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Summary The Turing test is a test for intelligence in machines.  In 1950, Alan Turing published "Computing Machinery and Intelligence" where he described a game he called the "imitation game" involving a human judge conversing only in written text with a second human and a language-using computer, each hidden away in separate rooms (3 rooms total).  The point of the game is for the computer to converse in such a human-like way with the judge that the judge cannot tell the second human from the computer (in usual renditions of the Test, the second human also tries to convince the judge that he or she is the human, so the test becomes a contest).  The computer wins if the judge cannot tell which conversant is the human and which is the computer.  Turing's point is that were a computer to successfully and repeatedly pass such a test, we should then regard the computer as intelligent on the human level. To date, no computer has passed the Test reliably and often.
Key works Turing 1950; Weizenbaum, Joseph (January 1966), "ELIZA—A Computer Program For the Study of Natural Language Communication Between Man And Machine", Communications of the ACM 9 (1): 36–45.
Introductions McCorduck, Pamela (2004), Machines Who Think (2nd ed.), Natick, MA: A. K. Peters, Ltd.; Weizenbaum, Joseph (1976), Computer power and human reason: from judgment to calculationW. H. Freeman and CompanyISBN 0-7167-0463-3; Robert Epstein, Gary Roberts, Grace Beber (eds.) (2008), Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer; Searle 1980
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  1. Introduction to a Systemic Theory of Meaning (July 2014 Update).Christophe Menant - manuscript
    Information and Meaning are present everywhere around us and within ourselves. Specific studies have been implemented in order to link information and meaning: - Semiotics - Phenomenology - Analytic Philosophy - Psychology No general coverage is available for the notion of meaning. We propose to complement this lack by a systemic approach to meaning generation.
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  2. A Novel Approach for Identifying a Human-Like Self-Conscious Behavior.Gianpiero Negri - manuscript
    In this paper a possible extension of Turing test [1] will be presented, which is intended to overcome the limits highlighted by several researchers and scientists in the last seventy years. The main problem related to the execution in Turing test is substantially dealing with the trouble in identification of a human-like intelligence based on a pure evaluation of external behavior of a machine. In this work first of all a description of classical Turing test will be done. After that, (...)
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  3. Vindication of the Rights of Machine.Kris Rhodes - manuscript
    In this paper, I argue that certain Machines can have rights independently of whether they are sentient, or conscious, or whatever you might call it.
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  4. The Significance of Evidence-Based Reasoning for Mathematics, Mathematics Education, Philosophy and the Natural Sciences.Bhupinder Singh Anand - forthcoming
    In this multi-disciplinary investigation we show how an evidence-based perspective of quantification---in terms of algorithmic verifiability and algorithmic computability---admits evidence-based definitions of well-definedness and effective computability, which yield two unarguably constructive interpretations of the first-order Peano Arithmetic PA---over the structure N of the natural numbers---that are complementary, not contradictory. The first yields the weak, standard, interpretation of PA over N, which is well-defined with respect to assignments of algorithmically verifiable Tarskian truth values to the formulas of PA under the interpretation. (...)
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  5. 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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  6. Case Study: Just Another Test?Herbert J. Bonifacio & Annie Janvier - forthcoming - Hastings Center Report.
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  7. The Turing Test is a Thought Experiment.Bernardo Gonçalves - forthcoming - Minds and Machines:1-31.
    The Turing test has been studied and run as a controlled experiment and found to be underspecified and poorly designed. On the other hand, it has been defended and still attracts interest as a test for true artificial intelligence (AI). Scientists and philosophers regret the test’s current status, acknowledging that the situation is at odds with the intellectual standards of Turing’s works. This article refers to this as the Turing Test Dilemma, following the observation that the test has been under (...)
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  8. 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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  9. 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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  10. What is a Turing test for emotional AI?Manh-Tung Ho - forthcoming - AI and Society:1-2.
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  11. Non-Turing Computers Are the New Non-Euclidean Geometries.Mark Hogarth - forthcoming - International Journal of Unconventional Computing:1--15.
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  12. 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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  13. Towards an Assessment of an AI System's Validity by a TURING Test.Rainer Knauf, Ilka Philippow & Avelino J. Gonzalez - forthcoming - Flairs {97, Proc. Florida Ai Research Symposium, Daytona Beach, Fl, Usa, May 11 {14, 1997, 397 {401. Florida Ai Research Society.
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  14. A new Turing test: metaphor vs. nonsense.Irving Massey - forthcoming - AI and Society:1-8.
