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  1. 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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  2. THE ROBOTS ARE COMING: What’s Happening in Philosophy (WHiP)-The Philosophers, August 2022.Jeff Hawley - unknown
    Should we fear a future in which the already tricky world of academic publishing is increasingly crowded out by super-intelligent artificial general intelligence (AGI) systems writing papers on phenomenology and ethics? What are the chances that AGI advances to a stage where a human philosophy instructor is similarly removed from the equation? If Jobst Landgrebe and Barry Smith are correct, we have nothing to fear.
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  3. What’s Happening in Philosophy (WHiP)-The Philosophers, July 2022.Jeff Hawley - unknown
    Originally published in PhilosophyNews, July 19, 2022. -/- This new series, What’s Happening in Philosophy (WHiP)-The Philosophers aims to provide a monthly snapshot of various trends and discussions happening across the discipline. -/- In this inaugural post, we begin with a harrowing tale from David Edmonds involving the murder of the German philosopher Moritz Schlick. Schlick was a Vienna Circle guiding spirit and logical positivist thinker. Next up is Steven Nadler’s take on several biographies of the ‘father of modern philosophy’ (...)
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  4. The Kantian Notion of Freedom and Autonomy of Artificial Agency.Manas Sahu - 2021 - Prometeica - Revista De Filosofía Y Ciencias 23:136-149.
    The objective of this paper is to provide critical analysis of the Kantian notion of freedom ; its significance in the contemporary debate on free-will and determinism, and the possibility of autonomy of artificial agency in the Kantian paradigm of autonomy. Kant's resolution of the third antinomy by positing the ground in the noumenal self resolves the problem of antinomies; however, it invites an explanatory gap between phenomenality and the noumenal self; even if he has successfully established the compatibility of (...)
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  5. From Symbols to Knowledge Systems: A. Newell and H. A. Simon's Contribution to Symbolic AI.Luis M. Augusto - 2021 - Journal of Knowledge Structures and Systems 2 (1):29 - 62.
    A. Newell and H. A. Simon were two of the most influential scientists in the emerging field of artificial intelligence (AI) in the late 1950s through to the early 1990s. This paper reviews their crucial contribution to this field, namely to symbolic AI. This contribution was constituted mostly by their quest for the implementation of general intelligence and (commonsense) knowledge in artificial thinking or reasoning artifacts, a project they shared with many other scientists but that in their case was theoretically (...)
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  6. Saint Thomas d'Aquin contre les robots. Pistes pour une approche philosophique de l'Intelligence Artificielle.Matthieu Raffray - 2019 - Angelicum 4 (96):553-572.
    In light of the pervasive developments of new technologies, such as NBIC (Nanotechnology, biotechnology, information technology, and cognitive science), it is imperative to produce a coherent and deep reflexion on the human nature, on human intelligence and on the limit of both of them, in order to successfully respond to some technical argumentations that strive to depict humanity as a purely mechanical system. For this purpose, it is interesting to refer to the epistemology and metaphysics of Thomas Aquinas as a (...)
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  7. Can Artificial Intelligence Make Art?Elzė Sigutė Mikalonytė & Markus Kneer - 2022 - ACM Transactions on Human-Robot Interactions.
    In two experiments (total N=693) we explored whether people are willing to consider paintings made by AI-driven robots as art, and robots as artists. Across the two experiments, we manipulated three factors: (i) agent type (AI-driven robot v. human agent), (ii) behavior type (intentional creation of a painting v. accidental creation), and (iii) object type (abstract v. representational painting). We found that people judge robot paintings and human painting as art to roughly the same extent. However, people are much less (...)
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  8. Playing the Blame Game with Robots.Markus Kneer & Michael T. Stuart - 2021 - In Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction (HRI’21 Companion). New York, NY, USA:
    Recent research shows – somewhat astonishingly – that people are willing to ascribe moral blame to AI-driven systems when they cause harm [1]–[4]. In this paper, we explore the moral- psychological underpinnings of these findings. Our hypothesis was that the reason why people ascribe moral blame to AI systems is that they consider them capable of entertaining inculpating mental states (what is called mens rea in the law). To explore this hypothesis, we created a scenario in which an AI system (...)
