Search results for 'Artificial intelligence Social aspects' (try it on Scholar)

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  1. Maurits Kaptein, Panos Markopoulos, Boris Ruyter & Emile Aarts (2011). Two Acts of Social Intelligence: The Effects of Mimicry and Social Praise on the Evaluation of an Artificial Agent. [REVIEW] AI and Society 26 (3):261-273.score: 558.0
    This paper describes a study of the effects of two acts of social intelligence, namely mimicry and social praise, when used by an artificial social agent. An experiment ( N = 50) is described which shows that social praise—positive feedback about the ongoing conversation—increases the perceived friendliness of a chat-robot. Mimicry—displaying matching behavior—enhances the perceived intelligence of the robot. We advice designers to incorporate both mimicry and social praise when their system needs (...)
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  2. Richard Ennals (1987). Socially Useful Artificial Intelligence. AI and Society 1 (1):5-15.score: 538.5
    Artificial intelligence is presented as a set of tools with which we can try to come to terms with human problems, and with the assistance of which, some human problems can be solved. Artificial intelligence is located in its social context, in terms of the environment within which it is developed, and the applications to which it is put. Drawing on social theory, there is consideration of the collaborative and social problem-solving processes which (...)
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  3. Raimo Tuomela (1996). Philosophy and Distributed Artificial Intelligence: The Case of Joint Intention. In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley.score: 522.0
    In current philosophical research the term 'philosophy of social action' can be used - and has been used - in a broad sense to encompass the following central research topics: 1) action occurring in a social context; this includes multi-agent action; 2) joint attitudes (or "we-attitudes" such as joint intention, mutual belief) and other social attitudes needed for the explication and explanation of social action; 3) social macro-notions, such as actions performed by social groups (...)
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  4. Steven Torrance (ed.) (1984). The Mind And The Machine: Philosophical Aspects Of Artificial Intelligence. Chichester: Horwood.score: 508.5
  5. Pompeu Casanovas Romeu (ed.) (2007). Trends in Legal Knowledge: The Semantic Web and the Regulation of Electronic Social Systems: Papers From the B-4 Workshop on Artificial Intelligence and Law, May 25th- 27th 2005: Xxii World Congress of Philosophy Ivr '05 Granada, May 24th-29th 2005. [REVIEW] European Press Academic Pub..score: 508.5
  6. Cristiano Castelfranchi & Rosaria Conte (1996). Distributed Artificial Intelligence and Social Science: Critical Issues. In N. Jennings & G. O'Hare (eds.), Foundations of Distributed Artificial Intelligence. Wiley.score: 468.0
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  7. Achille Ardigo (1988). Artificial Intelligence: A Contribution to Systems Theories of Sociology. [REVIEW] AI and Society 2 (2):113-120.score: 459.0
    The aim of my contribution is to try to analyse some points of similarity and difference between post-Parsonian social systems theory models for sociology — with special reference to those of W. Buckley, F.E. Emery and N. Luhmann — and expert systems models1 from Artificial Intelligence. I keep specifically to post-Parsonian systems theories within sociology because they assume some postulates and criteria derived from cybernetics and which are at the roots of AI. I refer in particular to (...)
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  8. Maria Miceli, Amedo Cesta & Paola Rizzo (1995). Distributed Artificial Intelligence From a Socio-Cognitive Standpoint: Looking at Reasons for Interaction. [REVIEW] AI and Society 9 (4):287-320.score: 459.0
    Distributed Artificial Intelligence (DAI) deals with computational systems where several intelligent components interact in a common environment. This paper is aimed at pointing out and fostering the exchange between DAI and cognitive and social science in order to deal with the issues of interaction, and in particular with the reasons and possible strategies for social behaviour in multi-agent interaction is also described which is motivated by requirements of cognitive plausibility and grounded the notions of power, dependence (...)
