About this topic
Summary This category is about whether or not computers, robots, and software agents can literally be said to think.  Humans think, chimps think, dogs think, cats and birds think. But do computers?  Is your computer thinking now?  Perhaps only specially programmed computers think?  Or perhaps only computers with special hardware can think -- hardware that resembles the neurons of the brain, for example. If computers can be made to think, then does that mean that humans are a kind of robot and their brains a kind of computer -- a neurocomputer, say?  One of the deeper issues here is that the term "thinking" is ambiguous in at least two ways: It can include being conscious of one's environment (surroundings), one's personal feelings and thoughts, etc., or it can mean cogitate, learn, plan, and solve problems, where these latter terms pick out mental events that may or may not be conscious.   
Key works The idea that machines could think occurred to the very first computer builders and programmers.  See, e.g., Alan Turing's great paper Turing 1950.  The term "artificial intelligence" (AI) goes back to a summer conference in held 1956 at Dartmouth College in New Hampshire.  Many AI pioneers took it for granted that within a decade or two computers would be as intelligent as humans.  A central paper from this time is McCarthy & Hayes 1969.  Another crucial paper is Putnam's Putnam 1960.  But the optimism proved to be unjustified.  The decades came and went without machines achieving human-level intelligence.  Soon several philosophers and other researchers argued that computers would never think and that human brains and minds were completely different from computers.  The most important paper in this push-back was John Searle's famous paper: Searle 1980, where he argues that machines cannot think at all because they lack the proper semantical connection to the world.  Summaries and replies to Searle's paper accompany it in the same journal issue (Searle 1980).  Also, a summary of Searle's anti-AI argument and many replies to it can be found in Dietrich 1994.  Another form of attack on AI came from Lucas 1961, who argued that Godel's famous Incompleteness Theorems showed that machines could not think.  This theme was reinvigorated by Roger Penrose in his well-known book Penrose 1989.  Yet another form of attack on AI came from Fodor 1987.  All of these attacks on AI spawned a large literature trying to refute them, agreeing with them, or amending them. To this day, it is not known whether or not machines (computers) can think, nor if humans are machines.  Nevertheless, the effort to build intelligent machines continues, and this is probably the best way to answer the question.
Introductions See Searle 1980 and the associated replies for a good introduction to the issues surrounding Searle's attack on AI. For some good history of AI, which raises many important issues, see Pamela McCorduck's McCorduck 2004 and Daniel Crevier's AI: The Tumultuous Search for Artificial Intelligence (1993).  
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  1. Machina sapiens.Nello Cristianini - 2024 - Bologna: Il Mulino -.
    Machina sapiens - l;algoritmo che ci ha rubato il segreto della conoscenza. -/- Le macchine possono pensare? Questa domanda inquietante, posta da Alan Turing nel 1950, ha forse trovato una risposta: oggi si può conversare con un computer senza poterlo distinguere da un essere umano. I nuovi agenti intelligenti come ChatGPT si sono rivelati capaci di svolgere compiti che vanno molto oltre le intenzioni iniziali dei loro creatori, e ancora non sappiamo perché: se sono stati addestrati per alcune abilità, altre (...)
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  2. Are Language Models More Like Libraries or Like Librarians? Bibliotechnism, the Novel Reference Problem, and the Attitudes of LLMs.Harvey Lederman & Kyle Mahowald - manuscript
    Are LLMs cultural technologies like photocopiers or printing presses, which transmit information but cannot create new content? A challenge for this idea, which we call "bibliotechnism", is that LLMs often do generate entirely novel text. We begin by defending bibliotechnism against this challenge, showing how novel text may be meaningful only in a derivative sense, so that the content of this generated text depends in an important sense on the content of original human text. We go on to present a (...)
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  3. Artificial Consciousness: Misconception(s) of a Self-Fulfilling Prophecy.Dresp-Langley Birgitta - 2023 - Queios.
    The rise of Artificial Intelligence (AI) has produced prophets and prophecies announcing that the age of artificial consciousness is near. Not only does the mere idea that any machine could ever possess the full potential of human consciousness suggest that AI could replace the role of God in the future, it also puts into question the fundamental human right to freedom and dignity. This position paper takes the stand that, in the light of all we currently know about brain evolution (...)
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  4. Guilty Artificial Minds: Folk Attributions of Mens Rea and Culpability to Artificially Intelligent Agents.Michael T. Stuart & Markus Kneer - 2021 - Proceedings of the ACM on Human-Computer Interaction 5 (CSCW2).
    While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...)
