Search results for 'Intelligence' (try it on Scholar)

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  1. Of Intelligence (2002). Unraveling Trie Enigma of Human Intelligence: Evolutionary Psychology and the Multimodular Mind. In Robert J. Sternberg & J. Kaufman (eds.), The Evolution of Intelligence. Lawrence Erlbaum. 145.score: 210.0
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  2. Hans F. M. Crombag (1993). On the Artificiality of Artificial Intelligence. Artificial Intelligence and Law 2 (1):39-49.score: 27.0
    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 neural network, but (...)
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  3. Christopher Mole (2012). Three Philosophical Lessons for the Analysis of Criminal and Military Intelligence. Intelligence and National Security 27 (4):441-58.score: 27.0
    It has recently been suggested that philosophy – in particular epistemology – has a contribution to make to the analysis of criminal and military intelligence. The present article pursues this suggestion, taking three phenomena that have recently been studied by philosophers, and showing that they have important implications for the gathering and sharing of intelligence, and for the use of intelligence in the determining of military strategy. The phenomena discussed are: (1) Simpson's Paradox, (2) the distinction between (...)
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  4. Daniel C. Dennett (1994). The Role of Language in Intelligence. In Jean Khalfa (ed.), What is Intelligence? The Darwin College Lectures. Cambridge, Cambridge University Press.score: 25.0
    We human beings may not be the most admirable species on the planet, or the most likely to survive for another millennium, but we are without any doubt at all the most intelligent. We are also the only species with language. What is the relation between these two obvious facts?
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  5. 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: 24.0
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  6. 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: 24.0
    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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  7. John M. Preston & John Mark Bishop (eds.) (2002). Views Into the Chinese Room: New Essays on Searle and Artificial Intelligence. Oxford University Press.score: 24.0
    The most famous challenge to computational cognitive science and artificial intelligence is the philosopher John Searle's "Chinese Room" argument.
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  8. John T. Sanders (1985). Experience, Memory and Intelligence. The Monist 68 (4):507-521.score: 24.0
    What characterizes most technical or theoretical accounts of memory is their reliance upon an internal storage model. Psychologists and neurophysiologists have suggested neural traces (either dynamic or static) as the mechanism for this storage, and designers of artificial intelligence have relied upon the same general model, instantiated magnetically or electronically instead of neurally, to do the same job. Both psychology and artificial intelligence design have heretofore relied, without much question, upon the idea that memory is to be understood (...)
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  9. David Marr (1977). Artificial Intelligence: A Personal View. Artificial Intelligence 9 (September):37-48.score: 24.0
  10. Satish P. Deshpande & Jacob Joseph (2009). Impact of Emotional Intelligence, Ethical Climate, and Behavior of Peers on Ethical Behavior of Nurses. Journal of Business Ethics 85 (3):403 - 410.score: 24.0
    This study examines factors impacting ethical behavior of 103 hospital nurses. The level of emotional intelligence and ethical behavior of peers had a significant impact on ethical behavior of nurses. Independence climate had a significant impact on ethical behavior of nurses. Other ethical climate types such as professional, caring, rules, instrumental, and efficiency did not impact ethical behavior of respondents. Implications of this study for researchers and practitioners are discussed.
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  11. Peter-Paul Verbeek (2009). Ambient Intelligence and Persuasive Technology: The Blurring Boundaries Between Human and Technology. [REVIEW] NanoEthics 3 (3):231-242.score: 24.0
    The currently developing fields of Ambient Intelligence and Persuasive Technology bring about a convergence of information technology and cognitive science. Smart environments that are able to respond intelligently to what we do and that even aim to influence our behaviour challenge the basic frameworks we commonly use for understanding the relations and role divisions between human beings and technological artifacts. After discussing the promises and threats of these technologies, this article develops alternative conceptions of agency, freedom, and responsibility that (...)