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  9. Tama Leaver (2011). Artificial Culture: Identity, Technology and Bodies. Routledge.score: 456.0
  10. Bruce Edmonds, The Social Embedding of Intelligence.score: 438.0
    I claim that in order to pass the Turing Test over any period of extended time, it will necessary to embed the entity into society. This chapter discusses why this is, and how it might be brought about. I start by arguing that intelligence is better characterised by tests of social interaction, especially in open-ended and extended situations. I then argue that learning is an essential component of intelligence and hence that a universal intelligence is impossible. (...)
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  11. M. A. Boden (1990). The Social Impact of Artificial Intelligence. In R. Kurzweil (ed.), The Age of Intelligent Machines. Mit Press. 450--453.score: 430.5
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  12. Pascal Acot, Sandrine Charles & Marie-Laure Delignette-Muller (2000). Artificial Intelligence and Meaning — Some Philosophical Aspects of Decision-Making. Acta Biotheoretica 48 (3-4).score: 427.5
  13. John Bryant (1991). Systems Theory and Scientific Philosophy: An Application of the Cybernetics of W. Ross Ashby to Personal and Social Philosophy, the Philosophy of Mind, and the Problems of Artificial Intelligence. University Press of America.score: 427.5
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  14. Thierry Chaminade, Delphine Rosset, David Da Fonseca, Bruno Nazarian, Ewald Lutcher, Gordon Cheng & Christine Deruelle (2012). How Do We Think Machines Think? An fMRI Study of Alleged Competition with an Artificial Intelligence. Frontiers in Human Neuroscience 6.score: 409.5
    Humans are particularly skilled in mentalizing, the inference of other agents’ hidden mental states. Here we question whether activity in brain areas involved in mentalizing is specific to the processing of mental states or can be generalized to the inference of non-mental states by investigating brain responses during the interaction with an artificial agent. Participants were scanned using fMRI during interactive rock-paper-scissors games while believing the opponent was a fellow human (Intentional agent), a humanoid robot endowed with an algorithm (...)
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  15. Christine Deruelle Thierry Chaminade, Delphine Rosset, David Da Fonseca, Bruno Nazarian, Ewald Lutcher, Gordon Cheng (2012). How Do We Think Machines Think? An fMRI Study of Alleged Competition with an Artificial Intelligence. Frontiers in Human Neuroscience 6.score: 409.5
    Humans are particularly skilled in mentalizing, the inference of other agents’ hidden mental states. Here we question whether activity in brain areas involved in mentalizing is specific to the processing of mental states or can be generalized to the inference of non-mental states by investigating brain responses during the interaction with an artificial agent. Participants were scanned using fMRI during interactive rock-paper-scissors games while believing the opponent was a fellow human (Intentional agent), a humanoid robot endowed with an algorithm (...)
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  16. Gill Kirkup (ed.) (2000). The Gendered Cyborg: A Reader. Routledge in Association with the Open University.score: 408.0
    The Gendered Cyborg brings together material from a variety of disciplines that analyze the relationship between gender and technoscience, and the way that this relationship is represented through ideas, language and visual imagery. The book opens with key feminist articles from the history and philosophy of science. They look at the ways that modern scientific thinking has constructed oppositional dualities such as objectivity/subjectivity, human/machine, nature/science, and male/female, and how these have constrained who can engage in science/technology and how they have (...)
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  17. Maurits Kaptein, Panos Markopoulos, Boris de Ruyter & Emile Aarts (2011). Two Acts of Social Intelligence: The Effects of Mimicry and Social Praise on the Evaluation of an Artificial Agent. AI and Society 26 (3):261-273.score: 405.0
  18. Margaret Boden (1987). Artificial Intelligence: Cannibal or Missionary? [REVIEW] AI and Society 1 (1):17-23.score: 373.5
    Some of the concerns people have about AI are: its misuses, effect on unemployment, and its potential for dehumanising. Contrary to what most people believe and fear, AI can lead to respect for the enormous power and complexity of the human mind. It is potentially very dangerous for users in the public domain to impute much more inferential power to computer systems, which look common-sensical, than they actually have. No matter how impressive AI programs may be, we must be aware (...)
