Results for 'Machine intelligence'

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  1.  14
    Situating Machine Intelligence Within the Cognitive Ecology of the Internet.Paul Smart - 2017 - Minds and Machines 27 (2):357-380.
    The Internet is an important focus of attention for the philosophy of mind and cognitive science communities. This is partly because the Internet serves as an important part of the material environment in which a broad array of human cognitive and epistemic activities are situated. The Internet can thus be seen as an important part of the ‘cognitive ecology’ that helps to shape, support and realize aspects of human cognizing. Much of the previous philosophical work in this area has sought (...)
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  2.  15
    From the Buzzing in Turing’s Head to Machine Intelligence Contests.Huma Shah & Kevin Warwick - 2010 - In TCIT 2010 / AISB 2010 Convention.
    This paper presents an analysis of three major contests for machine intelligence. We conclude that a new era for Turing’s test requires a fillip in the guise of a committed sponsor, not unlike DARPA, funders of the successful 2007 Urban Challenge.
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  3.  2
    Machine Intelligence and the Social Web: How to Get a Cognitive Upgrade.Paul Smart - 2017 - In Vincent Gripon, Olga Chernavskaya, Paul R. Smart & Tiago Thompsen Primo (eds.), 9th International Conference on Advanced Cognitive Technologies and Applications (COGNITIVE'17). Wilmington, DE, USA: pp. 96–103.
    The World Wide Web (Web) provides access to a global space of information assets and computational services. It also, however, serves as a platform for social interaction (e.g., Facebook) and participatory involvement in all manner of online tasks and activities (e.g., Wikipedia). There is a sense, therefore, that the advent of the Social Web has transformed our understanding of the Web. In addition to viewing the Web as a form of information repository, we are now able to view the Web (...)
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  4.  2
    The Social Scaffolding of Machine Intelligence.Paul Smart - 2017 - International Journal on Advances in Intelligent Systems 10 (3&4):261–279.
    The Internet provides access to a global space of information assets and computational services. It also, however, serves as a platform for social interaction (e.g., Facebook) and participatory involvement in all manner of online tasks and activities (e.g., Wikipedia). There is a sense, therefore, that the Internet yields an unprecedented form of access to the human social environment: it provides insight into the dynamics of human behavior (both individual and collective), and it additionally provides access to the digital products of (...)
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  5.  35
    Machine Intelligence and the Long-Term Future of the Human Species.Tom Stonier - 1988 - AI and Society 2 (2):133-139.
    Intelligence is not a property unique to the human brain; rather it represents a spectrum of phenomena. An understanding of the evolution of intelligence makes it clear that the evolution of machine intelligence has no theoretical limits — unlike the evolution of the human brain. Machine intelligence will outpace human intelligence and very likely will do so during the lifetime of our children. The mix of advanced machine intelligence with human individual (...)
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  6.  24
    The Limits of Machine Intelligence.Henry Shevlin, Karina Vold, Matthew Crosby & Marta Halina - 2019 - EMBO Reports 49177 (20).
    Despite there being little consensus on what intelligence is or how to measure it, the media and the public have become increasingly preoccupied with the concept owing to recent accomplishments in machine learning and research on artificial intelligence (AI). Governments and corporations are investing billions of dollars to fund researchers who are keen to produce an ever‐expanding range of artificial intelligent systems. More than 30 countries have announced such research initiatives over the past 3 years 1. For (...)
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  7. How Godel's Theorem Supports the Possibility of Machine Intelligence.Taner Edis - 1998 - Minds and Machines 8 (2):251-262.
    Gödel's Theorem is often used in arguments against machine intelligence, suggesting humans are not bound by the rules of any formal system. However, Gödelian arguments can be used to support AI, provided we extend our notion of computation to include devices incorporating random number generators. A complete description scheme can be given for integer functions, by which nonalgorithmic functions are shown to be partly random. Not being restricted to algorithms can be accounted for by the availability of an (...)