    My basic argument is that a computer cannot distinguish between metaphor and nonsense. This would be my new “Turing Test.” I was very fond of a particular Italian poem, but I was told by an Italian friend that it was a hackneyed poem of little worth. I then taught myself to experience the poem alternately, as real poetry and as the silly nonsense that my friend claimed it really was. Having done so, I realized that I could do the same (...)
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  15. I Test Epicutanei. Florence.A. Sertoli & P. Fabbri - forthcoming - Teorema: International Journal of Philosophy.
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  16. The Turing Test, or a Misuse of Language When Ascribing Mental Qualities to Machines.Józef Bremer & Mariusz Flasiński - 2022 - Forum Philosophicum: International Journal for Philosophy 27 (1):6-25.
    In this paper we discuss the views on the Turing test of four influential thinkers who belong to the tradition of analytic philosophy: Ludwig Wittgenstein, Noam Chomsky, Hilary Putnam and John Searle. Based on various beliefs about philosophical and/or linguistic matters, they arrive at different assessments of both the significance and suitability of the imitation game for the development of cognitive science and AI models. Nevertheless, they share a rejection of the idea that one can treat Turing test as a (...)
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  17. Intelligence as a Social Concept: a Socio-Technological Interpretation of the Turing Test.Shlomo Danziger - 2022 - Philosophy and Technology 35 (3):1-26.
    Alan Turing’s 1950 imitation game has been widely understood as a means for testing if an entity is intelligent. Following a series of papers by Diane Proudfoot, I offer a socio-technological interpretation of Turing’s paper and present an alternative way of understanding both the imitation game and Turing’s concept of intelligence. Turing, I claim, saw intelligence as a social concept, meaning that possession of intelligence is a property determined by society’s attitude toward the entity. He realized that as long as (...)
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  18. Turing’s Conceptual Engineering.Marcin Miłkowski - 2022 - Philosophies 7 (3):69.
    Alan Turing’s influence on subsequent research in artificial intelligence is undeniable. His proposed test for intelligence remains influential. In this paper, I propose to analyze his conception of intelligence by relying on traditional close reading and language technology. The Turing test is interpreted as an instance of conceptual engineering that rejects the role of the previous linguistic usage, but appeals to intuition pumps instead. Even though many conceive his proposal as a prime case of operationalism, it is more plausibly viewed (...)
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  19. Passing the Turing Test? AI Generated Poetry and Posthuman Creativity.Regina Schober - 2022 - In Herta Nagl-Docekal & Waldemar Zacharasiewicz (eds.), Artificial Intelligence and Human Enhancement: Affirmative and Critical Approaches in the Humanities. De Gruyter. pp. 151-166.
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  20. The Philosophising Machine – a Specification of the Turing Test.Arthur C. Schwaninger - 2022 - Philosophia 50 (3):1437-1453.
    Block’s, 5–43 1981) anti-behaviourist attack of the Turing Test not only illustrates that the test is a non-sufficient criterion for attributing thought; I suggest that it also exemplifies the limiting case of the more general concern that a machine which has access to enormous amounts of data can pass the Turing Test by simple symbol-manipulation techniques. If the answers to a human interrogator are entailed by the machines’ data, the Turing Test offers no clear criterion to distinguish between a thinking (...)
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  21. 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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  22. 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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  23. The Irrelevance of the Turing Test in Current Deep Learning.Ondrej Hriadel - 2021 - Pro-Fil 22 (2):28-44.
    The role of artificial intelligence in the Turing test is to imitate human beings to such an extent that people will not realize it is a machine. With the rise of deep learning, the situation is changing rapidly as the new systems do not focus on imitating human intelligence but emphasize thorough solutions to specific issues. The main difference between predefined AI and deep learning is that these systems are self-learning and have verifiable results. Firstly, we need to analyse the (...)
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  24. Artificial Intelligence and its Natural Limits.Karl D. Stephan & Gyula Klima - 2021 - AI and Society (1):9-18.
    An argument with roots in ancient Greek philosophy claims that only humans are capable of a certain class of thought termed conceptual, as opposed to perceptual thought, which is common to humans, the higher animals, and some machines. We outline the most detailed modern version of this argument due to Mortimer Adler, who in the 1960s argued for the uniqueness of the human power of conceptual thought. He also admitted that if conceptual thought were ever manifested by machines, such an (...)
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  25. 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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  26. Magical Thinking: The Intersection of Quantum Entanglement and Self-Referential Recursion.Ilexa Yardley - 2021 - Https://Medium.Com/the-Circular-Theory/.
    The superposition of magical thinking, quantum entanglement, and self-referential recursion explains the relationship between human and machine intelligence (universal intelligence).
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  27. Philosophy of Mind: The Basics.Amy Kind - 2020 - New York, NY: Routledge.
