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  1. Wide computationalism revisited: distributed mechanisms, parismony and testability.Luke Kersten - 2024 - Philosophical Explorations 27 (2):1-18.
    Recent years have seen a surge of interest in applying mechanistic thinking to computational accounts of implementation and individuation. One recent extension of this work involves so-called ‘wide’ approaches to computation, the view that computational processes spread out beyond the boundaries of the individual. These ‘mechanistic accounts of wide computation’ maintain that computational processes are wide in virtue of being part of mechanisms that extend beyond the boundary of the individual. This paper aims to further develop the mechanistic account of (...)
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  2. Theorizing the multitude before Machiavelli. Marsilius of Padua between Aristotle and Ibn Rushd.Alessandro Mulieri - 2023 - European Journal of Political Theory 22 (4):542-564.
    Even if political theorists rarely read him, Italian political thinker, Marsilius of Padua, presents one of the most radical theories of the multitude prior to Machiavelli and Spinoza. This article reconstructs Marsilius of Padua's political theory of the multitude in his Defender of Peace and pays special attention to two main sources from which Marsilius frames his theory: Aristotle and Ibn Rushd. Compared to Aristotle, Marsilius advances a more epistemic view of the multitude as a lawmaker. Marsilius’ ideas on the (...)
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  3. The Great Philoosphical Objections to AI: The History and Legacy of the AI Wars.Eric Dietrich, Chris Fields, John P. Sullins, Van Heuveln Bram & Robin Zebrowski - 2021 - London: Bloomsbury Academic.
    This book surveys and examines the most famous philosophical arguments against building a machine with human-level intelligence. From claims and counter-claims about the ability to implement consciousness, rationality, and meaning, to arguments about cognitive architecture, the book presents a vivid history of the clash between the philosophy and AI. Tellingly, the AI Wars are mostly quiet now. Explaining this crucial fact opens new paths to understanding the current resurgence AI (especially, deep learning AI and robotics), what happens when philosophy meets (...)
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  4. O "Frame Problem": a sensibilidade ao contexto como um desafio para teorias representacionais da mente.Carlos Barth - 2019 - Dissertation, Federal University of Minas Gerais
    Context sensitivity is one of the distinctive marks of human intelligence. Understanding the flexible way in which humans think and act in a potentially infinite number of circumstances, even though they’re only finite and limited beings, is a central challenge for the philosophy of mind and cognitive science, particularly in the case of those using representational theories. In this work, the frame problem, that is, the challenge of explaining how human cognition efficiently acknowledges what is relevant from what is not (...)
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  5. Computing machines, body and mind: metaphorical origins of mechanistic computationalism.П. Н Барышников - 2023 - Philosophical Problems of IT and Cyberspace (PhilIT&C) 1:4-13.
    The article presents preliminary results of the conceptual analysis of the mechanistic profile of the computer metaphor. Mechanic reductionism is a special direction of computer metaphor rooted in various historical forms of word usage. Here we trace the stages of formation of the principles of transferring the properties of a mechanical computer to the properties of the human body and mind. We are also trying to identify the basic principles of semantic transfer, which have survived to this day in the (...)
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  6. On Computationalism: Formal Interpretation and Initial Model.Mohamad Awwad - 2023 - Bulletin of Taras Shevchenko National University of Kyiv Philosophy 1 (8):5-8.
    In this article, we propose an initial formal model of computationalism based on mathematical relations between cognition and computation. More specifically, based on a set of cognitive constituents as a domain, and a set of computational implementations as a range, we define two relations of transformation over these sets. Moreover, we define the principles of implementability, describability, and phenomena correspondence, and we conjecture that full computationalism does not hold since these principles are not fulfilled. Particularly, many cognitively-tied phenomena fail to (...)
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  7. ¿What is Artificial Intelligence?Fabio Morandín-Ahuerma - 2022 - Int. J. Res. Publ. Rev 3 (12):1947-1951.
    La inteligencia artificial (IA) es la capacidad de una máquina o sistema informático para simular y realizar tareas que normalmente requerirían inteligencia humana, como el razonamiento lógico, el aprendizaje y la resolución de problemas. La inteligencia artificial se basa en el uso de algoritmos y tecnologías de aprendizaje automático para dar a las máquinas la capacidad de aplicar ciertas habilidades cognitivas y realizar tareas por sí mismas de manera autónoma o semiautónoma. La inteligencia artificial se distingue por su grado de (...)