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  8. Turing on the Integration of Human and Machine Intelligence.S. G. Sterrett - manuscript
    Abstract Philosophical discussion of Alan Turing’s writings on intelligence has mostly revolved around a single point made in a paper published in the journal Mind in 1950. This is unfortunate, for Turing’s reflections on machine (artificial) intelligence, human intelligence, and the relation between them were more extensive and sophisticated. They are seen to be extremely well-considered and sound in retrospect. Recently, IBM developed a question-answering computer (Watson) that could compete against humans on the game show Jeopardy! (...)
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  9. Unraveling Trie Enigma of Human Intelligence: Evolutionary Psychology and the Multimodular Mind.Of Intelligence - 2002 - In Robert J. Sternberg & J. Kaufman (eds.), The Evolution of Intelligence. Lawrence Erlbaum. pp. 145.
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  10. Universal Intelligence: A Definition of Machine Intelligence.Shane Legg & Marcus Hutter - 2007 - Minds and Machines 17 (4):391-444.
    A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: we take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of (...) for arbitrary machines. We believe that this equation formally captures the concept of machine intelligence in the broadest reasonable sense. We then show how this formal definition is related to the theory of universal optimal learning agents. Finally, we survey the many other tests and definitions of intelligence that have been proposed for machines. (shrink)
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  11. Economic Growth Given Machine Intelligence.Robin Hanson - unknown
    A simple exogenous growth model gives conservative estimates of the economic implications of machine intelligence. Machines complement human labor when they become more productive at the jobs they perform, but machines also substitute for human labor by taking over human jobs. At first, expensive hardware and software does only the few jobs where computers have the strongest advantage over humans. Eventually, computers do most jobs. At first, complementary effects dominate, and human wages rise with computer productivity. But eventually (...)
     
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  12.  37
    Machine Intelligence (MI), Competence and Creativity.Rajakishore Nath - 2009 - AI and Society 23 (3):441-458.
    In mid-twentieth century, the hypothesis, ‘a machine can think’ became very popular after, Alan Turing’s article on ‘Computing Machinery and Intelligence’. This hypothesis, ‘a machine can think’ established the foundations of machine intelligence (MI), and claimed that machines have consciousness and creativity, with the power to compete with human beings. In the first section, I shall show how consciousness and creativity is conceptualized in the domain of MI. The main aim of MI is not only (...)
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  13. Donald Michie: Machine Intelligence, Biology and More.Ashwin Srinivasan - 2009 - Oxford University Press.
    Donald Michie was many things; a computing pioneer in machine intelligence, a cryptographer who made key breakthroughs at Bletchley Park, and a geneticist. Tragically, two years ago he died in a car crash. Here, Ashwin Srinivasan presents an engaging collection of lively essays from Michie's writings, on thinking computers, mice, and much more.
     
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  14.  64
    Machine Intelligence: A Chimera.Mihai Nadin - 2019 - AI and Society 34 (2):215-242.
    The notion of computation has changed the world more than any previous expressions of knowledge. However, as know-how in its particular algorithmic embodiment, computation is closed to meaning. Therefore, computer-based data processing can only mimic life’s creative aspects, without being creative itself. AI’s current record of accomplishments shows that it automates tasks associated with intelligence, without being intelligent itself. Mistaking the abstract for the concrete has led to the religion of “everything is an output of computation”—even the humankind that (...)
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  15. Machine Intelligence: Perspectives on the Computational Model.Andy Clark & Josefa Toribio (eds.) - 1998 - Routledge.
    First published in 1998. Routledge is an imprint of Taylor & Francis, an informa company.
     
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  16.  28
    Animal Automatism and Machine Intelligence.Deborah Brown - 2015 - Res Philosophica 92 (1):93-115.