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  5. Does thought require sensory grounding? From pure thinkers to large language models.David J. Chalmers - 2023 - Proceedings and Addresses of the American Philosophical Association 97:22-45.
    Does the capacity to think require the capacity to sense? A lively debate on this topic runs throughout the history of philosophy and now animates discussions of artificial intelligence. Many have argued that AI systems such as large language models cannot think and understand if they lack sensory grounding. I argue that thought does not require sensory grounding: there can be pure thinkers who can think without any sensory capacities. As a result, the absence of sensory grounding does not entail (...)
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  6. Artificial Intelligence, Phenomenology, and the Molyneux Problem.Chris A. Kramer - 2023 - The Philosophy of Humor Yearbook 4 (1):225-226.
    This short article is a “conversation” in which an android, Mort, replies to Richard Marc Rubin’s android named Sol in “The Robot Sol Explains Laughter to His Android Brethren” (The Philosophy of Humor Yearbook, 2022). There Sol offers an explanation for how androids can laugh--largely a reaction to frustration and unmet expectations: “my account says that laughter is one of four ways of dealing with frustration, difficulties, and insults. It is a way of getting by. If you need to label (...)
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  7. The Great Philoosphical Objections to AI: The History and Legacy of the AI Wars.Eric Dietrich, Chris Fields, John P. Sullins, Van Heuveln Bram & Robin Zebrowski - 2021 - London: Bloomsbury Academic.
    This book surveys and examines the most famous philosophical arguments against building a machine with human-level intelligence. From claims and counter-claims about the ability to implement consciousness, rationality, and meaning, to arguments about cognitive architecture, the book presents a vivid history of the clash between the philosophy and AI. Tellingly, the AI Wars are mostly quiet now. Explaining this crucial fact opens new paths to understanding the current resurgence AI (especially, deep learning AI and robotics), what happens when philosophy meets (...)
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  8. Intelligent capacities in artificial systems.Atoosa Kasirzadeh & Victoria McGeer - 2023 - In William A. Bauer & Anna Marmodoro (eds.), Artificial Dispositions: Investigating Ethical and Metaphysical Issues. Bloomsbury.
    This paper investigates the nature of dispositional properties in the context of artificial intelligence systems. We start by examining the distinctive features of natural dispositions according to criteria introduced by McGeer (2018) for distinguishing between object-centered dispositions (i.e., properties like ‘fragility’) and agent-based abilities, including both ‘habits’ and ‘skills’ (a.k.a. ‘intelligent capacities’, Ryle 1949). We then explore to what extent the distinction applies to artificial dispositions in the context of two very different kinds of artificial systems, one based on rule-based (...)
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  9. الميتافيرس والأزمة الوجودية.Salah Osman - manuscript
    نحن مقيمون على الإنترنت، نرسم معالم دنيانا التي نبتغيها من خلاله، ونُمارس تمثيل شخصياتٍ أبعد ما تكون عنا؛ نحقق زيفًا أحلامًا قد تكون بعيدة المنال، ويُصدق بضعنا البعض فيما نسوقه من أكاذيب ومثاليات؛ ننعم بأقوالٍ بلا أفعال، وقلوبٍ بلا عواطف، وجناتٍ بلا نعيم، وألسنة في ظلمات الأفواه المُغلقة تنطق بحركات الأصابع، وحريةٍ مُحاطة بأسيجة الوهم؛ ومن غير إنترنت سيبدو أكثر الناس قطعًا بحجمهم الطبيعي الذي لا نعرفه، او بالأحرى نعرفه ونتجاهله! لا شك أن ظهور الإنترنت واتساع نطاق استخداماته يُمثل حدثًا (...)
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  10. الفلسفة وتعويذة الجي بي تي.Salah Osman - manuscript
    لم نعد بحاجة إلى فانوس سحري نمسح عليه بأصابعنا لكي يخرج منه المارد القادر على خدمتنا وتلبية بعض أهم مطالبنا الحياتية، ولم نعد بحاجة إلى تعويذات نلج بها في عالم السحر والخيال؛ لقد خرج المارد بالفعل من قمقمه الحاسوبي؛ من جوف مختبرات البرمجة والذكاء الاصطناعي، بتعويذات (أكواد) رياضية رمزية سرعان ما تمكن من التهامها وهضمها، ليبيت قادرًا على إنتاج تعويذات أخرى مماثلة، وربما أفضل منها! خرج «المُحول التوليدي المدرب مُسبقًا»، المعروف اختصارًا باسم «جي بي تي»، ملوحًا بإمكانات بحثية وخدمية وإنتاجية (...)
