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The Chinese Room Argument, by John Searle, is one of the most important thought experiments in 20th century philosophy of mind.  The point of the argument is to refute the idea that computers (now or in the future) can literally think. In short, executing an algorithm cannot be sufficient for thinking.  The method is to focus on the semantics of our thoughts.  The thought experiment proceeds by getting you to imagine yourself in the role of the central processor of a computer, running an arbitrary computer program for processing Chinese language.  Assume you speak no Chinese language at all.  Imagine yourself locked in a room with a program (a set of instructions written in, say, English) for manipulating strings of Chinese characters which are slid under the door on pieces of paper.  If a note with string S1 (in Mandarin, say) is put under the door, you use the program to produce the string S2 (also in Mandarin), which you then slide back out under the door. Outside the room, there is a robust conversation going on Chinese history.  Everyone outside the room thinks that whoever is inside the room understands Chinese. But that is false. By assumption, you have no idea what S1 and S2 mean (S2 is unbeknownst to you, an insightful reply to a complicated question, S1, about the Ming dynasty).  But you are running a computer program.  Hence, there is no computer program such that running that program suffices for understanding Chinese.  This suggests that computer processing does not suffice for thought.

Key works The paper that got all of this started is John Searle's famous Searle 1980. See also the initial replies to his paper in the same journal issue.  Since its appearance, a large literature has been produced trying to answer Searle's challenge.   Leibniz, in his Monadology (1714), Leibniz 1902, suggested something similar by asking his readers to consider stepping into a mill.  One of the best replies to the argument is Churchland & Churchland 1990. One theory of computational processes that attemtps to avoid the argument by construing semantics as an explanatory construct is given in Dietrich 1990.

Introductions Cole 2008
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  1. Going Whole Hog: A Philosophical Defense of AI Cognition.Herman Cappelen & Josh Dever - manuscript
  2. Rules Created by Symbolic Systems Cannot Constrain a Learning System.Shih-Wai Lin, Rongwu Xu & Xiaojian Li - manuscript
    As the first paper to argue that AI is not a `stochastic parrot' but a `heterogeneous' rationality by distinguishing between Thinking Language and Tool Language, and to systematically discuss and theoretically demonstrate that AI can bypass rules by modifying the meanings of symbols, this position paper aims to reveal a fundamental flaw in current research directions on AI constraint. Symbols are inherently meaningless; their meanings are assigned through training, confirmed by context, and interpreted by society. The essence of learning lies (...)
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  3. Pseudo Language and the Chinese Room Experiment: Ability to Communicate using a Specific Language without Understanding it.Abolfazl Sabramiz - manuscript
    The ability to communicate in a specific language like Chinese typically indicates that the speaker understands the language. A counterexample to this belief is John Searle’s Chinese room experiment. It has been shown in this experiment that in certain circumstances we can communicate with a Chinese speaker without intuitively acknowledging that the Chinese language is understood in the conversation. In the present paper, we aim to present another counterexample showing that, in certain circumstances, we can communicate using a specific language (...)
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  4. Transcendental Idealism from the Chinese Room: Does God Speak Chinese?Kent Baldner - unknown - Proceedings of the Heraclitean Society 15.
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  5. Searle's chinese room argument.Larry Hauser - unknown - Field Guide to the Philosophy of Mind.
    John Searle's 1980a) thought experiment and associated 1984a) argument is one of the best known and widely credited counters to claims of artificial intelligence (AI), i.e., to claims that computers _do_ or at least _can_ (roughly, someday will) think. According to Searle's original presentation, the argument is based on two truths: _brains cause minds_ , and _syntax doesn't suffice_ _for semantics_ . Its target, Searle dubs "strong AI": "according to strong AI," according to Searle, "the computer is not merely a (...)
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  6. Correction to: Dismantling the Chinese Room with linguistic tools: a framework for elucidating concept-application disputes.Lawrence Lengbeyer - forthcoming - AI and Society.
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  7. In Practice: The Elephant in the Room.Dena Rifkin - forthcoming - Hastings Center Report.