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  9. Updating the Frame Problem for Artificial Intelligence Research.Lisa Miracchi - 2020 - Journal of Artificial Intelligence and Consciousness 7 (2):217-230.
    The Frame Problem is the problem of how one can design a machine to use information so as to behave competently, with respect to the kinds of tasks a genuinely intelligent agent can reliably, effectively perform. I will argue that the way the Frame Problem is standardly interpreted, and so the strategies considered for attempting to solve it, must be updated. We must replace overly simplistic and reductionist assumptions with more sophisticated and plausible ones. In particular, the standard interpretation assumes (...)
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  10. Blended Cognition.Jordi Vallverdú & Vincent C. Müller (eds.) - 2019 - Cham: Springer.
    The central concept of this edited volume is "blended cognition", the natural skill of human beings for combining constantly different heuristics during their several task-solving activities. Something that was sometimes observed like a problem as “bad reasoning”, is now the central key for the understanding of the richness, adaptability and creativity of human cognition. The topic of this book connects in a significant way with the disciplines of psychology, neurology, anthropology, philosophy, logics, engineering, logics, and AI. In a nutshell: understanding (...)
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  11. In 30 Schritten zum Mond? Zukünftiger Fortschritt in der KI.Vincent C. Müller - 2018 - Medienkorrespondenz 20 (05.10.2018):5-15.
    Die Entwicklungen in der Künstlichen Intelligenz (KI) sind spannend. Aber wohin geht die Reise? Ich stelle eine Analyse vor, der zufolge exponentielles Wachstum von Rechengeschwindigkeit und Daten die entscheidenden Faktoren im bisherigen Fortschritt waren. Im Folgenden erläutere ich, unter welchen Annahmen dieses Wachstum auch weiterhin Fortschritt ermöglichen wird: 1) Intelligenz ist eindimensional und messbar, 2) Kognitionswissenschaft wird für KI nicht benötigt, 3) Berechnung (computation) ist hinreichend für Kognition, 4) Gegenwärtige Techniken und Architektur sind ausreichend skalierbar, 5) Technological Readiness Levels (TRL) (...)
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  12. Philosophy and Theory of Artificial Intelligence 2017.Vincent C. Müller (ed.) - 2017 - Berlin: Springer.
    This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; (...)
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  13. Should Machines Be Tools or Tool-Users? Clarifying Motivations and Assumptions in the Quest for Superintelligence.Dan J. Bruiger - manuscript
    Much of the basic non-technical vocabulary of artificial intelligence is surprisingly ambiguous. Some key terms with unclear meanings include intelligence, embodiment, simulation, mind, consciousness, perception, value, goal, agent, knowledge, belief, optimality, friendliness, containment, machine and thinking. Much of this vocabulary is naively borrowed from the realm of conscious human experience to apply to a theoretical notion of “mind-in-general” based on computation. However, if there is indeed a threshold between mechanical tool and autonomous agent (and a tipping point for singularity), projecting (...)
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  14. Computability and Human Symbolic Output.Jason Megill & Tim Melvin - 2014 - Logic and Logical Philosophy 23 (4):391-401.
    This paper concerns “human symbolic output,” or strings of characters produced by humans in our various symbolic systems; e.g., sentences in a natural language, mathematical propositions, and so on. One can form a set that consists of all of the strings of characters that have been produced by at least one human up to any given moment in human history. We argue that at any particular moment in human history, even at moments in the distant future, this set is finite. (...)
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  15. Genes, Affect, and Reason: Why Autonomous Robot Intelligence Will Be Nothing Like Human Intelligence.Henry Moss - 2016 - Techné: Research in Philosophy and Technology 20 (1):1-15.
    Abstract: Many believe that, in addition to cognitive capacities, autonomous robots need something similar to affect. As in humans, affect, including specific emotions, would filter robot experience based on a set of goals, values, and interests. This narrows behavioral options and avoids combinatorial explosion or regress problems that challenge purely cognitive assessments in a continuously changing experiential field. Adding human-like affect to robots is not straightforward, however. Affect in organisms is an aspect of evolved biological systems, from the taxes of (...)