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  19. James H. Fetzer (1990). Artificial Intelligence: Its Scope and Limits. Kluwer.score: 369.0
    1. WHAT IS ARTIFICIAL INTELLIGENCE? One of the fascinating aspects of the field of artificial intelligence (AI) is that the precise nature of its subject ..
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  20. Frederick Kile (2013). Artificial Intelligence and Society: A Furtive Transformation. [REVIEW] AI and Society 28 (1):107-115.score: 369.0
    During the 1950s, there was a burst of enthusiasm about whether artificial intelligence might surpass human intelligence. Since then, technology has changed society so dramatically that the focus of study has shifted toward society’s ability to adapt to technological change. Technology and rapid communications weaken the capacity of society to integrate into the broader social structure those people who have had little or no access to education. (Most of the recent use of communications by the excluded (...)
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  21. Tim Smithers (1988). Product Creation: An Appropriate Coupling of Human and Artificial Intelligence. [REVIEW] AI and Society 2 (4):341-353.score: 369.0
    Small batch manufacture dominates the manufacturing sector of a growing number of industrialised countries. The organisational structures and management methods currently adopted in such enterprises are firmly based upon historical developments which started with individual craftsmen. These structures and methods are primarily concerned with the co-ordination of human activities, rather than with the management of theknowledge process underlying the creation of products.This paper argues that it is the failure to understand this knowledge process and its effective integration at aKnowledge Level (...)
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  22. Massimo Negrotti (1987). The Piping of Thought and the Need for a Permanent Monitoring of the Cultural Effects of Artificial Intelligence. AI and Society 1 (2):85-91.score: 364.5
    Over the years, AI has undergone a transformation from its original aim of producing an ‘intelligent’ machine to that of producing pragmatic solutions of problems of the market place. In doing so, AI has made a significant contribution to the debate on whether the computer is an instrument or an interlocutor. This paper discusses issues of problem solving and creativity underlying this transformation, and attempts to clarify the distinction between theresolutive intelligence andproblematic intelligence. It points out that the (...)
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  23. Maurizio Cardaci, Antonella D'Amico & Barbara Caci (2007). The Social Cognitive Theory: A New Framework for Implementing Artificial Consciousness. In Antonio Chella & Riccardo Manzotti (eds.), Artificial Consciousness. Imprint Academic. 116-123.score: 360.0
  24. Michael Paetau (1991). 'Adaptive' and 'Cooperative' Computer Systems — A Challenge for Sociological Research. AI and Society 5 (1):61-70.score: 342.0
    The vision of the new generation of office systems is based on the hypothesis that an automatic support system is all the more useful and acceptable, the more systems behaviour and performance are in accordance with features ofhuman behaviour. Consequently recent development activities are influenced by the paradigm of the computer as man's “cooperative assistant”. The metaphors ofassistance andcooperation illustrate some major requirements to be met by new office systems. Cooperative office systems will raise a set of new questions about (...)
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  25. Bruce Edmonds (2000). The Constructability of Artificial Intelligence (as Defined by the Turing Test). Journal of Logic Language and Information 9 (4):419-424.score: 334.5
    The Turing Test (TT), as originally specified, centres on theability to perform a social role. The TT can be seen as a test of anability to enter into normal human social dynamics. In this light itseems unlikely that such an entity can be wholly designed in anoff-line mode; rather a considerable period of training insitu would be required. The argument that since we can pass the TT,and our cognitive processes might be implemented as a Turing Machine(TM), (...)
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  26. B. Edmonds (2000). The Constructibility of Artificial Intelligence (as Defined by the Turing Test). Journal of Logic, Language and Information 9 (4):419-424.score: 334.5
    The Turing Test (TT), as originally specified, centres on theability to perform a social role. The TT can be seen as a test of anability to enter into normal human social dynamics. In this light itseems unlikely that such an entity can be wholly designed in an off-line mode; rather a considerable period of training insitu would be required. The argument that since we can pass the TT,and our cognitive processes might be implemented as a Turing Machine(TM), that (...)