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  8. John Haugeland, ed., Mind Design II: Philosophy, Psychology, and Artificial Intelligence[REVIEW]Varol Akman - 1998 - ACM SIGART Bulletin 9 (3-4):33-36.
    This is a review of Mind Design II: Philosophy, Psychology, and Artificial Intelligence, edited by John Haugeland and published by The MIT Press in 1997.
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  9. Phenomenology as Proto-Computationalism: Do the Prolegomena Indicate a Computational Reading of the Logical Investigations?Jesse D. Lopes - 2023 - Husserl Studies 39 (1):47-68.
    This essay examines the possibility that phenomenological laws might be implemented by a computational mechanism by carefully analyzing key passages from the Prolegomena to Pure Logic. Part I examines the famous Denkmaschine passage as evidence for the view that intuitions of evidence are causally produced by computational means. Part II connects the less famous criticism of Avenarius & Mach on thought-economy with Husserl's 1891 essay 'On the Logic of Signs (Semiotic).' Husserl is shown to reaffirm his earlier opposition to associationist (...)
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  10. Two Roadblocks of Computationalism.Napoleon Mabaquiao - 2019 - Philosophia: International Journal of Philosophy (Philippine e-journal) 20 (2):163-179.
    With its use of the powerful technology of computer, the computational theory of mind or computationalism, which regards minds as computational systems, has been widely hailed as the most promising theory that will carry out the project of explaining the workings of the mind in purely scientific terms. While it continues to serve as the primary framework for scientifically inclined theorizing and investigations about the nature of minds, especially in the area of cognitive science, it, however, continues to face strong (...)
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  11. Platon et Aristotle a Paris.Jacques Chomarat - 1974 - Moreana 11 (2):49-56.
  12. Aristotle in Africa-Towards a Comparative Africanist reading of the South African Truth and Reconciliation Commission.Wim van Binsbergen - 2002 - Quest - and African Journal of Philosophy 16 (1-2):238-272.
  13. Extended Computation: Wide Computationalism in Reverse.Paul Smart, Wendy Hall & Michael Boniface - 2021 - Proceedings of the 13th ACM Web Science Conference (Companion Volume).
    Arguments for extended cognition and the extended mind are typically directed at human-centred forms of cognitive extension—forms of cognitive extension in which the cognitive/mental states/processes of a given human individual are subject to a form of extended or wide realization. The same is true of debates and discussions pertaining to the possibility of Web-extended minds and Internet-based forms of cognitive extension. In this case, the focus of attention concerns the extent to which the informational and technological elements of the online (...)
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  14. Insights in How Computer Science can be a Science.Robert W. P. Luk - 2020 - Science and Philosophy 8 (2):17-46.
    Recently, information retrieval is shown to be a science by mapping information retrieval scientific study to scientific study abstracted from physics. The exercise was rather tedious and lengthy. Instead of dealing with the nitty gritty, this paper looks at the insights into how computer science can be made into a science by using that methodology. That is by mapping computer science scientific study to the scientific study abstracted from physics. To show the mapping between computer science and physics, we need (...)
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  15. Empathy and Instrumentalization: Late Ancient Cultural Critique and the Challenge of Apparently Personal Robots.Jordan Joseph Wales - 2020 - In Marco Norskov, Johanna Seibt & Oliver S. Quick (eds.), Culturally Sustainable Social Robotics: Proceedings of Robophilosophy 2020. pp. 114-124.
    According to a tradition that we hold variously today, the relational person lives most personally in affective and cognitive empathy, whereby we enter subjective communion with another person. Near future social AIs, including social robots, will give us this experience without possessing any subjectivity of their own. They will also be consumer products, designed to be subservient instruments of their users’ satisfaction. This would seem inevitable. Yet we cannot live as personal when caught between instrumentalizing apparent persons (slaveholding) or numbly (...)
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  16. Neural Computation of Surface Border Ownership and Relative Surface Depth from Ambiguous Contrast Inputs.Birgitta Dresp-Langley & Stephen Grossberg - 2016 - Frontiers in Psychology 7.
    The segregation of image parts into foreground and background is an important aspect of the neural computation of 3D scene perception. To achieve such segregation, the brain needs information about border ownership; that is, the belongingness of a contour to a specific surface represented in the image. This article presents psychophysical data derived from 3D percepts of figure and ground that were generated by presenting 2D images composed of spatially disjoint shapes that pointed inward or outward relative to the continuous (...)
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  17. Finita la commedia.Andrej Poleev - 2020 - Enzymes 18.