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  16. Future Progress in Artificial Intelligence: A Poll Among Experts.Vincent C. Müller & Nick Bostrom - 2014 - AI Matters 1 (1):9-11.
    [This is the short version of: Müller, Vincent C. and Bostrom, Nick (forthcoming 2016), ‘Future progress in artificial intelligence: A survey of expert opinion’, in Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library 377; Berlin: Springer).] - - - In some quarters, there is intense concern about high–level machine intelligence and superintelligent AI coming up in a few dec- ades, bringing with it significant risks for human- ity; in other quarters, these issues are ignored or considered science (...)
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  17. Future Progress in Artificial Intelligence: A Survey of Expert Opinion.Vincent C. Müller & Nick Bostrom - 2016 - In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence. Springer. pp. 553-571.
    There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. We thus (...)
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  18. Challenges for Artificial Cognitive Systems.Antoni Gomila & Vincent C. Müller - 2012 - Journal of Cognitive Science 13 (4):452-469.
    The declared goal of this paper is to fill this gap: “... cognitive systems research needs questions or challenges that define progress. The challenges are not (yet more) predictions of the future, but a guideline to what are the aims and what would constitute progress.” – the quotation being from the project description of EUCogII, the project for the European Network for Cognitive Systems within which this formulation of the ‘challenges’ was originally developed (http://www.eucognition.org). So, we stick out our neck (...)
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  19. Philosophy and Theory of Artificial Intelligence, 3–4 October (Report on PT-AI 2011).Vincent C. Müller - 2011 - The Reasoner 5 (11):192-193.
    Report for "The Reasoner" on the conference "Philosophy and Theory of Artificial Intelligence", 3 & 4 October 2011, Thessaloniki, Anatolia College/ACT, http://www.pt-ai.org. --- Organization: Vincent C. Müller, Professor of Philosophy at ACT & James Martin Fellow, Oxford http://www.sophia.de --- Sponsors: EUCogII, Oxford-FutureTech, AAAI, ACM-SIGART, IACAP, ECCAI.
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  20. How Do We Read a Dictionary (as Machines and as Humans)? Kinds of Information in Dictionaries Constructed and Reconstructed.Vincent C. Müller - 2000 - In Evangelos Dermatas (ed.), Proceedings of COMLEX2000: Computational lexicography. Patras University Press. pp. 141-144.
    Two large lexicological projects for the Center for the Greek Language, Thessaloniki, were to be published in print and on the WWW, which meant that two conversions were needed: a near-database file had to be converted to fully formatted file for printing and a fully formatted file had to be converted to a database for WWW access. As it turned out, both conversions could make use of existing clues that indicated the kinds of information contained in each particular piece of (...)
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  21. Fundamental Issues of Artificial Intelligence.Vincent C. Müller (ed.) - 2016 - Springer.
    [Müller, Vincent C. (ed.), (2016), Fundamental issues of artificial intelligence (Synthese Library, 377; Berlin: Springer). 570 pp.] -- This volume offers a look at the fundamental issues of present and future AI, especially from cognitive science, computer science, neuroscience and philosophy. This work examines the conditions for artificial intelligence, how these relate to the conditions for intelligence in humans and other natural agents, as well as ethical and societal problems that artificial intelligence raises or will raise. The key issues this (...)
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  22. Mind and Machine.Cathal O’Madagain - 2014 - International Journal of Philosophical Studies 22 (2):291-295.
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  23. Philosophy and Theory of Artificial Intelligence.Vincent Müller (ed.) - 2013 - Springer.
    [Müller, Vincent C. (ed.), (2013), Philosophy and theory of artificial intelligence (SAPERE, 5; Berlin: Springer). 429 pp. ] --- Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This (...)
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  24. Is There a Future for AI Without Representation?Vincent C. Müller - 2007 - Minds and Machines 17 (1):101-115.
    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 (...)
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  25. Margaret A. Boden, Mind as Machine: A History of Cognitive Science , 2 Vols. [REVIEW]Vincent C. Müller - 2008 - Minds and Machines 18 (1):121-125.