    Philosophy of Mind: The Basics is a concise and engaging introduction to the fundamental philosophical questions and theories about the mind. The author Amy Kind, a leading expert in the field, examines central issues concerning the nature of consciousness, thought, and emotion. The book addresses key questions such as: • What is the nature of the mind? • What is the relationship between the mind and the brain? • Can machines have minds? • How will future technology impact the mind? (...)
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  28. 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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  29. 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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  30. 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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  31. 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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  32. 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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  33. 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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  34. 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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  35. 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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  36. 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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  37. 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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  38. 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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  39. 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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  40. Alan Turing and the theoretical foundation of the information age.Paul E. Ceruzzi - 2017 - Metascience 26 (1):63-66.
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  41. From Alan Turing to Modern AI: Practical Solutions and an Implicit Epistemic Stance.George F. Luger & Chayan Chakrabarti - 2017 - AI and Society 32 (3):321-338.
    It has been just over 100 years since the birth of Alan Turing and more than 65 years since he published in Mind his seminal paper, Computing Machinery and Intelligence. In the Mind paper, Turing asked a number of questions, including whether computers could ever be said to have the power of “thinking”. Turing also set up a number of criteria—including his imitation game—under which a human could judge whether a computer could be said to be “intelligent”. Turing’s paper, as (...)
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  42. Machine Humour: Examples From Turing Test Experiments.Huma Shah & Kevin Warwick - 2017 - AI and Society 32 (4):553-561.
    In this paper, we look at the possibility of a machine having a sense of humour. In particular, we focus on actual machine utterances in Turing test discourses. In doing so, we do not consider the Turing test in depth and what this might mean for humanity, rather we merely look at cases in conversations when the output from a machine can be considered to be humorous. We link such outpourings with Turing’s “arguments from various disabilities” used against the concept (...)
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  43. Será que as Máquinas Podem Pensar? Da Resposta Cartesiana à Crítica do Teste de Turing.Eurico Carvalho - 2016 - Apeiron — Student Journal of Philosophy (Portugal) 1 (7):15-44.
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  44. Review of The Emotion Machine by Marvin Minsky (2007).Michael Starks - 2016 - In Suicidal Utopian Delusions in the 21st Century: Philosophy, Human Nature and the Collapse of Civilization-- Articles and Reviews 2006-2017 2nd Edition Feb 2018. Michael Starks. pp. 627.
    Dullest book by a major scientist I have ever read. I suppose if you know almost nothing about cognition or AI research you might find this book useful. For anyone else it is a horrific bore. There are hundreds of books in cog sci, robotics, AI, evolutionary psychology and philosophy offering far more info and insight on cognition than this one. Minsky is a top rate senior scientist but it barely shows here. He has alot of good references but they (...)
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  45. The Importance of a Human Viewpoint on Computer Natural Language Capabilities: A Turing Test Perspective.Kevin Warwick & Huma Shah - 2016 - AI and Society 31 (2):207-221.
  46. Effects of Lying in Practical Turing Tests.Kevin Warwick & Huma Shah - 2016 - AI and Society 31 (1):5-15.
  47. Retaking the Test.David Isaac Backer & Tyson Edward Lewis - 2015 - Educational Studies: A Jrnl of the American Educ. Studies Assoc 51 (3):193-208.
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  48. Trois leçons philosophiques de Turing et la philosophie de l’information.Luciano Floridi, Paolo Quintili & Éric Guichard - 2015 - Rue Descartes 87 (4):157.
    Quand on se penche sur l’héritage philosophique de Turing, deux risques se posent. Le premier, c’est de le réduire à son test célèbre (Turing 1950). Ce qui a toutefois le mérite de la clarté. N’importe qui peut reconnaître la contribution en question et la situer dans le débat important sur la philosophie de l’intelligence artificielle. Le second risque est de le diluer dans un récit universel, faisant des idées deTuring les graines de tout ce que nous faisons et savons aujourd’hui. (...)
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  49. How Sensorimotor Interactions Enable Sentence Imitation.Tzu-Wei Hung - 2015 - Minds and Machines 25 (4):321-338.
    Despite intensive debates regarding action imitation and sentence imitation, few studies have examined their relationship. In this paper, we argue that the mechanism of action imitation is necessary and in some cases sufficient to describe sentence imitation. We first develop a framework for action imitation in which key ideas of Hurley’s shared circuits model are integrated with Wolpert et al.’s motor selection mechanism and its extensions. We then explain how this action-based framework clarifies sentence imitation without a language-specific faculty. Finally, (...)
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  50. A Test Unlike Any Other.Jacqueline Savard - 2015 - Narrative Inquiry in Bioethics 5 (3):216-218.
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