concerning the mind’s qualia, unity, causality, and ontology. (shrink)

Is the mathematical function being computed by a given physical system determined by the system’s dynamics? This question is at the heart of the indeterminacy of computation phenomenon (Fresco et al. [unpublished]). A paradigmatic example is a conventional electrical AND-gate that is often said to compute conjunction, but it can just as well be used to compute disjunction. Despite the pervasiveness of this phenomenon in physical computational systems, it has been discussed in the philosophical literature only indirectly, mostly with reference (...) to the debate over realism about physical computation and computationalism. A welcome exception is Dewhurst’s ([2018]) recent analysis of computational individuation under the mechanistic framework. He rejects the idea of appealing to semantic properties for determining the computational identity of a physical system. But Dewhurst seems to be too quick to pay the price of giving up the notion of computational equivalence. We aim to show that the mechanist need not pay this price. The mechanistic framework can, in principle, preserve the idea of computational equivalence even between two different enough kinds of physical systems, say, electrical and hydraulic ones. (shrink)

Advocates of dynamic systems have suggested that higher mental processes are based on continuous representations. In order to evaluate this claim, we first define the concept of representation, and rigorously distinguish between discrete representations and continuous representations. We also explore two important bases of representational content. Then, we present seven arguments that discrete representations are necessary for any system that must discriminate between two or more states. It follows that higher mental processes require discrete representations. We also argue that discrete (...) representations are more influenced by conceptual role than continuous representations. We end by arguing that the presence of discrete representations in cognitive systems entails that computationalism (i.e., the view that the mind is a computational device) is true, and that cognitive science should embrace representational pluralism. (shrink)

The journal of Cognitive Computation is defined in part by the notion that biologically inspired computational accounts are at the heart of cognitive processes in both natural and artificial systems. Many studies of various important aspects of cognition (memory, observational learning, decision making, reward prediction learning, attention control, etc.) have been made by modelling the various experimental results using ever-more sophisticated computer programs. In this manner progressive inroads have been made into gaining a better understanding of the many components of (...) cognition. Concomitantly in both science and science fiction the hope is periodically re-ignited that a manmade system can be engineered to be fully cognitive and conscious purely in virtue of its execution of an appropriate computer program. However, whilst the usefulness of the computational metaphor in many areas of psychology and neuroscience is clear, it has not gone unchallenged and in this article I will review a group of philosophical arguments that suggest either such unequivocal optimism in computationalism is misplaced—computation is neither necessary nor sufficient for cognition—or panpsychism (the belief that the physical universe is fundamentally composed of elements each of which is conscious) is true. I conclude by highlighting an alternative metaphor for cognitive processes based on communication and interaction. (shrink)

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)

Good sciences have good metaphors. Indeed, good sciences are good because they have good metaphors. AI could use more good metaphors. In this editorial, I would like to propose a new metaphor to help us understand intelligence. Of course, whether the metaphor is any good or not depends on whether it actually does help us. (What I am going to propose is not something opposed to computationalism -- the hypothesis that cognition is computation. Noncomputational metaphors are in vogue these (...) days, and to date they have all been equally plausible and equally successful. And, just to be explicit, I do not mean “IQ” by “intelligence.” I am using “intelligence” in the way AI uses it: as a semi-techical term referring to a general property of all intelligent systems, animal (including humans), or machine, alike.). (shrink)

We again press the case for computationalism by considering the latest in ill- conceived attacks on this foundational idea. We briefly but clearly define and delimit computationalism and then consider three authors from a new anti- computationalist collection.

The new kid on the block in cognitive science these days is dynamic systems. This way of thinking about the mind is, as usual, radically opposed to computationalism - - the hypothesis that thinking is computing. The use of dynamic systems is just the latest in a series of attempts, from Searle's Chinese Room Argument, through the weirdnesses of postmodernism, to overthrown computationalism, which as we all know is a perfectly nice hypothesis about the mind that never hurt (...) anyone. (shrink)

Without a proper restriction on mappings, virtually any system could be seen as implementing any computation. That would not allow characterization of systems in terms of implemented computations and is not compatible with a computationalist philosophy of mind. Information-based criteria for independence of substates within structured states are proposed as a solution. Objections to the use of requirements for transitions in counterfactual states are addressed, in part using the partial-brain argument as a general counterargument to neural replacement arguments.