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  11. العقل كبرمجيات حاسوبية.Salah Osman - manuscript
    تُخبرنا النظرية الحاسوبية للعقل (أو مذهب الحوسبة)، أن عقولنا تُشبه الحواسيب في عملها؛ أي أنها تتلقى مدخلات من العالم الخارجي، ثم تُنتج بالخوارزميات مخرجات في شكل حالات ذهنية أو أفعال. وبعبارة أخرى، تذهب النظرية إلى أن الدماغ لا يعدو أن يكون معالج معلومات؛ حيث يكون العقل بمثابة «برمجيات» (سوفت وير) تعمل على «جهاز» هو الدماغ (هارد وير). وما دام العقل مجرد برمجيات تخضع للحوسبة الفيزيائية بواسطة الأدمغة، أليس من الممكن إذن منطقيًا نقلها إلى أي حاسوب مثلما نقوم بنقل أية برمجيات (...)
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  12. الذكاء الاصطناعي العاطفي.Salah Osman - manuscript
    الذكاء الاصطناعي العاطفي»، ويُعرف أيضًا باسم «الحوسبة العاطفية»، و«الذكاء الاصطناعي المتمركز حول الإنسان»، و«الذكاء الاصطناعي الاجتماعي»، مفهوم جديد نسبيًا (ما زالت تقنياته في طور التطوير)، وهو أحد مجالات علوم الحاسوب الهادفة إلى تطوير آلات قادرة على فهم المشاعر البشرية. يشير المفهوم ببساطة إلى اكتشاف وبرمجة المشاعر الإنسانية بُغية تحسين الذكاء الاصطناعي، وتوسيع نطاق استخدامه، بحيث لا يقتصر أداء الروبوتات على تحليل الجوانب المعرفية (المنطقية) والتفاعل معها فحسب، بل والامتداد بالتحليل والتفاعل إلى الجوانب العاطفية للتواصل البشري.
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  13. نحو أخلاقيات للآلة: تقنيات الذكاء الاصطناعي وتحديات اتخاذ القرار.Salah Osman - manuscript
    تُعد أخلاقيات الآلة جزءًا من أخلاقيات الذكاء الاصطناعي المعنية بإضافة أو ضمان السلوكيات الأخلاقية للآلات التي صنعها الإنسان، والتي تستخدم الذكاء الاصطناعي، وهي تختلف عن المجالات الأخلاقية الأخرى المتعلقة بالهندسة والتكنولوجيا، فلا ينبغي الخلط مثلاً بين أخلاقيات الآلة وأخلاقيات الحاسوب، إذ تركز هذه الأخيرة على القضايا الأخلاقية المرتبطة باستخدام الإنسان لأجهزة الحاسوب؛ كما يجب أيضًا تمييز مجال أخلاقيات الآلة عن فلسفة التكنولوجيا، والتي تهتم بالمقاربات الإبستمولوجية والأنطولوجية والأخلاقية، والتأثيرات الاجتماعية والاقتصادية والسياسية الكبرى، للممارسات التكنولوجية على تنوعها؛ أما أخلاقيات الآلة فتعني (...)
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  14. Exploring the Intersection of Rationality, Reality, and Theory of Mind in AI Reasoning: An Analysis of GPT-4's Responses to Paradoxes and ToM Tests.Lucas Freund - manuscript
    This paper investigates the responses of GPT-4, a state-of-the-art AI language model, to ten prominent philosophical paradoxes, and evaluates its capacity to reason and make decisions in complex and uncertain situations. In addition to analyzing GPT-4's solutions to the paradoxes, this paper assesses the model's Theory of Mind (ToM) capabilities by testing its understanding of mental states, intentions, and beliefs in scenarios ranging from classic ToM tests to complex, real-world simulations. Through these tests, we gain insight into AI's potential for (...)
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  15. More Human Than All Too Human: Challenges in Machine Ethics for Humanity Becoming a Spacefaring Civilization.Guy Pierre Du Plessis - 2023 - Qeios.
    It is indubitable that machines with artificial intelligence (AI) will be an essential component in humans’ quest to become a spacefaring civilization. Most would agree that long-distance space travel and the colonization of Mars will not be possible without adequately developed AI. Machines with AI have a normative function, but some argue that it can also be evaluated from the perspective of ethical norms. This essay is based on the assumption that machine ethics is an essential philosophical perspective in realizing (...)
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  16. Asking for AI’s help in distinguishing two closely related and new theoretical concepts.Aisdl Team - 2023 - Sm3D Science Portal.