    Review of: Margaret A. Boden, Mind as Machine: A History of Cognitive Science, 2 vols, Oxford: Oxford University Press, 2006, xlvii+1631, cloth $225, ISBN 0-19-924144-9. - Mind as Machine is Margaret Boden’s opus magnum. For one thing, it comes in two massive volumes of nearly 1700 pages, ... But it is not just the opus magnum in simple terms of size, but also a truly crowning achievement of half a century’s career in cognitive science.
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  26. Minds and Machines.Hilary Putnam - 1960 - In Sidney Hook (ed.), Dimensions of Minds. New York, USA: New York University Press. pp. 138-164.
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  27. Understanding Understanding: Syntactic Semantics and Computational Cognition.William J. Rapaport - 1995 - Philosophical Perspectives 9:49-88.
    John Searle once said: "The Chinese room shows what we knew all along: syntax by itself is not sufficient for semantics. (Does anyone actually deny this point, I mean straight out? Is anyone actually willing to say, straight out, that they think that syntax, in the sense of formal symbols, is really the same as semantic content, in the sense of meanings, thought contents, understanding, etc.?)." I say: "Yes". Stuart C. Shapiro has said: "Does that make any sense? Yes: Everything (...)
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The Turing Test
  1. Techno-Animism and the Pygmalion Effect.Emanuele Arielli & Lev Manovich - forthcoming - Http://Manovich.Net/Index.Php/Projects/Artificial-Aesthetics.
    Chapter 3 of the ongoing publication "Artificial Aesthetics" Book information: Assume you're a designer, an architect, a photographer, a videographer, a curator, an art historian, a musician, a writer, an artist, or any other creative professional or student. Perhaps you're a digital content creator who works across multiple platforms. Alternatively, you could be an art historian, curator, or museum professional. -/- You may be wondering how AI will affect your professional area in general and your work and career. Our book (...)
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  2. On Being a Lonely Brain-in-a-Vat: Structuralism, Solipsism, and the Threat From External World Skepticism.Grace Helton - forthcoming - Analytic Philosophy.
    David Chalmers has recently developed a novel strategy of refuting external world skepticism, one he dubs the structuralist solution. In this paper, I make three primary claims: First, structuralism does not vindicate knowledge of other minds, even if it is combined with a functionalist approach to the metaphysics of minds. Second, because structuralism does not vindicate knowledge of other minds, the structuralist solution vindicates far less worldly knowledge than we would hope for from a solution to skepticism. Third, these results (...)
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  3. The Mandatory Ontology of Robot Responsibility.Marc Champagne - 2021 - Cambridge Quarterly of Healthcare Ethics 30 (3):448–454.
    Do we suddenly become justified in treating robots like humans by positing new notions like “artificial moral agency” and “artificial moral responsibility”? I answer no. Or, to be more precise, I argue that such notions may become philosophically acceptable only after crucial metaphysical issues have been addressed. My main claim, in sum, is that “artificial moral responsibility” betokens moral responsibility to the same degree that a “fake orgasm” betokens an orgasm.
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  4. Can Machines Think? The Controversy That Led to the Turing Test.Bernardo Gonçalves - forthcoming - AI and Society:1-11.
    Turing’s much debated test has turned 70 and is still fairly controversial. His 1950 paper is seen as a complex and multilayered text, and key questions about it remain largely unanswered. Why did Turing select learning from experience as the best approach to achieve machine intelligence? Why did he spend several years working with chess playing as a task to illustrate and test for machine intelligence only to trade it out for conversational question-answering in 1950? Why did Turing refer to (...)
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  5. Computing Machinery and Sexual Difference: The Sexed Presuppositions Underlying the Turing Test.Amy Kind - forthcoming - In Jennifer McWeeny & Keya Maitra (eds.), Feminist Philosophy of Mind.
    In his 1950 paper “Computing Machinery and Intelligence,” Alan Turing proposed that we can determine whether a machine thinks by considering whether it can win at a simple imitation game. A neutral questioner communicates with two different systems – one a machine and a human being – without knowing which is which. If after some reasonable amount of time the machine is able to fool the questioner into identifying it as the human, the machine wins the game, and we should (...)