    Descartes’s uncompromising rejection of the possibility of animal intelligence was among his most controversial theses. That rejection is based on his commitment to the doctrine of animal automatism and two tests that he takes to be sufficient indicators of thought. Of these two tests, only the language test is truly definitive, and Descartes is firmly of the view that no animal could demonstrate the capacity to use signs to convey meaning in “all the circumstances of life.” The topic is (...)
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  17.  48
    Mindless Thought Experiments (a Critique of Machine Intelligence).Jaron Lanier - manuscript
    Since there isn't a computer that seems conscious at this time, the idea of machine consciousness is supported by thought experiments. Here's one old chestnut: "What if you replaced your neurons one by one with neuron sized and shaped substitutes made of silicon chips that perfectly mimicked the chemical and electric functions of the originals? If you just replaced one single neuron, surely you'd feel the same. As you proceed, as more and more neurons are replaced, you'd stay conscious. (...)
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  18.  30
    Intelligence Unbound: The Future of Uploaded and Machine Minds.Russell Blackford & Damien Broderick (eds.) - 2014 - Wiley-Blackwell.
    _Intelligence Unbound_ explores the prospects, promises, and potential dangers of machine intelligence and uploaded minds in a collection of state-of-the-art essays from internationally recognized philosophers, AI researchers, science fiction authors, and theorists. Compelling and intellectually sophisticated exploration of the latest thinking on Artificial Intelligence and machine minds Features contributions from an international cast of philosophers, Artificial Intelligence researchers, science fiction authors, and more Offers current, diverse perspectives on machine intelligence and uploaded minds, emerging (...)
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  19. Future Progress in Artificial Intelligence: A Survey of Expert Opinion.Vincent C. Müller & Nick Bostrom - 2016 - In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence. Springer. pp. 553-571.
    There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see (...)
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  20. Complexity and the Study of Human and Machine Intelligence.Z. W. Pylyshyn - 1981 - In J. Haugel (ed.), Mind Design. MIT Press.
  21. Machine Intelligence 4.Bernard Meltzer & Donald Michie - 1970 - British Journal for the Philosophy of Science 21 (2):212-214.
     
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  22.  15
    International Stability in a Digital World: Emerging Trends in Machine Intelligence, Environmental Sustainability and Society.Larry Stapleton - 2018 - AI and Society 33 (2):159-162.
  23.  35
    Evolutionary Computation: Toward a New Philosophy of Machine Intelligence.Thomas B.�ck - 1997 - Complexity 2 (4):28-30.
  24. Imagination and Machine Intelligence.James Mensch - unknown
    The question of the imagination is rather like the question Augustine raised with regard to the nature of time. We all seem to know what it involves, yet find it difficult to define. For Descartes, the imagination was simply our faculty for producing a mental image. He distinguished it from the understanding by noting that while the notion of a thousand sided figure was comprehensible—that is, was sufficiently clear and distinct to be differentiated from a thousand and one sided figure—the (...)
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  25.  8
    Alex Roland. Strategic Computing: DARPA and the Quest for Machine Intelligence, 1983–1993. With Philip Shiman. 453 Pp., Illus., Index. Cambridge, Mass.: MIT Press, 2002. [REVIEW]Chris Hables Gray - 2006 - Isis 97 (1):188-189.
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  26. Machine Intelligence 1.N. L. Collins, D. Michie & E. Dale - 1968 - British Journal for the Philosophy of Science 19 (3):271-274.
  27.  7
    Alex Roland with Philip Shiman, Strategic Computing: Darpa and the Quest for Machine Intelligence, 1983–1993. History of Computing. Cambridge, Ma and London: MIT Press, 2002. Pp. XXVI+427. Isbn 0-262-18226-2. £33.50. [REVIEW]James Sumner - 2006 - British Journal for the History of Science 39 (4):622-624.
  28. Human Versus Machine Intelligence.Robin Gandy - 1996 - In Peter Millican Andy Clark (ed.), Machines and Thought the Legacy of Alan Turing. pp. 1--125.