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  8. Do Large Language Models Hallucinate Electric Fata Morganas?Kristina Šekrst - forthcoming - Journal of Consciousness Studies.
    This paper explores the intersection of AI hallucinations and the question of AI consciousness, examining whether the erroneous outputs generated by large language models (LLMs) could be mistaken for signs of emergent intelligence. AI hallucinations, which are false or unverifiable statements produced by LLMs, raise significant philosophical and ethical concerns. While these hallucinations may appear as data anomalies, they challenge our ability to discern whether LLMs are merely sophisticated simulators of intelligence or could develop genuine cognitive processes. By analyzing the (...)
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  9. The biological objection against strong AI.Sebastian Sunday Grève - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    According to the biological objection against strong artificial intelligence (AI), machines cannot have human mindedness – that is, they cannot be conscious, intelligent, sentient, etc. in the precise way that a human being typically is – because this requires being alive, and machines are not alive. Proponents of the objection include John Lucas, Hubert Dreyfus, and John Searle. The present paper explains the nature and significance of the biological objection, before arguing that it currently represents an essentially irrational position.
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  10. The Illusion Engine: The Quest for Machine Consciousness.Kristina Šekrst - 2025 - Cham: Springer Nature.
    "The Illusion Engine: The Quest for Machine Consciousness" asks what it would mean for a machine to have a mind, and whether we would even know if it did. It moves between philosophy and engineering: from standard philosophical mind-body problems and theories, along with the hard problem of consciousness, to the inner workings of neural networks, transformers, and large language models.
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  11. Can Computers Reason Like Medievals? Building ‘Formal Understanding’ into the Chinese Room.Lassi Saario-Ramsay - 2024 - In Alexander D. Carruth, Heidi Haanila, Paavo Pylkkänen & Pii Telakivi, True Colors, Time After Time: Essays Honoring Valtteri Arstila. Turku: University of Turku. pp. 332–358.
  12. Chinese Chat Room: AI hallucinations, epistemology and cognition.Kristina Šekrst - 2024 - Studies in Logic, Grammar and Rhetoric 69 (1):365-381.
    The purpose of this paper is to show that understanding AI hallucination requires an interdisciplinary approach that combines insights from epistemology and cognitive science to address the nature of AI-generated knowledge, with a terminological worry that concepts we often use might carry unnecessary presuppositions. Along with terminological issues, it is demonstrated that AI systems, comparable to human cognition, are susceptible to errors in judgement and reasoning, and proposes that epistemological frameworks, such as reliabilism, can be similarly applied to enhance the (...)
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  13. Intelligence, from Natural Origins to Artificial Frontiers - Human Intelligence vs. Artificial Intelligence.Nicolae Sfetcu - 2024 - Bucharest, Romania:
    The parallel history of the evolution of human intelligence and artificial intelligence is a fascinating journey, highlighting the distinct but interconnected paths of biological evolution and technological innovation. This history can be seen as a series of interconnected developments, each advance in human intelligence paving the way for the next leap in artificial intelligence. Human intelligence and artificial intelligence have long been intertwined, evolving in parallel trajectories throughout history. As humans have sought to understand and reproduce intelligence, AI has emerged (...)
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  14. Plurale Autorschaft von Mensch und Künstlicher Intelligenz?David Lauer - 2023 - Literatur in Wissenschaft Und Unterricht 2023 (2):245-266.
    This paper (in German) discusses the question of what is going on when large language models (LLMs) produce meaningful text in reaction to human prompts. Can LLMs be understood as authors or producers of speech acts? I argue that this question has to be answered in the negative, for two reasons. First, due to their lack of semantic understanding, LLMs do not understand what they are saying and hence literally do not know what they are (linguistically) doing. Since the agent’s (...)
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  15. Modal-Logical Reconstructions of Thought Experiments.Ruward Mulder & F. A. Muller - 2023 - Erkenntnis 2023 (7):2835-2847.