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  27. Jack G. Conrad (2010). E-Discovery Revisited: The Need for Artificial Intelligence Beyond Information Retrieval. [REVIEW] Artificial Intelligence and Law 18 (4):321-345.score: 328.5
    In this work, we provide a broad overview of the distinct stages of E-Discovery. We portray them as an interconnected, often complex workflow process, while relating them to the general Electronic Discovery Reference Model (EDRM). We start with the definition of E-Discovery. We then describe the very positive role that NIST’s Text REtrieval Conference (TREC) has added to the science of E-Discovery, in terms of the tasks involved and the evaluation of the legal discovery work performed. Given the critical nature (...)
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  28. Romain Laufer (1992). The Social Acceptability of AI Systems: Legitimacy, Epistemology and Marketing. [REVIEW] AI and Society 6 (3):197-220.score: 301.5
    The expression, ‘the culture of the artificial’ results from the confusion between nature and culture, when nature mingles with culture to produce the ‘artificial’ and science becomes ‘the science of the artificial’. Artificial intelligence can thus be defined as the ultimate expression of the crisis affecting the very foundation of the system of legitimacy in Western society, i.e. Reason, and more precisely, Scientific Reason. The discussion focuses on the emergence of the culture of the (...) and the radical forms of pragmatism, sophism and marketing from a French philosophical perspective. The paper suggests that in the postmodern age of the ‘the crisis of the systems of legitimacy’, the question of social acceptability of any action, especially actions arising out of the application of AI, cannot be avoided. (shrink)
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  29. John Haugeland (1985). Artificial Intelligence: The Very Idea. Cambridge: Mit Press.score: 292.5
    The idea that human thinking and machine computing are "radically the same" provides the central theme for this marvelously lucid and witty book on...
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  30. M. Dascal (1992). Why Does Language Matter to Artificial Intelligence? Minds and Machines 2 (2):145-174.score: 288.0
    Artificial intelligence, conceived either as an attempt to provide models of human cognition or as the development of programs able to perform intelligent tasks, is primarily interested in theuses of language. It should be concerned, therefore, withpragmatics. But its concern with pragmatics should not be restricted to the narrow, traditional conception of pragmatics as the theory of communication (or of the social uses of language). In addition to that, AI should take into account also the mental uses (...)
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  31. B. Scott (2013). Some Comments on the Relationship Between Artificial Intelligence and Human Cognition. Constructivist Foundations 9 (1):64-65.score: 288.0
    Open peer commentary on the article “A Computational Constructivist Model as an Anticipatory Learning Mechanism for Coupled Agent–Environment Systems” by Filipo Studzinski Perotto. Upshot: In making a contribution to artificial intelligence research, Perotto has taken note of work on human cognition. However, there are certain aspects of human cognition that are not taken into account by the author’s model and that, generally, are overlooked or ignored by the artificial intelligence research community at large.
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  32. Lawrence B. Solum (1992). Legal Personhood for Artificial Intelligences. North Carolina Law Review 70:1231.score: 264.0
    Could an artificial intelligence become a legal person? As of today, this question is only theoretical. No existing computer program currently possesses the sort of capacities that would justify serious judicial inquiry into the question of legal personhood. The question is nonetheless of some interest. Cognitive science begins with the assumption that the nature of human intelligence is computational, and therefore, that the human mind can, in principle, be modelled as a program that runs on a computer. (...)
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  33. Richard Hanks (1985). Moral Reasoning in Adolescents: A Feature of Intelligence or Social Adjustment? Journal of Moral Education 14 (1):43-55.score: 261.0
    Abstract This paper summarizes certain aspects of an assessment of the level of the moral judgement of three groups of children: mildly educationally subnormal children, ESN(M), who are also maladjusted; stable ESN(M) children; and stable children of approximately average intelligence. A minimum age of 12.0 years was stipulated; all the children attended secondary school with the oldest in the total sample being 15 years 9 months. The assessment procedure which, although owing much if not all of its rationale (...)