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  6. Levels of Abstraction and the Turing Test.Luciano Floridi - 2010 - Kybernetes 39 (3):423-440.
    An important lesson that philosophy can learn from the Turing Test and computer science more generally concerns the careful use of the method of Levels of Abstraction (LoA). In this paper, the method is first briefly summarised. The constituents of the method are “observables”, collected together and moderated by predicates restraining their “behaviour”. The resulting collection of sets of observables is called a “gradient of abstractions” and it formalises the minimum consistency conditions that the chosen abstractions must satisfy. Two useful (...)
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  7. AI-Completeness: Using Deep Learning to Eliminate the Human Factor.Kristina Šekrst - 2020 - In Sandro Skansi (ed.), Guide to Deep Learning Basics. Springer. pp. 117-130.
    Computational complexity is a discipline of computer science and mathematics which classifies computational problems depending on their inherent difficulty, i.e. categorizes algorithms according to their performance, and relates these classes to each other. P problems are a class of computational problems that can be solved in polynomial time using a deterministic Turing machine while solutions to NP problems can be verified in polynomial time, but we still do not know whether they can be solved in polynomial time as well. A (...)
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  8. Susan Schneider's Proposed Tests for AI Consciousness: Promising but Flawed.D. B. Udell & Eric Schwitzgebel - 2021 - Journal of Consciousness Studies 28 (5-6):121-144.
    Susan Schneider (2019) has proposed two new tests for consciousness in AI (artificial intelligence) systems, the AI Consciousness Test and the Chip Test. On their face, the two tests seem to have the virtue of proving satisfactory to a wide range of consciousness theorists holding divergent theoretical positions, rather than narrowly relying on the truth of any particular theory of consciousness. Unfortunately, both tests are undermined in having an ‘audience problem’: Those theorists with the kind of architectural worries that motivate (...)
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  9. Philosophical and Methodological Foundations of Post-Turing Intelligent Robotics.Albert Efimov - 2021 - Dissertation, Institute of Philosophy Russian Academy of Science
    This is PhD thesis submitted to Institute Philosophy of Russian Academy of Science in March 2021.
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  10. Turingův test: filozofické aspekty umělé inteligence.Filip Tvrdý - 2011 - Dissertation, Palacky University
    Disertační práce se zabývá problematikou připisování myšlení jiným entitám, a to pomocí imitační hry navržené v roce 1950 britským filosofem Alanem Turingem. Jeho kritérium, známé v dějinách filosofie jako Turingův test, je podrobeno detailní analýze. Práce popisuje nejen původní námitky samotného Turinga, ale především pozdější diskuse v druhé polovině 20. století. Největší pozornost je věnována těmto kritikám: Lucasova matematická námitka využívající Gödelovu větu o neúplnosti, Searlův argument čínského pokoje konstatující nedostatečnost syntaxe pro sémantiku, Blockův návrh na použití brutální síly pro (...)
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  11. Turingův test: filozofické aspekty umělé inteligence.Filip Tvrdý - 2014 - Prague: Togga.
    Kniha se zabývá problematikou připisování myšlení jiným entitám, a to pomocí imitační hry navržené v roce 1950 britským filozofem Alanem Turingem. Jeho kritérium, známé v dějinách filozofie jako Turingův test, je podrobeno detailní analýze. Kniha popisuje nejen původní námitky samotného Turinga, ale především pozdější diskuse v druhé polovině 20. století. Největší pozornost je věnována těmto kritikám: Lucasova matematická námitka využívající Gödelovu větu o neúplnosti, Searlův argument čínského pokoje konstatující nedostatečnost syntaxe pro sémantiku, Blockův návrh na použití brutální síly pro řešení (...)
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  12. A Quantum Computer in a 'Chinese Room'.Vasil Penchev - 2020 - Mechanical Engineering eJournal (Elsevier: SSRN) 3 (155):1-8.
    Pattern recognition is represented as the limit, to which an infinite Turing process converges. A Turing machine, in which the bits are substituted with qubits, is introduced. That quantum Turing machine can recognize two complementary patterns in any data. That ability of universal pattern recognition is interpreted as an intellect featuring any quantum computer. The property is valid only within a quantum computer: To utilize it, the observer should be sited inside it. Being outside it, the observer would obtain quite (...)