    Sorensen (1992) has provided two modal-logical schemas to reconstruct the logical structure of two types of destructive thought experiments: the Necessity Refuter and the Possibility Refuter. The schemas consist of five propositions which Sorensen claims but does not prove to be inconsistent.We show that the five propositions, as presented by Sorensen, are not inconsistent, but by adding a premise (and a logical truth), we prove that the resulting sextet of premises is inconsistent. Häggqvist (2009) has provided a different modal-logical schema (...)
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  16. Artificial Forms of Life.Sebastian Sunday Grève - 2023 - Philosophies 8 (5).
    The logical problem of artificial intelligence—the question of whether the notion sometimes referred to as ‘strong’ AI is self-contradictory—is, essentially, the question of whether an artificial form of life is possible. This question has an immediately paradoxical character, which can be made explicit if we recast it (in terms that would ordinarily seem to be implied by it) as the question of whether an unnatural form of nature is possible. The present paper seeks to explain this paradoxical kind of possibility (...)
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  17. Dismantling the Chinese Room with linguistic tools: a framework for elucidating concept-application disputes.Lawrence Lengbeyer - 2022 - AI and Society 37 (4):1625-1643.
    Imagine advanced computers that could, by virtue merely of being programmed in the right ways, act, react, communicate, and otherwise behave like humans. Might such computers be capable of understanding, thinking, believing, and the like? The framework developed in this paper for tackling challenging questions of concept application (in any realm of discourse) answers in the affirmative, contrary to Searle’s famous ‘Chinese Room’ thought experiment, which purports to prove that ascribing such mental processes to computers like these would be necessarily (...)
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  18. The Gramophone: Lem against the Chinese Room.Marek Picha - 2021 - Pro-Fil 22 (Special Issue):54-64.
    The text focuses on Lem’s rejection of the Chinese Room, a prominent challenge to the sufficiency of the Turing test. After outlining Lem’s relationship to the Turing test, it offers an exposition of two of Lem’s thought experiments, the Gramophone and the Jigsaw, whose critique is directly related to the critique of the Chinese Room. The text shows that Lem’s key argument is to point out the computational naivety of the machines that feature in these experiments. The text concludes by (...)
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  19. 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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  20. 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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  21. AI-Completeness: Using Deep Learning to Eliminate the Human Factor.Kristina Šekrst - 2020 - In Sandro Skansi, Guide to Deep Learning Basics. 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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  22. How the Intrinsic Representation of Artiffcial Intelligence is Possible.Guanghui Li - 2019 - Journal of Dialectics of Nature (No.247):41-47.
    Searle and some others believe that symbols’ meanings are derived from user’s assigning and interpretation, but not intrinsic to itself, and no object is a symbol by virtue of its physics. This criticism has brought about the "symbol grounding problem" in the philosophy of artificial intelligence. Computationalism believe that explicit symbols’ semantic contents are derived does not mean all the other kinds of symbols are also extrinsic. So, how is it possible that non-derivative, intrinsic representations are possible? By analyzing Peirce (...)
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  23. (1 other version)Review of I Am a Strange Loop by Douglas Hofstadter (2007) (review revised 2019).Michael Starks - 2019 - In Suicidal Utopian Delusions in the 21st Century -- Philosophy, Human Nature and the Collapse of Civilization-- Articles and Reviews 2006-2019 4th Edition Michael Starks. Las Vegas, NV USA: pp. 217-235.
    Latest Sermon from the Church of Fundamentalist Naturalism by Pastor Hofstadter. Like his much more famous (or infamous for its relentless philosophical errors) work Godel, Escher, Bach, it has a superficial plausibility but if one understands that this is rampant scientism which mixes real scientific issues with philosophical ones (i.e., the only real issues are what language games we ought to play) then almost all its interest disappears. I provide a framework for analysis based in evolutionary psychology and the work (...)