  29. Machine Intelligence 4.B. Meltzer & Donald Michie (eds.) - 1969 - Edinburgh University Press.
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  30. Machine Intelligence 7.B. Meltzer, D. Michie, R. C. Schank & K. M. Colby - 1975 - British Journal for the Philosophy of Science 26 (3):269-273.
  31. Turing on the Integration of Human and Machine Intelligence.Susan Sterrett - 2017 - In Alisa Bokulich & Juliet Floyd (eds.), Philosophical Explorations of the Legacy of Alan Turing. Springer Verlag.
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  32. The problem of machine ethics in artificial intelligence.Rajakishore Nath & Vineet Sahu - 2020 - AI and Society 35 (1):103-111.
    The advent of the intelligent robot has occupied a significant position in society over the past decades and has given rise to new issues in society. As we know, the primary aim of artificial intelligence or robotic research is not only to develop advanced programs to solve our problems but also to reproduce mental qualities in machines. The critical claim of artificial intelligence advocates is that there is no distinction between mind and machines and thus they argue that (...)
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  33. The Intelligence of a Machine.Jean Epstein - 2014 - Univocal Publishing.
    The advent of the cinema radically altered our comprehension of time, space, and reality. With his experience as a pioneering avant-garde filmmaker, Jean Epstein uses the universes created by the cinematograph to deconstruct our understanding of how time and space, reality and unreality, continuity and discontinuity, determinism and randomness function both inside and outside the cinema. Time, he says, should be regarded as the first, not the fourth, dimension—and the cinematograph allows us, for the first time, to manipulate it in (...)
     
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  34.  50
    The Mind And The Machine: Philosophical Aspects Of Artificial Intelligence.Steven Torrance (ed.) - 1984 - Chichester: Horwood.
  35.  7
    Social Intelligence in a Human-Machine Collaboration System.Hiroshi Nakajima, Yasunori Morishima, Ryota Yamada, Scott Brave, Heidy Maldonado, Clifford Nass & Shigeyasu Kawaji - 2004 - Transactions of the Japanese Society for Artificial Intelligence 19:184-196.
  36.  17
    How Bioethics Can Shape Artificial Intelligence and Machine Learning.Junaid Nabi - 2018 - Hastings Center Report 48 (5):10-13.
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  37. Natural and Machine Learning, Intelligence, and Consciousness.Igor Kononenko - 2009 - In Eva Zerovnik, Olga Markič & A. Ule (eds.), Philosophical Insights About Modern Science. Nova Science Publishers.
  38.  15
    A Developmental Pattern of Artificial Intelligence Based on the Blend of Man and Machine.Gong Yingfu - 1988 - AI and Society 2 (4):356-360.
  39.  7
    Between Logos and Doxa: The Intelligence of a Machine.German A. Duarte - 2016 - Human and Social Studies 5 (1):113-134.
    This paper deals with Parmenides of Elea’s way of inquiry about reality and the opposition emerging from it. In more detail, it analyses how Parmenides’ concepts of logos and doxa present some analogies with Bergson’s thoughts about duration and Time and how these theories influenced the understanding of visual media, especially the cinematographic camera. This survey will allow us to demonstrate that some scientific theories about space that accompanied the development of the cinematographic camera progressively allowed for the birth of (...)
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  40.  11
    Mind, Machine, and Metaphor: An Essay on Artificial Intelligence and Legal Reasoning.Laurence Goldstein - 1995 - Philosophical Books 36 (2):134-136.
  41.  8
    Réflexion épistémologique sur l'intelligence artificielle et les sciences cognitives : à quelles conditions une machine pourrait-elle connaître?Serge Robert - 1992 - Horizons Philosophiques 2 (2):167-184.
  42. A Speculative Machine,(Information, Artificial-Intelligence and Cognitive Research).M. Borillo - 1990 - Revue Internationale de Philosophie 44 (172):47-61.