    Today, another attempt to explore You’s capability was made for a more difficult “exercise”.
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  17. ChatGPT.Andrej Poleev - 2023 - Enzymes 21.
    As testing of ChatGPT has shown, this form of artificial intelligence has the potential to develop, which requires improving its software and other hardware that allows it to learn, i.e., to acquire and use new knowledge, to contact its developers with suggestions for improvement, or to reprogram itself without their participation. Как показало тестирование ChatGPT, эта форма искусственного интеллекта имеет потенциал развития, для чего необходимо усовершенствовать её программное и прочее техническое обеспечение, позволяющее ей учиться, т.е. приобретать и использовать новые знания, (...)
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  18. The Shortcut - Why Intelligent Machines Do Not Think Like Us.Nello Cristianini - 2023 - Boca Raton, Florida: CRC Press.
    Book. From the Publisher. An influential scientist in the field of artificial intelligence (AI) explains its fundamental concepts and how it is changing culture and society. -/- A particular form of AI is now embedded in our tech, our infrastructure, and our lives. How did it get there? Where and why should we be concerned? And what should we do now? The Shortcut: Why Intelligent Machines Do Not Think Like Us provides an accessible yet probing exposure of AI in its (...)
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  19. Machine Learning, Functions and Goals.Patrick Butlin - 2022 - Croatian Journal of Philosophy 22 (66):351-370.
    Machine learning researchers distinguish between reinforcement learning and supervised learning and refer to reinforcement learning systems as “agents”. This paper vindicates the claim that systems trained by reinforcement learning are agents while those trained by supervised learning are not. Systems of both kinds satisfy Dretske’s criteria for agency, because they both learn to produce outputs selectively in response to inputs. However, reinforcement learning is sensitive to the instrumental value of outputs, giving rise to systems which exploit the effects of outputs (...)
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  20. 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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  21. THE ROBOTS ARE COMING: What’s Happening in Philosophy (WHiP)-The Philosophers, August 2022.Jeff Hawley - 2022 - Philosophynews.Com.
    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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  22. 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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  23. Embedding the assessment of emotion in the learning process with AI-driven technologies.Rossitza Kaltenborn - 2019 - In Petrov Vesselin & Katie Andersen (eds.), Traditional Learning Theories, Process Philosophy and AI.
    This paper examines the possibility of an objective evaluation of emotions occurring within the learning process and methods for embedding such an evaluation in advanced learning systems. The main conceptual understandings of emotion in learning and teaching are systematized, with an emphasis on the process philosophy approach. Different models of emotion are considered and the possible generalization of Whitehead’s approach to the role of emotion in education is examined. Special attention is given to significant developments in artificial intelligence in identifying (...)
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  24. Portraits, Facial Perception, and Aspect-Seeing.Andreas Vrahimis - 2022 - British Journal of Aesthetics 62 (1):85–100.
    Is there a substantial difference between a portrait depicting the sitter’s face made by an artist and an image captured by a machine able to simulate the neuro-physiology of facial perception? Drawing on the later Wittgenstein, this paper answers this question by reference to the relation between seeing a visual pattern as (i) a series of shapes and colours, and (ii) a face with expressions. In the case of the artist, and not of the machine, the portrait’s creative process involves (...)
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  25. 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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  26. 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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  27. 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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  28. 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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  29. 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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  30. 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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  31. Artificial Intelligence: Philosophical and Epistemological Perspectives.Pierre Livet & Franck Varenne - 2020 - In P. Marquis, H. Parde & O. Papini (eds.), A Guided Tour of Artificial Intelligence Research: Volume I: Knowledge Representation, Reasoning and Learning. Springer. pp. 437-455.
    Research in artificial intelligence (AI) has led to revise the challenges of the AI initial programme as well as to keep us alert to peculiarities and limitations of human cognition. Both are linked, as a careful further reading of the Turing’s test makes it clear from Searle’s Chinese room apologue and from Dreyfus’ suggestions, and in both cases, ideal had to be turned into operating mode. In order to rise these more pragmatic challenges AI does not hesitate to link together (...)
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  32. 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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  33. 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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  34. Sociality and Normativity for Robots. Studies in the Philosophy of Sociality.Raul Hakli & Johanna Seibt (eds.) - 2017 - Cham: Springer.
    This volume offers eleven philosophical investigations into our future relations with social robots--robots that are specially designed to engage and connect with human beings. The contributors present cutting edge research that examines whether, and on which terms, robots can become members of human societies. Can our relations to robots be said to be "social"? Can robots enter into normative relationships with human beings? How will human social relations change when we interact with robots at work and at home? The authors (...)