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  13. Recensione di I Am a Strange Loop (Sono un Ciclo Strano) di Douglas Hofstadter (2007) (recensione 2019).Michael Richard Starks - 2020 - In Benvenuti all'inferno sulla Terra: Bambini, Cambiamenti climatici, Bitcoin, Cartelli, Cina, Democrazia, Diversità, Disgenetica, Uguaglianza, Pirati Informatici, Diritti umani, Islam, Liberalismo, Prosperità, Web, Caos, Fame, Malattia, Violenza, Intellig. Las Vegas, NV, USA: Reality Press. pp. 107-123.
    Ultimo sermone della Chiesa del Naturalismo fondamentalista del pastore Hofstadter. Come il suo lavoro molto più famoso (o infame per i suoi instancabili errori filosofici) Godel, Escher, Bach, ha una plausibilità superficiale, ma se si capisce che questo è scientismo dilagante che mescola problemi scientifici reali con quelli filosofici (cioè, gli unici problemi reali sono quali giochi di linguaggio dovremmo giocare) allora quasi tutti i suoi interessi scompaiono. Fornisco un quadro per l'analisi basata sulla psicologia evolutiva e il lavoro di (...)
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  14. Wolpert, Chaitin und Wittgenstein über Unmöglichkeit, Unvollständigkeit, das Lügner-Paradoxon, Theismus, die Grenzen der Berechnung, ein nicht-quantenmechanisches Unsicherheitsprinzip und das Universum als Computer – der ultimative Satz in Turing Machine Theory (überarbeitet 2019).Michael Richard Starks - 2020 - In Willkommen in der Hölle auf Erden: Babys, Klimawandel, Bitcoin, Kartelle, China, Demokratie, Vielfalt, Dysgenie, Gleichheit, Hacker, Menschenrechte, Islam, Liberalismus, Wohlstand, Internet, Chaos, Hunger, Krankheit, Gewalt, Künstliche Intelligenz, Krieg. Las Vegas, NV, USA: Reality Press. pp. 186-190.
    Ich habe viele kürzliche Diskussionen über die Grenzen der Berechnung und das Universum als Computer gelesen, in der Hoffnung, einige Kommentare über die erstaunliche Arbeit des Polymath Physikers und Entscheidungstheoretikers David Wolpert zu finden, aber habe kein einziges Zitat gefunden und so präsentiere ich diese sehr kurze Zusammenfassung. Wolpert bewies einige verblüffende Unmöglichkeit oder Unvollständigkeit Theoreme (1992 bis 2008-siehe arxiv dot org) über die Grenzen der Schlussfolgerung (Berechnung), die so allgemein sind, dass sie unabhängig von dem Gerät, das die Berechnung, (...)
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  15. のレビュー"「理由の外側の限界"」(The Outer Limits of Reason) by Noson Yanofsky (2019年改訂レビュー).Michael Richard Starks - 2020 - In 地獄へようこそ 赤ちゃん、気候変動、ビットコイン、カルテル、中国、民主主義、多様性、ディスジェニックス、平等、ハッカー、人権、イスラム教、自由主義、繁栄、ウェブ、カオス、飢餓、病気、暴力、人工知能、戦争. Las Vegas, NV , USA: Reality Press. pp. 178-192.
    ノソン・ヤノフスキーの「理性の外側の限界」を、ウィトゲンシュタインと進化心理学の統一的な視点から詳しくレビューします。私は、言語や数学のパラドックス、不完全さ、デデシッド性、コンピュータとしての脳、宇 宙などの問題の難しさは、すべて適切な文脈での言語の使用を注意深く見なさなかったことから生じるため、科学的事実の問題を言語の仕組みの問題から切り離すことができなかったことを示しています。私は、不完全さ、 パラタンシ、不整合性に関するヴィトゲンシュタインの見解と、計算の限界に関するウォルパートの仕事について議論します。要約すると:ブルックリンによると宇宙---良い科学、それほど良い哲学ではありません。 現代の2つのシス・エムスの見解から人間の行動のための包括的な最新の枠組みを望む人は、私の著書「ルートヴィヒ・ヴィトゲンシュタインとジョン・サールの第2回(2019)における哲学、心理学、ミンと言語の論 理的構造」を参照することができます。私の著作の多くにご興味がある人は、運命の惑星における「話す猿--哲学、心理学、科学、宗教、政治―記事とレビュー2006-2019 第3回(2019)」と21世紀4日(2019年)の自殺ユートピア妄想st Century 4th ed (2019)などを見ることができます。 .