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  12. Clancy Blair (2006). How Similar Are Fluid Cognition and General Intelligence? A Developmental Neuroscience Perspective on Fluid Cognition as an Aspect of Human Cognitive Ability. Behavioral and Brain Sciences 29 (2):109-125.score: 24.0
    This target article considers the relation of fluid cognitive functioning to general intelligence. A neurobiological model differentiating working memory/executive function cognitive processes of the prefrontal cortex from aspects of psychometrically defined general intelligence is presented. Work examining the rise in mean intelligence-test performance between normative cohorts, the neuropsychology and neuroscience of cognitive function in typically and atypically developing human populations, and stress, brain development, and corticolimbic connectivity in human and nonhuman animal models is reviewed and found to (...)
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  13. Susan G. Sterrett (2000). Turing's Two Tests for Intelligence. Minds and Machines 10 (4):541-559.score: 24.0
    On a literal reading of `Computing Machinery and Intelligence'', Alan Turing presented not one, but two, practical tests to replace the question `Can machines think?'' He presented them as equivalent. I show here that the first test described in that much-discussed paper is in fact not equivalent to the second one, which has since become known as `the Turing Test''. The two tests can yield different results; it is the first, neglected test that provides the more appropriate indication of (...)
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  14. Marcus Hutter (2012). Can Intelligence Explode? Journal of Consciousness Studies 19 (1-2):143-166.score: 24.0
    The technological singularity refers to a hypothetical scenario in which technological advances virtually explode. The most popular scenario is the creation of super-intelligent algorithms that recursively create ever higher intelligences. It took many decades for these ideas to spread from science fiction to popular science magazines and finally to attract the attention of serious philosophers. David Chalmers' (JCS 2010) article is the first comprehensive philosophical analysis of the singularity in a respected philosophy journal. The motivation of my article is to (...)
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  15. James H. Fetzer (1990). Artificial Intelligence: Its Scope and Limits. Kluwer.score: 24.0
    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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  16. Viola Schiaffonati (2003). A Framework for the Foundation of the Philosophy of Artificial Intelligence. Minds and Machines 13 (4):537-552.score: 24.0
    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. Moreover, (...)
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  17. Rajakishore Nath (2009). Philosophy of Artificial Intelligence: A Critique of the Mechanistic Theory of Mind. Universal Publishers.score: 24.0
    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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  18. Philip Brey (2005). Freedom and Privacy in Ambient Intelligence. Ethics and Information Technology 7 (3):157-166.score: 24.0
    This paper analyzes ethical aspects of the new paradigm of Ambient Intelligence, which is a combination of Ubiquitous Computing and Intelligent User Interfaces (IUI’s). After an introduction to the approach, two key ethical dimensions will be analyzed: freedom and privacy. It is argued that Ambient Intelligence, though often designed to enhance freedom and control, has the potential to limit freedom and autonomy as well. Ambient Intelligence also harbors great privacy risks, and these are explored as well.
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  19. H. G. Callaway (1999). Intelligence, Community and Cartesian Doubt. Humanism Today 13:31-48.score: 24.0
    This paper attempts some integration of two perspectives on questions about rationality and irrationality: the classical conception of irrationality as sophism and themes from the romantic revolt against Enlightenment reason. However, since talk of "reason" and "the irrational" often invites rigid dualities of reason and its opposites (such as feeling, intuition, faith, or tradition), the paper turns to "intelligence" in place of "reason," thinking of human intelligence as something less abstract, less purely theoretical, and more firmly rooted in (...)
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  20. Taner Edis (1998). How Godel's Theorem Supports the Possibility of Machine Intelligence. Minds and Machines 8 (2):251-262.score: 24.0
    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 arbitrary (...)
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  21. Shane Legg & Marcus Hutter (2007). Universal Intelligence: A Definition of Machine Intelligence. [REVIEW] Minds and Machines 17 (4):391-444.score: 24.0
    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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  22. Selmer Bringsjord (2010). Meeting Floridi's Challenge to Artificial Intelligence From the Knowledge-Game Test for Self-Consciousness. Metaphilosophy 41 (3):292-312.score: 24.0
    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 is (...)
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  23. Jamie Cullen (2009). Imitation Versus Communication: Testing for Human-Like Intelligence. Minds and Machines 19 (2):237-254.score: 24.0
    Turing’s Imitation Game is often viewed as a test for theorised machines that could ‘think’ and/or demonstrate ‘intelligence’. However, contrary to Turing’s apparent intent, it can be shown that Turing’s Test is essentially a test for humans only. Such a test does not provide for theorised artificial intellects with human-like, but not human-exact, intellectual capabilities. As an attempt to bypass this limitation, I explore the notion of shifting the goal posts of the Turing Test, and related tests such as (...)