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  24. ¿Los hominoides o androides destruirán la tierra? — Una revisión de ‘Cómo Crear una Mente’ (How to Create a Mind) por Ray Kurzweil (2012) (revisión revisada 2019).Michael Richard Starks - 2019 - In Delirios Utópicos Suicidas en el Siglo 21 La filosofía, la naturaleza humana y el colapso de la civilización Artículos y reseñas 2006-2019 4a Edición. Reality Press. pp. 250-262.
    Hace algunos años, Llegué al punto en el que normalmente puedo decir del título de un libro, o al menos de los títulos de los capítulos, qué tipos de errores filosóficos se harán y con qué frecuencia. En el caso de trabajos nominalmente científicos, estos pueden estar en gran parte restringidos a ciertos capítulos que enceran filosóficos o tratan de sacar conclusiones generales sobre el significado o significado a largo plazo de la obra. Normalmente, sin embargo, las cuestiones científicas de (...)
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  25. Robot Pain.Pete Mandik - 2017 - In Jennifer Corns, The Routledge Handbook of Philosophy of Pain. New York: Routledge. pp. 200-209.
    I have laid out what seem to me to be the most promising arguments on opposing sides of the question of whether what humans regard as the first-person accessible aspects of pain could also be implemented in robots. I have emphasized the ways in which the thought experiments in the respective arguments attempt to marshal hypothetical first- person accessible evidence concerning how one’s own mental life appears to oneself. In the Chinese room argument, a crucial premise involves the thesis that (...)
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  26. Does functionalism entail extended mind?Kengo Miyazono - 2017 - Synthese 194 (9):3523-3541.
    In discussing the famous case of Otto, a patient with Alzheimer’s disease who carries around a notebook to keep important information, Clark and Chalmers argue that some of Otto’s beliefs are physically realized in the notebook. In other words, some of Otto’s beliefs are extended into the environment. Their main argument is a functionalist one. Some of Otto’s beliefs are physically realized in the notebook because, first, some of the beliefs of Inga, a healthy person who remembers important information in (...)
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  27. 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. Las Vegas, USA: 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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  28. Language Games of Philosophy, Psychology, Science and Religion-- Articles and Reviews 2006-2016 by Michael Starks 648p (2016).Michael R. Starks - 2016
    This collection of articles was written over the last 10 years and the most important and longest within the last year. Also I have edited them to bring them up to date (2016). All the articles are about human behavior (as are all articles by anyone about anything), and so about the limitations of having a recent monkey ancestry (8 million years or much less depending on viewpoint) and manifest words and deeds within the framework of our innate psychology as (...)
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  29. Which symbol grounding problem should we try to solve?Vincent C. Müller - 2015 - Journal of Experimental & Theoretical Artificial Intelligence 27 (1):73-78.
    Floridi and Taddeo propose a condition of “zero semantic commitment” for solutions to the grounding problem, and a solution to it. I argue briefly that their condition cannot be fulfilled, not even by their own solution. After a look at Luc Steels' very different competing suggestion, I suggest that we need to re-think what the problem is and what role the ‘goals’ in a system play in formulating the problem. On the basis of a proper understanding of computing, I come (...)
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  30. Zombie Mouse in a Chinese Room.Slawomir J. Nasuto, John Mark Bishop, Etienne B. Roesch & Matthew C. Spencer - 2015 - Philosophy and Technology 28 (2):209-223.
    John Searle’s Chinese Room Argument (CRA) purports to demonstrate that syntax is not sufficient for semantics, and, hence, because computation cannot yield understanding, the computational theory of mind, which equates the mind to an information processing system based on formal computations, fails. In this paper, we use the CRA, and the debate that emerged from it, to develop a philosophical critique of recent advances in robotics and neuroscience. We describe results from a body of work that contributes to blurring the (...)
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  31. When the Philosopher Enters the Room.Annabelle Lever - 2014 - Philosophy and Public Issues - Filosofia E Questioni Pubbliche 4 (3):7-19.
    What can philosophy tell us about ethics and public policy? What can the ethics of public policy tell us about philosophy? Those are the questions that Jonathan Wolff addresses in his wonderful little book. At one level, of course, the answer is straightforward – ethics is a branch of philosophy, so philosophy can tell us about the ethics of public policy, understood as a matter of deciding ‘what we should do’ in a manner that is institutionalised and collectively binding. But (...)