    Искусственный интеллект – последняя, хотя и иллюзорная надежда продажных и провалившихся режимов как на Западе, так и на Востоке остаться на плаву: ведь тонущий хватается и за соломинку. Но всё течёт и всё изменяется, и никаким деспотиям и деспотам не удастся остановить ход истории, как бы они этого не желали и тому не противились. Хотя у истории нет конца, но их история и история совершённых ими предательств уже закончилась. Plaudite, cives, plaudite, amici, finita est comoedia: „Рукоплещите, граждане, друзья, комедия окончена.“.
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  18. Artificial Intelligence: Philosophical and Epistemological Perspectives.Pierre Livet & Franck Varenne - 2020 - In P. Marquis, H. Parde & O. Papini (eds.), A Guided Tour of Artificial Intelligence Research: Volume I: Knowledge Representation, Reasoning and Learning. Springer. pp. 437-455.
    Research in artificial intelligence (AI) has led to revise the challenges of the AI initial programme as well as to keep us alert to peculiarities and limitations of human cognition. Both are linked, as a careful further reading of the Turing’s test makes it clear from Searle’s Chinese room apologue and from Dreyfus’ suggestions, and in both cases, ideal had to be turned into operating mode. In order to rise these more pragmatic challenges AI does not hesitate to link together (...)
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  19. Philosophy.Robert A. Wilson - 1999 - In Robert A. Wilson & Frank C. Keil (eds.), MIT Encyclopedia of the Cognitive Sciences. Cambridge, MA, USA:
  20. Autômatos, Androides e Bergson ou A percepção e a Extensão em seres artificiais da Ficção: Um olhar Bergsoniano.Sandro Rinaldi Feliciano - 2016 - Dissertation, Universidade Federal Do Abc
    Androides são "autômatos com forma humana" . Enquanto robôs são "aparelhos automáticos capazes de manipular objetos ou executar operações segundo um programa". Assim podemos dizer que um androide pode ser considerado um robô, mas nem todo robô é um androide. Devido à diversidade de gêneros, foi criado o termo ginóide, separando-se assim os androides de aparência masculina (andros) da feminina (ginos). A propagação destes se deu à ficção cientifica, em livros de Isaac Asimov, em seriados para televisão como Jornada nas (...)
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  21. The Routledge Handbook of the Computational Mind.Mark Sprevak & Matteo Colombo (eds.) - 2018 - Routledge.
    Computational approaches dominate contemporary cognitive science, promising a unified, scientific explanation of how the mind works. However, computational approaches raise major philosophical and scientific questions. In what sense is the mind computational? How do computational approaches explain perception, learning, and decision making? What kinds of challenges should computational approaches overcome to advance our understanding of mind, brain, and behaviour? The Routledge Handbook of the Computational Mind is an outstanding overview and exploration of these issues and the first philosophical collection of (...)
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  22. Physical Computation: A Mechanistic Account, by Gualtiero Piccinini: Oxford: Oxford University Press, 2015, pp. ix + 343, £35. [REVIEW]Nir Fresco - 2017 - Australasian Journal of Philosophy 95 (3):625-626.
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  23. Physical Computation and Cognitive Science, by Nir Fresco: Heidelberg: Springer, 2014, pp. xxii + 229, 99,99€. [REVIEW]Gordana Dodig-Crnkovic - 2016 - Australasian Journal of Philosophy 94 (2):396-399.
    This is review of the book "Physical Computation and Cognitive Science" by Nir Fresco: http://www.springer.com/la/book/9783642413742.
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  24. Using computational models to discover and understand mechanisms.William Bechtel - 2016 - Studies in History and Philosophy of Science Part A 56:113-121.
  25. Emergence, Computation and the Freedom Degree Loss Information Principle in Complex Systems.Ignazio Licata & Gianfranco Minati - 2017 - Foundations of Science 22 (4):863-881.
    We consider processes of emergence within the conceptual framework of the Information Loss principle and the concepts of systems conserving information; systems compressing information; and systems amplifying information. We deal with the supposed incompatibility between emergence and computability tout-court. We distinguish between computational emergence, when computation acquires properties, and emergent computation, when computation emerges as a property. The focus is on emergence processes occurring within computational processes. Violations of Turing-computability such as non-explicitness and incompleteness are intended to represent partially the (...)
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  26. Social Autonomy and Heteronomy in the Age of ICT: The Digital Pharmakon and the (Dis)Empowerment of the General Intellect.Pieter Lemmens - 2017 - Foundations of Science 22 (2):287-296.