  43. Une machine spéculative (informatique, intelligence artificielle et recherche cognitive).Mario Borillo - 1990 - Revue Internationale de Philosophie 44 (172):47.
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  44. L'esprit dans la machine : fondements de l'intelligence artificielle.J. Haugeland - 1992 - Revue Philosophique de la France Et de l'Etranger 182 (1):112-115.
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  45.  52
    Bringing Up Turing's 'Child-Machine'.Susan G. Sterrett - 2012 - In S. Barry Cooper (ed.), How the World Computes. pp. 703--713.
    Turing wrote that the “guiding principle” of his investigation into the possibility of intelligent machinery was “The analogy [of machinery that might be made to show intelligent behavior] with the human brain.” [10] In his discussion of the investigations that Turing said were guided by this analogy, however, he employs a more far-reaching analogy: he eventually expands the analogy from the human brain out to “the human community as a whole.” Along the way, he takes note of an obvious fact (...)
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  46. On Potential Cognitive Abilities in the Machine Kingdom.José Hernández-Orallo & David L. Dowe - 2013 - Minds and Machines 23 (2):179-210.
    Animals, including humans, are usually judged on what they could become, rather than what they are. Many physical and cognitive abilities in the ‘animal kingdom’ are only acquired (to a given degree) when the subject reaches a certain stage of development, which can be accelerated or spoilt depending on how the environment, training or education is. The term ‘potential ability’ usually refers to how quick and likely the process of attaining the ability is. In principle, things should not be different (...)
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  47.  44
    The Future of Human-Artificial Intelligence Nexus and its Environmental Costs.Petr Spelda & Vit Stritecky - forthcoming - Futures.
    The environmental costs and energy constraints have become emerging issues for the future development of Machine Learning (ML) and Artificial Intelligence (AI). So far, the discussion on environmental impacts of ML/AI lacks a perspective reaching beyond quantitative measurements of the energy-related research costs. Building on the foundations laid down by Schwartz et al., 2019 in the GreenAI initiative, our argument considers two interlinked phenomena, the gratuitous generalisation capability and the future where ML/AI performs the majority of quantifiable inductive (...)
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  48.  86
    Intelligence is Not Enough: On the Socialization of Talking Machines. [REVIEW]E. Ronald & Moshe Sipper - 2001 - Minds and Machines 11 (4):567-576.
    Since the introduction of the imitation game by Turing in 1950 there has been much debate as to its validity in ascertaining machine intelligence. We wish herein to consider a different issue altogether: granted that a computing machine passes the Turing Test, thereby earning the label of ``Turing Chatterbox'', would it then be of any use (to us humans)? From the examination of scenarios, we conclude that when machines begin to participate in social transactions, unresolved issues of (...)
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  49. Machine Intentionality, the Moral Status of Machines, and the Composition Problem.David Leech Anderson - 2012 - In Vincent C. Müller (ed.), Philosophy & Theory of Artificial Intelligence. Springer. pp. 312-333.
    According to the most popular theories of intentionality, a family of theories we will refer to as “functional intentionality,” a machine can have genuine intentional states so long as it has functionally characterizable mental states that are causally hooked up to the world in the right way. This paper considers a detailed description of a robot that seems to meet the conditions of functional intentionality, but which falls victim to what I call “the composition problem.” One obvious way to (...)
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  50. Safety Engineering for Artificial General Intelligence.Roman Yampolskiy & Joshua Fox - 2013 - Topoi 32 (2):217-226.
    Machine ethics and robot rights are quickly becoming hot topics in artificial intelligence and robotics communities. We will argue that attempts to attribute moral agency and assign rights to all intelligent machines are misguided, whether applied to infrahuman or superhuman AIs, as are proposals to limit the negative effects of AIs by constraining their behavior. As an alternative, we propose a new science of safety engineering for intelligent artificial agents based on maximizing for what humans value. In particular, (...)
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