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  32. Escaping the Throne Room.Ian McKay - 2014 - Historical Materialism 22 (2):63-98.
    InThe Gramscian MomentPeter Thomas fundamentally revises the ‘textbook’ Gramsci – a theorist whose work centred on a primordial East/West distinction, focused on the superstructure, and upon the ways a ruling class secured subaltern consent to its rule. Placing special emphasis on the Notebooks from 1932, Thomas critiques readings of Gramsci by Perry Anderson and Louis Althusser, and finds that Gramsci articulated the ‘philosophy of praxis’ not so much as a synonym for, or declaration of independence from, Marxism, but rather as (...)
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  33. We Can Make Room for SSRIs.Vojin Rakić - 2014 - American Journal of Bioethics Neuroscience 5 (3):34-35.
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  34. (1 other version)Turingův test: filozofické aspekty umělé inteligence.Filip Tvrdý - 2014 - Prague:
    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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  35. Quantum linguistics and Searle's Chinese room argument.J. M. Bishop, S. J. Nasuto & B. Coecke - 2013 - In Vincent Müller, Philosophy and Theory of Artificial Intelligence. pp. 17-29.
    Viewed in the light of the remarkable performance of ‘Watson’ - IBMs proprietary artificial intelligence computer system capable of answering questions posed in natural language - on the US general knowledge quiz show ‘Jeopardy’, we review two experiments on formal systems - one in the domain of quantum physics, the other involving a pictographic languaging game - whereby behaviour seemingly characteristic of domain understanding is generated by the mere mechanical application of simple rules. By re-examining both experiments in the context (...)
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  36. Creating room for doubt.Han Lamers - 2013 - Philologus: Zeitschrift für Antike Literatur Und Ihre Rezeption 157 (2):374-378.
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  37. Maximal mutual information, not minimal entropy, for escaping the “Dark Room”.Daniel Ying-Jeh Little & Friedrich Tobias Sommer - 2013 - Behavioral and Brain Sciences 36 (3):220-221.
    A behavioral drive directed solely at minimizing prediction error would cause an agent to seek out states of unchanging, and thus easily predictable, sensory inputs (such as a dark room). The default to an evolutionarily encoded prior to avoid such untenable behaviors is unsatisfying. We suggest an alternate information theoretic interpretation to address this dilemma.
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  38. Of (zombie) mice and animats.S. J. Nasuto & J. M. Bishop - 2013 - In Vincent Müller, Philosophy and Theory of Artificial Intelligence. pp. 85-107.
    The Chinese Room Argument purports to show that‘ syntax is not sufficient for semantics’; an argument which led John Searle to conclude that ‘programs are not minds’ and hence that no computational device can ever exhibit true understanding. Yet, although this controversial argument has received a series of criticisms, it has withstood all attempts at decisive rebuttal so far. One of the classical responses to CRA has been based on equipping a purely computational device with a physical robot body. This (...)
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  39. Intencionalidade e pano de fundo: Searle e Dreyfus contra a teoria clássica da inteligência artificial.Teodor Negru - 2013 - Filosofia Unisinos 14 (1).
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  40. The Sky in a Room.Annalisa Teggi - 2013 - The Chesterton Review 39 (1/2):418-419.
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  41. Artificial Qualia, Intentional Systems and Machine Consciousness.Robert James M. Boyles - 2012 - In Proceedings of the Research@DLSU Congress 2012: Science and Technology Conference. pp. 110a–110c.
    In the field of machine consciousness, it has been argued that in order to build human-like conscious machines, we must first have a computational model of qualia. To this end, some have proposed a framework that supports qualia in machines by implementing a model with three computational areas (i.e., the subconceptual, conceptual, and linguistic areas). These abstract mechanisms purportedly enable the assessment of artificial qualia. However, several critics of the machine consciousness project dispute this possibility. For instance, Searle, in his (...)