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  34. Patrice Caire (2009). Designing Convivial Digital Cities: A Social Intelligence Design Approach. [REVIEW] AI and Society 24 (1):97-114.score: 261.0
    Conviviality has been identified as a key concept necessary to web communities, such as digital cities, and while it has been simultaneously defined in literature as individual freedom realized in personal interdependence, rational and cooperative behavior and normative instrument, no model for conviviality has yet been proposed for computer science. In this article, we raised the question whether social intelligence design could be used to designing convivial digital cities. We first looked at digital cities and identified, from a (...)
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  35. Stevan Dedijer, Jan Annerstedt & Andrew Jamison (eds.) (1988). From Research Policy to Social Intelligence: Essays for Stevan Dedijer. Macmillan Press.score: 261.0
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  36. Debasis Patnaik (forthcoming). Theorizing Change in Artificial Intelligence: Inductivising Philosophy From Economic Cognition Processes. [REVIEW] AI and Society:1-9.score: 255.0
    Economic value additions to knowledge and demand provide practical, embedded and extensible meaning to philosophizing cognitive systems. Evaluation of a cognitive system is an empirical matter. Thinking of science in terms of distributed cognition (interactionism) enlarges the domain of cognition. Anything that actually contributes to the specific quality of output of a cognitive system is part of the system in time and/or space. Cognitive science studies behaviour and knowledge structures of experts and categorized structures based on underlying structures. Knowledge representation (...)
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  37. Ronald J. Allen (2001). Artificial Intelligence and the Evidentiary Process: The Challenges of Formalism and Computation. [REVIEW] Artificial Intelligence and Law 9 (2-3):99-114.score: 252.0
    The tension between rule and judgment is well known with respect to the meaning of substantive legal commands. The same conflict is present in fact finding. The law penetrates to virtually all aspects of human affairs; irtually any interaction can generate a legal conflict. Accurate fact finding about such disputes is a necessary condition for the appropriate application of substantive legal commands. Without accuracy in fact finding, the law is unpredictable, and thus individuals cannot efficiently accommodate their affairs to (...)
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  38. Gordana Dodig Crnkovic & Daniel Persson (2008). Sharing Moral Responsibility with Robots: A Pragmatic Approach. In Holst, Per Kreuger & Peter Funk (eds.), Frontiers in Artificial Intelligence and Applications Volume 173. IOS Press Books.score: 248.0
    Roboethics is a recently developed field of applied ethics which deals with the ethical aspects of technologies such as robots, ambient intelligence, direct neural interfaces and invasive nano-devices and intelligent soft bots. In this article we look specifically at the issue of (moral) responsibility in artificial intelligent systems. We argue for a pragmatic approach, where responsibility is seen as a social regulatory mechanism. We claim that having a system which takes care of certain tasks intelligently, learning (...)
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  39. Hans F. M. Crombag (1993). On the Artificiality of Artificial Intelligence. Artificial Intelligence and Law 2 (1):39-49.score: 243.0
    In this article the question is raised whether artificial intelligence has any psychological relevance, i.e. contributes to our knowledge of how the mind/brain works. It is argued that the psychological relevance of artificial intelligence of the symbolic kind is questionable as yet, since there is no indication that the brain structurally resembles or operates like a digital computer. However, artificial intelligence of the connectionist kind may have psychological relevance, not because the brain is a (...)
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  40. Yanna Vogiazou (2007). Design for Emergence: Collaborative Social Play with Online and Location-Based Media. Ios Press.score: 225.0
    In light of the fact that social dynamics and unexpected uses of technology can inspire innovation, this book proposes a research model of design for emergence, ...
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  41. Don Sherratt, Simon Rogerson & N. Ben Fairweather (2005). The Challenge of Raising Ethical Awareness: A Case-Based Aiding System for Use by Computing and ICT Students. Science and Engineering Ethics 11 (2):299-315.score: 225.0
    Students, the future Information and Communication Technology (ICT) professionals, are often perceived to have little understanding of the ethical issues associated with the use of ICTs. There is a growing recognition that the moral issues associated with the use of the new technologies should be brought to the attention of students. Furthermore, they should be encouraged to explore and think more deeply about the social and legal consequences of the use of ICTs. This paper describes the development of a (...)