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  24. Craig DeLancey (2001). Passionate Engines: What Emotions Reveal About the Mind and Artificial Intelligence. Oxford University Press.score: 24.0
    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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  25. Jacob Joseph, Kevin Berry & Satish P. Deshpande (2009). Impact of Emotional Intelligence and Other Factors on Perception of Ethical Behavior of Peers. Journal of Business Ethics 89 (4):539 - 546.score: 24.0
    This study investigates factors impacting perceptions of ethical conduct of peers of 293 students in four US universities. Self-reported ethical behavior and recognition of emotions in others (a dimension of emotional intelligence) impacted perception of ethical behavior of peers. None of the other dimensions of emotional intelligence were significant. Age, Race, Sex, GPA, or type of major (business versus nonbusiness) did not impact perception of ethical behavior of peers. Implications of the results of the study for business schools (...)
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  26. E. Ronald & Moshe Sipper (2001). Intelligence is Not Enough: On the Socialization of Talking Machines. [REVIEW] Minds and Machines 11 (4):567-576.score: 24.0
    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 trust and (...)
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  27. Niels van Dijk (2010). Property, Privacy and Personhood in a World of Ambient Intelligence. Ethics and Information Technology 12 (1):57-69.score: 24.0
    Profiling technologies are the facilitating force behind the vision of Ambient Intelligence in which everyday devices are connected and embedded with all kinds of smart characteristics enabling them to take decisions in order to serve our preferences without us being aware of it. These technological practices have considerable impact on the process by which our personhood takes shape and pose threats like discrimination and normalisation. The legal response to these developments should move away from a focus on entitlements to (...)
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  28. David Carr (2002). Feelings in Moral Conflict and the Hazards of Emotional Intelligence. Ethical Theory and Moral Practice 5 (1):3-21.score: 24.0
    From some perspectives, it seems obvious that emotions and feelings must be both reasonable and morally significant: from others, it may seem as obvious that they cannot be. This paper seeks to advance discussion of ethical implications of the currently contested issue of the relationship of reason to feeling and emotion via reflection upon various examples of affectively charged moral dilemma. This discussion also proceeds by way of critical consideration of recent empirical enquiry into these issues in the literature of (...)
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  29. Thomas Li-Ping Tang & Yuh-Jia Chen (2008). Intelligence Vs. Wisdom: The Love of Money, Machiavellianism, and Unethical Behavior Across College Major and Gender. [REVIEW] Journal of Business Ethics 82 (1):1 - 26.score: 24.0
    This research investigates the efficacy of business ethics intervention, tests a theoretical model that the love of money is directly or indirectly related to propensity to engage in unethical behavior (PUB), and treats college major (business vs. psychology) and gender (male vs. female) as moderators in multi-group analyses. Results suggested that business students who received business ethics intervention significantly changed their conceptions of unethical behavior and reduced their propensity to engage in theft; while psychology students without intervention had no such (...)
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  30. Gary L. Drescher (1991). Made-Up Minds: A Constructivist Approach to Artificial Intelligence. Cambridge: MIT Press.score: 24.0
    Made-Up Minds addresses fundamental questions of learning and concept invention by means of an innovative computer program that is based on the cognitive ...
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  31. Marco Ernandes (2005). Artificial Intelligence & Games: Should Computational Psychology Be Revalued? Topoi 24 (2):229-242.score: 24.0
    The aims of this paper are threefold: To show that game-playing (GP), the discipline of Artificial Intelligence (AI) concerned with the development of automated game players, has a strong epistemological relevance within both AI and the vast area of cognitive sciences. In this context games can be seen as a way of securely reducing (segmenting) real-world complexity, thus creating the laboratory environment necessary for testing the diverse types and facets of intelligence produced by computer models. This paper aims (...)