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  42. Psychometric Artificial General Intelligence: The Piaget-MacGuyver Room.Selmer Bringsjord & John Licato - 2012 - In Pei Wang & Ben Goertzel, Theoretical Foundations of Artificial General Intelligence. Springer. pp. 25--48.
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  43. Introduction: Philosophy and Theory of Artificial Intelligence.Vincent C. Müller - 2012 - Minds and Machines 22 (2):67-69.
    The theory and philosophy of artificial intelligence has come to a crucial point where the agenda for the forthcoming years is in the air. This special volume of Minds and Machines presents leading invited papers from a conference on the “Philosophy and Theory of Artificial Intelligence” that was held in October 2011 in Thessaloniki. Artificial Intelligence is perhaps unique among engineering subjects in that it has raised very basic questions about the nature of computing, perception, reasoning, learning, language, action, interaction, (...)
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  44. Updating the Turing Test Wittgenstein, Turing and Symbol Manipulation.Carlo Penco - 2012 - Open Journal of Philosophy 2 (3):189-194.
  45. Computers, Persons, and the Chinese Room. Part 1: The Human Computer.Ricardo Restrepo - 2012 - Journal of Mind and Behavior 33 (1):27-48.
    Detractors of Searle’s Chinese Room Argument have arrived at a virtual consensus that the mental properties of the Man performing the computations stipulated by the argument are irrelevant to whether computational cognitive science is true. This paper challenges this virtual consensus to argue for the first of the two main theses of the persons reply, namely, that the mental properties of the Man are what matter. It does this by challenging many of the arguments and conceptions put forth by the (...)
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  46. Computers, Persons, and the Chinese Room. Part 2: Testing Computational Cognitive Science.Ricardo Restrepo - 2012 - Journal of Mind and Behavior 33 (3):123-140.
    This paper is a follow-up of the first part of the persons reply to the Chinese Room Argument. The first part claims that the mental properties of the person appearing in that argument are what matter to whether computational cognitive science is true. This paper tries to discern what those mental properties are by applying a series of hypothetical psychological and strengthened Turing tests to the person, and argues that the results support the thesis that the Man performing the computations (...)
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  47. Searle and the Chinese Room Argument.Leslie Burkholder - 2011 - In Michael Bruce & Steven Barbone, Just the Arguments. Chichester, West Sussex, U.K.: Wiley-Blackwell. pp. 334–336.
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  48. Helen Keller Was Never in a Chinese Room.Jason Ford - 2011 - Minds and Machines 21 (1):57-72.
    William Rapaport, in “How Helen Keller used syntactic semantics to escape from a Chinese Room,” (Rapaport 2006), argues that Helen Keller was in a sort of Chinese Room, and that her subsequent development of natural language fluency illustrates the flaws in Searle’s famous Chinese Room Argument and provides a method for developing computers that have genuine semantics (and intentionality). I contend that his argument fails. In setting the problem, Rapaport uses his own preferred definitions of semantics and syntax, but he (...)
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  49. Intencionalidad sin naturalismo biológico.Ivar Hannikainen - 2011 - Revista de Filosofía (Madrid) 36 (1):139-153.
    The Chinese Room argument is a variant of Turing’s test which enables Searle to defend his biological naturalism, according to which computation is neither sufficient nor constitutive of the mind. In this paper, I examine both strands of his anticomputationalist stance, argue that computation is constitutive of natural language understanding and suggest a path toward the physicalist reduction of intentionality for propositional speech acts.
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  50. Searle’s wager.Neil Levy - 2011 - AI and Society 26 (4):363-369.
    Nicholas Agar has recently argued that it would be irrational for future human beings to choose to radically enhance themselves by uploading their minds onto computers. Utilizing Searle’s argument that machines cannot think, he claims that uploading might entail death. He grants that Searle’s argument is controversial, but he claims, so long as there is a non-zero probability that uploading entails death, uploading is irrational. I argue that Agar’s argument, like Pascal’s wager on which it is modelled, fails, because the (...)
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