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  42. Ronald Stamper (1988). Pathologies of AI: Responsible Use of Artificial Intelligence in Professional Work. [REVIEW] AI and Society 2 (1):3-16.score: 220.5
    Although the AI paradigm is useful for building knowledge-based systems for the applied natural sciences, there are dangers when it is extended into the domains of business, law and other social systems. It is misleading to treat knowledge as a commodity that can be separated from the context in which it is regularly used. Especially when it relates to social behaviour, knowledge should be treated as socially constructed, interpreted and maintained through its practical use in context. The meanings (...)
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  43. Murat Aydede & Guven Guzeldere (2000). Consciousness, Intentionality, and Intelligence: Some Foundational Issues for Artificial Intelligence. Journal of Experimental and Theoretical Artificial Intelligence 12 (3):263-277.score: 216.0
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  44. Selmer Bringsjord (2000). Animals, Zombanimals, and the Total Turing Test: The Essence of Artificial Intelligence. Journal of Logic Language and Information 9 (4):397-418.score: 216.0
    Alan Turing devised his famous test (TT) through a slight modificationof the parlor game in which a judge tries to ascertain the gender of twopeople who are only linguistically accessible. Stevan Harnad hasintroduced the Total TT, in which the judge can look at thecontestants in an attempt to determine which is a robot and which aperson. But what if we confront the judge with an animal, and arobot striving to pass for one, and then challenge him to peg which iswhich? (...)
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  45. John M. Preston & John Mark Bishop (eds.) (2002). Views Into the Chinese Room: New Essays on Searle and Artificial Intelligence. Oxford University Press.score: 216.0
    The most famous challenge to computational cognitive science and artificial intelligence is the philosopher John Searle's "Chinese Room" argument.
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  46. David Marr (1977). Artificial Intelligence: A Personal View. Artificial Intelligence 9 (September):37-48.score: 216.0
  47. Rajakishore Nath (2009). Philosophy of Artificial Intelligence: A Critique of the Mechanistic Theory of Mind. Universal Publishers.score: 216.0
    This book deals with the major philosophical issues in the theoretical framework of Artificial Intelligence (AI) in particular and cognitive science in general.
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  48. Selmer Bringsjord (2010). Meeting Floridi's Challenge to Artificial Intelligence From the Knowledge-Game Test for Self-Consciousness. Metaphilosophy 41 (3):292-312.score: 216.0
    Abstract: In the course of seeking an answer to the question "How do you know you are not a zombie?" Floridi (2005) issues an ingenious, philosophically rich challenge to artificial intelligence (AI) in the form of an extremely demanding version of the so-called knowledge game (or "wise-man puzzle," or "muddy-children puzzle")—one that purportedly ensures that those who pass it are self-conscious. In this article, on behalf of (at least the logic-based variety of) AI, I take up the challenge—which (...)
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  49. Craig DeLancey (2001). Passionate Engines: What Emotions Reveal About the Mind and Artificial Intelligence. Oxford University Press.score: 216.0
    The emotions have been one of the most fertile areas of study in psychology, neuroscience, and other cognitive disciplines. Yet as influential as the work in those fields is, it has not yet made its way to the desks of philosophers who study the nature of mind. Passionate Engines unites the two for the first time, providing both a survey of what emotions can tell us about the mind, and an argument for how work in the cognitive disciplines can help (...)
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  50. Viola Schiaffonati (2003). A Framework for the Foundation of the Philosophy of Artificial Intelligence. Minds and Machines 13 (4):537-552.score: 216.0
    The peculiarity of the relationship between philosophy and Artificial Intelligence (AI) has been evidenced since the advent of AI. This paper aims to put the basis of an extended and well founded philosophy of AI: it delineates a multi-layered general framework to which different contributions in the field may be traced back. The core point is to underline how in the same scenario both the role of philosophy on AI and role of AI on philosophy must be considered. (...)
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