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  16. Wolpert, Chaitin and Wittgenstein 不可能性、不完全性、嘘つきパラドックス、 無神論、計算の限界、非量子力学的不確実性原理、そしてコンピューターとして の宇宙-チューリング機械理論の究極の定理 (2019年改訂レビュー).Michael Richard Starks - 2020 - In 地獄へようこそ 赤ちゃん、気候変動、ビットコイン、カルテル、中国、民主主義、多様性、ディスジェニックス、平等、ハッカー、人権、イスラム教、自由主義、繁栄、ウェブ、カオス、飢餓、病気、暴力、人工知能、戦争. Las Vegas,, NV , USA: Reality Press. pp. 173-177.
    私は計算と宇宙の限界に関する最近の議論をコンピュータとして読み、ポリマス物理学者と意思決定理論家デビッド・ウォルパートの驚くべき仕事に関するいくつかのコメントを見つけることを望んでいますが、単一の引用 を見つけていないので、私はこの非常に簡単な要約を提示します。ウォルパートは、計算を行うデバイスから独立し、物理学の法則から独立している推論(計算)の限界に関する驚くべき不可能または不完全な定理(199 2年から2008年のarxiv.org参照)を証明したので、コンピュータ、物理学、人間の行動に適用されます。彼らは、カントールの対角化、嘘つきのパラドックス、ワールドラインを利用して、チューリングマシ ン理論の究極の定理である可能性のあるものを提供し、不可能、不完全性、計算の限界、そしてコンピュータとしての宇宙に関する洞察を提供し、すべての可能な宇宙とすべての存在またはメカニズムを生み出し、とりわけ 非量子機械不確実性原理と単一主義の証明を生み出します。チャイティン、ソロモノフ、コモルガロフ、ヴィトゲンシュタインの古典的な作品と、どのプログラム(したがってデバイスも)が所有するよりも複雑なシーケン ス(またはデバイス)を生成できないという考えには明らかなつながりがあります。この作品の体は、物理的な宇宙よりも複雑な存在はあり得ないので無テズムを意味すると言うかもしれませんし、ヴィトゲンチニアンの観 点から見ると、「より複雑な」は無意味です(満足の条件はありません、すなわち、真実のメーカーやテスト)。「神」(つまり、無限の時間/空間とエネルギーを持つ「デバイス」)でさえ、与えられた「数」が「ランダ ム」であるかどうかを判断したり、与えられた「公式」、定理または「文章」または「デバイス」(これらはすべて複雑な言語ゲームである)が特定の「システム」の一部であることを示す特定の方法を見つけることができ ません。 現代の2つのシス・エムスの見解から人間の行動のための包括的な最新の枠組みを望む人は、私の著書「ルートヴィヒ・ヴィトゲンシュタインとジョン・サールの第2回(2019)における哲学、心理学、ミンと言語の論 理的構造」を参照することができます。私の著作の多くにご興味がある人は、21世紀4日(2019年)の「話す猿--哲学、心理学、科学、宗教、政治」を見ることができます。 .
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  17. Что означают парапоследовательные, неопределимые, случайные, вычислительные и неполные? Обзор: “Путь Годеля - Приключения в неопределенном мире” (Godel's Way: Exploits into an undecidable world) by Gregory Chaitin, Francisco A Doria, Newton C.A. da Costa 160p (2012) (обзор пересмотрен 2019).Michael Richard Starks - 2020 - In ДОБРО ПОЖАЛОВАТЬ В АД НА НАШЕМ МИРЕ : Дети, Изменение климата, Биткойн, Картели, Китай, Демократия, Разнообразие, Диссигеника, Равенство, Хакеры, Права человека, Ислам, Либерализм, Процветание, Сеть, Хаос, Голод, Болезнь, Насилие, Искусственный интелле. Las Vegas, NV USA: Reality Press. pp. 171-186.