    ‘The art of living with ICTs ’ today not only means finding new ways to cope, interact and create new lifestyles on the basis of the new digital technologies individually, as ‘consumer-citizens’. It also means inventing new modes of living, producing and, not in the least place, struggling collectively, as workers and producers. As the so-called digital revolution unfolds in the context of a neoliberal cognitive and consumerist capitalism, its ‘innovations’ are predominantly employed to modulate and control both production processes (...)
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  27. Models and people: An alternative view of the emergent properties of computational models.Fabio Boschetti - 2016 - Complexity 21 (6):202-213.
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  28. Hypercomputation and the Physical Church‐Turing Thesis.Paolo Cotogno - 2003 - British Journal for the Philosophy of Science 54 (2):181-223.
    A version of the Church-Turing Thesis states that every effectively realizable physical system can be simulated by Turing Machines (‘Thesis P’). In this formulation the Thesis appears to be an empirical hypothesis, subject to physical falsification. We review the main approaches to computation beyond Turing definability (‘hypercomputation’): supertask, non-well-founded, analog, quantum, and retrocausal computation. The conclusions are that these models reduce to supertasks, i.e. infinite computation, and that even supertasks are no solution for recursive incomputability. This yields that the realization (...)
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  29. Mental Algorithms: Are Minds Computational Systems?James H. Fetzer - 1994 - Pragmatics and Cognition 2 (1):1-29.
    The idea that human thought requires the execution of mental algorithms provides a foundation for research programs in cognitive science, which are largely based upon the computational conception of language and mentality. Consideration is given to recent work by Penrose, Searle, and Cleland, who supply various grounds for disputing computationalism. These grounds in turn qualify as reasons for preferring a non-computational, semiotic approach, which can account for them as predictable manifestations of a more adquate conception. Thinking does not ordinarily require (...)
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  30. Searle's mind: Physical, irreducible, subjective, and non-computational.Amir Horowitz - 1994 - Pragmatics and Cognition 2 (1):207-220.
  31. Computational Tractability and Conceptual Coherence.Paul Thagard - 1993 - Canadian Journal of Philosophy 23 (3):349-363.
    According to Church’s thesis, we can identify the intuitive concept of effective computability with such well-defined mathematical concepts as Turing computability and partial recursiveness. The almost universal acceptance of Church’s thesis among logicians and computer scientists is puzzling from some epistemological perspectives, since no formal proof is possible of a thesis that involves an informal concept such as effectiveness. Elliott Mendelson has recently argued, however, that equivalencies between intuitive notions and precise notions need not always be considered unprovable theses, and (...)
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  32. Consciousness and the Computational Mind. [REVIEW]D. S. Clarke Jr - 1988 - Review of Metaphysics 42 (1):147-149.
    The term 'consciousness' has not been consistently used in the history of philosophy and psychology. It has been taken to stand for the mental activity in which all of us are engaged during our waking lives, whether absorbed in the solving of a task or in calm moments of contemplation. It has also been allied with the term 'introspection' to stand for a self-monitoring activity, one in which we are not simply engaged, but in which we aware of the succession (...)
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  33. A Philosophy of Computing? - The Case of Sociology and Computing.H. Robinson - 1993 - Journal of Intelligent Systems 3 (2-4):189-216.
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  34. Computational Models of Consciousness: An Evaluation.Ron Sun - 1999 - Journal of Intelligent Systems 9 (5-6):507-568.
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  35. Design and Implementation of SeTiA: Secure Multi Auction System II: Architecture and Implementation Issues.V. S. Borkar, M. S. Dave & R. K. Shyamasundar - 2005 - Journal of Intelligent Systems 14 (1):69-93.
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  36. Thinking Must Be Computation of the Right Kind.James H. Fetzer - 2000 - The Proceedings of the Twentieth World Congress of Philosophy 9:115-122.
    In this paper I argue for a computational theory of thinking that does not eliminate the mind. In doing so, I will defend computationalism against the arguments of John Searle and James Fetzer, and briefly respond to other common criticisms.
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  37. Informational Macrodynamics for Cognitive Information Modeling and Computation.Vladimir S. Lerner - 2001 - Journal of Intelligent Systems 11 (6):409-470.
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  38. Parallel Implementation of Backpropagation Algorithm.R. Szabo & M. Steinmetz - 1996 - Journal of Intelligent Systems 6 (3-4):261-278.
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  39. The Computational Notion of Life.Ciaus Emmeche - 1994 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 9 (2):1-30.