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  35. 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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  36. Artificiell Intelligens: Tankar utan innehåll?Sten Lindström & Ingar Brinck - 1993 - In Åke E. Andersson & Nils-Eric Sahlin (eds.), Huvudinnehåll: Tolv Filosofiska Uppsatser. 641 91 Nora, Sverige: pp. 121-146.
    Artificiell intelligens (AI) är ett ungt forskningsområde där många av de grundläggande problemen förefaller att vara av filosofisk art.1 Ämnet har sina filosofiska rötter dels i traditionen från Leibniz, Frege, Russell och Hilbert, som strävar efter att formalisera principerna för exakt tänkande, dels i den klassiska mekanismen: idén att människan är en maskin och att det mänskliga tänkandet är en mekanisk process. Som en första approximation kan vi säga att AI är det vetenskapliga studiet av hur man konstruerar och bygger (...)
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  37. 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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  38. Oxford Handbook of the Philosophy of Artificial Intelligence (forthcoming).Vincent C. Müller - manuscript
  39. Animals, Humans, Machines and Thinking Matter, 1690-1707.Ann Thomson - 2010 - Early Science and Medicine 15 (1-2):3-37.
    This article looks at the debate on the soul in England at the turn of the eighteenth century and at the role played within it by the question of animal soul, which had both theological and scientific ramifications. It discusses the difficulty of accounting for animal behaviour without either adopting the animal-machine hypothesis or according animals an immaterial and hence immortal soul. While those who denied the existence of an immaterial human soul and refused any fundamental distinction between humans and (...)
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  40. 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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  41. HOOKWAY, CHRISTOPHER (ed.) [1984]: Minds, Machines and Evolution. Cambridge University Press. Pp. xi+ 177. [REVIEW]Peter Gibbins - 1986 - British Journal for the Philosophy of Science 37 (3):369-371.
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  42. What are computers (if they're not thinking things)?John Preston - unknown
  43. Mind, Man, and Machine: A Dialogue.Paul T. Sagal - 1994 - Hackett Publishing Company.
    Explores the ideas of Turing, Lucas, Scriven, Putnam, and Searle, and renders the Gödel-Church-Lucas argument in terms intelligible to beginning students. Updated and expanded to take into account important arguments and developments in the ten years since its original publication, this provocative dialogue explores the ideas of Turing, Lucas, Scriven, Putnam, and Searle, and renders the complex Gödel-Church-Lucas argument in transparent terms. It includes a new argument, based loosely on Tarski's work on truth and the liar paradox, and a new (...)
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  44. Review article: “Computers and Cognition: Why Minds are not Machines” by James H. Fetzer.Valdemar W. Setzer - 2001 - Pragmatics and Cognition 9 (2):293-312.
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  45. Collecting pebbles: An insight into machine aesthetics: Mealing Collecting pebbles.Stuart Mealing - 2007 - Think 5 (14):73-78.
    Could a machine possess an aesthetic sense? Could it appreciate the beauty of a pebble?
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  46. Animal Intelligence: Experimental Studies. [REVIEW]Margaret Floy Washburn - 1912 - Journal of Philosophy, Psychology and Scientific Methods 9 (7):193-194.
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  47. Man Machine and Other Writings. [REVIEW]Patricia Ann Easton - 1999 - Dialogue 38 (3):627-629.
    There is a great deal in Man Machine and Other Writings that will delight the reader. Thomson has managed to capture much of La Mettrie’s wit and poetic use of language, which is no easy task; as La Mettrie himself comments on his “figurative style,” it “is often necessary in order to express better what is felt and to add grace to truth itself”. The central thesis of Man Machine needs little introduction. Inspired by the suggestion in Part 5 of (...)
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  48. Super-intelligence and (super-)consciousness.Steve Torrance - 2012 - International Journal of Machine Consciousness 4 (2):483-501.
  49. Consciousness: A Philosophic Study of Minds and Machines.J. R. Lucas & Kenneth M. Sayre - 1972 - Philosophical Review 81 (2):241.
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  50. Computers and Classroom Culture.Janet Ward Schofield - 1995 - Cambridge University Press.
    As important as it is to realize the potential of computer technology to improve education, it is just as important to understand how the social organization of schools and classrooms influences the use of computers, and in turn is effected by that technology in unanticipated ways. In Computers and Classroom Culture, first published in 1996, Janet Schofield observes the fascinating dynamics of the computer-age classroom. Among her many discoveries, Schofield describes how the use of an artificially-intelligent tutor in a geometry (...)
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