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  32. Beth Preston (1991). Anthropocentrism, and the Evolution of 'Intelligence'. Minds and Machines 1 (3):259-277.score: 24.0
    Intuitive conceptions guide practice, but practice reciprocally reshapes intuition. The intuitive conception of intelligence in AI was originally highly anthropocentric. However, the internal dynamics of AI research have resulted in a divergence from anthropocentric concerns. In particular, the increasing emphasis on commonsense knowledge and peripheral intelligence (perception and movement) in effect constitutes an incipient reorientation of intuitions about the nature of intelligence in a non-anthropocentric direction. I argue that this conceptual shift undermines Joseph Weizenbaum's claim that the (...)
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  33. Richard E. Korf (1995). Heuristic Evaluation Functions in Artificial Intelligence Search Algorithms. Minds and Machines 5 (4):489-498.score: 24.0
    We consider a special case of heuristics, namely numeric heuristic evaluation functions, and their use in artificial intelligence search algorithms. The problems they are applied to fall into three general classes: single-agent path-finding problems, two-player games, and constraint-satisfaction problems. In a single-agent path-finding problem, such as the Fifteen Puzzle or the travelling salesman problem, a single agent searches for a shortest path from an initial state to a goal state. Two-player games, such as chess and checkers, involve an adversarial (...)
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  34. Evan Selinger (2008). Collins's Incorrect Depiction of Dreyfus's Critique of Artificial Intelligence. Phenomenology and the Cognitive Sciences 7 (2):301-308.score: 24.0
    Harry Collins interprets Hubert Dreyfus’s philosophy of embodiment as a criticism of all possible forms of artificial intelligence. I argue that this characterization is inaccurate and predicated upon a misunderstanding of the relevance of phenomenology for empirical scientific research.
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  35. S. G. Sterrett, Turing on the Integration of Human and Machine Intelligence.score: 24.0
    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! There (...)
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  36. Barbara Warnick (2004). Rehabilitating AI: Argument Loci and the Case for Artificial Intelligence. [REVIEW] Argumentation 18 (2):149-170.score: 24.0
    This article examines argument structures and strategies in pro and con argumentation about the possibility of human-level artificial intelligence (AI) in the near term future. It examines renewed controversy about strong AI that originated in a prominent 1999 book and continued at major conferences and in periodicals, media commentary, and Web-based discussions through 2002. It will be argued that the book made use of implicit, anticipatory refutation to reverse prevailing value hierarchies related to AI. Drawing on Perelman and Olbrechts-Tyteca's (...)
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  37. Eleni Kosta, Olli Pitkänen, Marketta Niemelä & Eija Kaasinen (2010). Mobile-Centric Ambient Intelligence in Health- and Homecare—Anticipating Ethical and Legal Challenges. Science and Engineering Ethics 16 (2):303-323.score: 24.0
    Ambient Intelligence provides the potential for vast and varied applications, bringing with it both promise and peril. The development of Ambient Intelligence applications poses a number of ethical and legal concerns. Mobile devices are increasingly evolving into tools to orientate in and interact with the environment, thus introducing a user-centric approach to Ambient Intelligence. The MINAmI (Micro-Nano integrated platform for transverse Ambient Intelligence applications) FP6 research project aims at creating core technologies for mobile device based Ambient (...)
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  38. Douglas N. Walton (2008). Witness Testimony Evidence: Argumentation, Artificial Intelligence, and Law. Cambridge University Press.score: 24.0
    Recent work in artificial intelligence has increasingly turned to argumentation as a rich, interdisciplinary area of research that can provide new methods related to evidence and reasoning in the area of law. Douglas Walton provides an introduction to basic concepts, tools and methods in argumentation theory and artificial intelligence as applied to the analysis and evaluation of witness testimony. He shows how witness testimony is by its nature inherently fallible and sometimes subject to disastrous failures. At the same (...)
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  39. James M. Bloodgood, William H. Turnley & Peter Mudrack (2008). The Influence of Ethics Instruction, Religiosity, and Intelligence on Cheating Behavior. Journal of Business Ethics 82 (3):557 - 571.score: 24.0
    This study examines the influence of ethics instruction, religiosity, and intelligence on cheating behavior. A sample of 230 upper level, undergraduate business students had the opportunity to increase their chances of winning money in an experimental situation by falsely reporting their task performance. In general, the results indicate that students who attended worship services more frequently were less likely to cheat than those who attended worship services less frequently, but that students who had taken a course in business ethics (...)