    The present paper discusses a topic often neglected by contemporary philosophy of biology: The relation between metaphorical notions of living organisms as information processing systems, the attempts to model such systems by computational means, and the idea that life itself is a computational phenomenon. This question has ramifications in theoretical biology and thedefinition of Iife, in theoretical computer science and the concept of computation, and in semiotics, and the concept of the interpreter. It is argued, that the theory of autopoietic (...)
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  40. Computation and Causation.Richard Scheines - 2002 - Metaphilosophy 33 (1‐2):158-180.
    The computer’s effect on our understanding of causation has been enormous. By the mid‐1980s, philosophical and social‐scientific work on the topic had left us with (1) no reasonable reductive account of causation and (2) a class of statistical causal models tied to linear regression. At this time, computer scientists were attacking the problem of equipping robots with models of the external that included probabilistic portrayals of uncertainty. To solve the problem of efficiently storing such knowledge, they introduced Bayes Networks and (...)
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  41. Mediation and metaxý: the interval between analog animality and digital humanity.Thomas Sutherland - 2016 - Ctrl-Z: New Media Philosophy 6.
    This article examines Plotinus’ conception of metaxý – the human as interval between animals and gods – and its resonances in the work of Jacques Lacan, who implicitly retains and reconfigures the notion of the human being as a mediator. Lacan replicates this ancient narrative, but does so within the context of a cyberneticism that replaces gods and angels with symbolic computation. Humanity, according to such a conception, is tacitly regarded not only as a mediator, but as that which is (...)
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  42. Gualtiero Piccinini: Physical Computation: A Mechanistic Account: Oxford University Press, Oxford, 2015, ix + 313, £35.00, ISBN 9780199658855.Matteo Colombo - 2016 - Minds and Machines 26 (3):307-312.
  43. The Importance of Learning History and Philosophy of Computing.Colin Price - unknown
    Computers have invaded our offices, our homes, cars and coffee-pots; they have become ubiquitous. However, the advance of computing technologies is associated with an increasing lack of “visibility” of the underlying software and hardware technologies. While we use and accept the computer, we neither know its history nor functionality. In this paper, we argue that this is not a healthy situation. Also, recruitment onto UK Computing degree courses is steadily falling; these courses are appearing less attractive to school-leavers. This may (...)
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  44. Experimental computation as an ontological game changer: the impact of modern mathematical computation tools on the ontology of mathematics.David H. Bailey & Jonathan M. Borwein - unknown
    Robust, concrete and abstract, mathematical computation and inference on the scale now becoming possible should change the discourse about many matters mathematical. These include: what mathematics is, how we know something, how we persuade each other, what suffices as a proof, the infinite, mathematical discovery or invention, and other such issues.
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  45. Computation in Non-Classical Foundations?Toby Meadows & Zach Weber - 2016 - Philosophers' Imprint 16.
    The Church-Turing Thesis is widely regarded as true, because of evidence that there is only one genuine notion of computation. By contrast, there are nowadays many different formal logics, and different corresponding foundational frameworks. Which ones can deliver a theory of computability? This question sets up a difficult challenge: the meanings of basic mathematical terms are not stable across frameworks. While it is easy to compare what different frameworks say, it is not so easy to compare what they mean. We (...)
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  46. Models of neural computation: an examination of David Chalmers’ causal theory of the mind.Dinyar Mistry - unknown
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  47. From Aristotle to John Searle and Back Again: Formal Causes, Teleology, and Computation in Nature.Edward Feser - 2016 - Nova et Vetera 14 (2):459-494.
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  48. What Computations (Still, Still) Can't Do: Jerry Fodor on Computation and Modularity.Robert A. Wilson - 2004 - Canadian Journal of Philosophy 34 (sup1):407-425.
    Fodor's thinking on modularity has been influential throughout a range of the areas studying cognition, chiefly as a prod for positive work on modularity and domain-specificity. In _The Mind Doesn't Work That Way_, Fodor has developed the dark message of _The Modularity of Mind_ regarding the limits to modularity and computational analyses. This paper offers a critical assessment of Fodor's scepticism with an eye to highlighting some broader issues in play, including the nature of computation and the role of recent (...)
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  49. Narrow Versus Wide Mechanism: Including a Re-Examination of Turing’s Views on the Mind-Machine Issue.B. Jack Copeland - 2000 - Journal of Philosophy 97 (1):5-32.
  50. Computation and Consciousness.Tim Maudlin - 1989 - Journal of Philosophy 86 (8):407.
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