    В «Godel's Way» три видных ученых обсуждают такие вопросы, как неплатежеспособность, неполнота, случайность, вычислительность и последовательность. Я подхожу к этим вопросам с точки зрения Витгенштейна, что есть две основные проблемы, которые имеют совершенно разные решения. Есть научные или эмпирические вопросы, которые являются факты о мире, которые должны быть исследованы наблюдений и философские вопросы о том, как язык может быть использован внятно (которые включают в себя определенные вопросы в математике и логике), которые должны быть решены, глядят, как мы на самом деле (...)
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  18. Technological Prerequisites for Indistinguishability of a Person and His/Her Computer Replica.Albert Efimov - 2019 - Artificial Societies 4.
    Some people wrongly believe that A. Turing’s works that underlie all modern computer science never discussed “physical” robots. This is not so, since Turing did speak about such machines, though making a reservation that this discussion was still premature. In particular, in his 1948 report [8], he suggested that a physical intelligent machine equipped with motors, cameras and loudspeakers, when wandering through the fields of England, would present “the danger to the ordinary citizen would be serious.” [8, ]. Due to (...)
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  19. Do Chatbots Dream of Androids? Prospects for the Technological Development of Artificial Intelligence and Robotics.Albert R. Efimov - 2019 - Philosophical Sciences 62 (7):73-95.
    The article discusses the main trends in the development of artificial intelligence systems and robotics (AI&R). The main question that is considered in this context is whether artificial systems are going to become more and more anthropomorphic, both intellectually and physically. In the current article, the author analyzes the current state and prospects of technological development of artificial intelligence and robotics, and also determines the main aspects of the impact of these technologies on society and economy, indicating the geopolitical strategic (...)
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  20. There is No General AI.Jobst Landgrebe & Barry Smith - 2020 - arXiv.
    The goal of creating Artificial General Intelligence (AGI) – or in other words of creating Turing machines (modern computers) that can behave in a way that mimics human intelligence – has occupied AI researchers ever since the idea of AI was first proposed. One common theme in these discussions is the thesis that the ability of a machine to conduct convincing dialogues with human beings can serve as at least a sufficient criterion of AGI. We argue that this very ability (...)
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  21. Minimum Intelligent Signal Test as an Alternative to the Turing Test.Paweł Łupkowski & Patrycja Jurowska - 2019 - Diametros 59:35-47.
    The aim of this paper is to present and discuss the issue of the adequacy of the Minimum Intelligent Signal Test (MIST) as an alternative to the Turing Test. MIST has been proposed by Chris McKinstry as a better alternative to Turing’s original idea. Two of the main claims about MIST are that (1) MIST questions exploit commonsense knowledge and as a result are expected to be easy to answer for human beings and difficult for computer programs; and that (2) (...)
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  22. Davidson's No-Priority Thesis in Defending the Turing Test.Mohammad Reza Vaez Shahrestani - 2012 - Procedia - Social and Behavioral Sciences 32:456-461.
    Turing does not provide an explanation for substituting the original question of his test – i.e., “Can machines think?” with “Can a machine pass the imitation game?” – resulting in an argumentative gap in his main thesis. In this article, I argue that a positive answer to the second question would mean attributing the ability of linguistic interactions to machines; while a positive answer to the original question would mean attributing the ability of thinking to machines. In such a situation, (...)
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  23. The Turing Guide.Jack Copeland, Jonathan Bowen, Robin Wilson & Mark Sprevak (eds.) - 2017 - Oxford: Oxford University Press.
    This volume celebrates the various facets of Alan Turing (1912–1954), the British mathematician and computing pioneer, widely considered as the father of computer science. It is aimed at the general reader, with additional notes and references for those who wish to explore the life and work of Turing more deeply. -/- The book is divided into eight parts, covering different aspects of Turing’s life and work. -/- Part I presents various biographical aspects of Turing, some from a personal point of (...)
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