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  40. Mariusz Flasiński (1997). "Every Man in His Notions" or Alchemists' Discussion on Artificial Intelligence. Foundations of Science 2 (1):107-121.score: 24.0
    A survey of the main approaches in a mind study -oriented part of Artificial Intelligence is made focusing on controversial issues and extreme hypotheses. Various meanings of terms: "intelligence" and "artificial intelligence" are discussed. Limitations for constructing intelligent systems resulting from the lack of formalized models of cognitive activity are shown. The approaches surveyed are then recapitulated in the light of these limitations.
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  41. John Angelidis & Nabil A. Ibrahim (2011). The Impact of Emotional Intelligence on the Ethical Judgment of Managers. Journal of Business Ethics 99 (S1):111-119.score: 24.0
    In recent years there has been a substantial amount of research on emotional intelligence (EI) across a wide range of disciplines. Also, this term has been receiving increasing attention in the popular business press. This article extends previous research by seeking to determine whether there is a relationship between emotional intelligence and ethical judgment among practicing managers with respect to questions of ethical nature that can arise in their professional activity. It analyzes the results of a survey of (...)
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  42. Tracy B. Henley (1990). Natural Problems and Artificial Intelligence. Behavior and Philosophy 18 (2):43-55.score: 24.0
    Artificial Intelligence has become big business in the military and in many industries. In spite of this growth there still remains no consensus about what AI really is. The major factor which seems to be responsible for this is the lack of agreement about the relationship between behavior and intelligence. In part certain ethical concerns generated from saying who, what and how intelligence is determined may be facilitating this lack of agreement.
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  43. Frederick Kile (2013). Artificial Intelligence and Society: A Furtive Transformation. [REVIEW] AI and Society 28 (1):107-115.score: 24.0
    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 has been (...)
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  44. Amir S. Tabandeh (1994). Characterising Artificial Intelligence Technology for International Transfer. AI and Society 8 (4):315-325.score: 24.0
    One of the central factors influencing the process and the outcome of technology transfer is the nature of the technology being transferred. This paper identifies and discusses the main characteristics of Artificial Intelligence (AI) technology from the point of view of international technology transfer. It attempts to indicate the peculiarities of AI in this context and move towards a framework to assist recipient decision makers in optimising the formulation of their policies on AI technology transfer.
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  45. Richard Doyle (2012). Healing with Plant Intelligence: A Report From Ayahuasca. Anthropology of Consciousness 23 (1):28-43.score: 24.0
    Numerous and diverse reports indicate the efficacy of shamanic plant adjuncts (e.g., iboga, ayahuasca, psilocybin) for the care and treatment of addiction, post-traumatic stress disorder, cancer, cluster headaches, and depression. This article reports on a first-person healing of lifelong asthma and atopic dermatitis in the shamanic context of the contemporary Peruvian Amazon and the sometimes digital ontology of online communities. The article suggests that emerging language, concepts, and data drawn from the sciences of plant signaling and behavior regarding “plant (...)” provide a useful heuristic framework for comprehending and actualizing the healing potentials of visionary plant “entheogens” (Wasson 1971) as represented both through first-person experience and online reports. Together with the paradigms and practices of plant signaling, biosemiotics provides a robust and coherent map for contextualizing the often reported experience of plant communication with ayahuasca and other entheogenic plants. The archetype of the “plant teachers” (called Doctores in the upper Amazon) is explored as a means for organizing and interacting with this data within an epistemology of the “hallucination/perception continuum (Fischer 1975). “Ecodelic” is offered as a new linguistic interface alongside “entheogen” (Wasson 1971). (shrink)
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  46. Morton Wagman (ed.) (2000). Historical Dictionary of Quotations in Cognitive Science: A Treasury of Quotations in Psychology, Philosophy, and Artificial Intelligence. Greenwood Press.score: 24.0
    Focuses on distinguished quotations representing the best thinking in philosophy, psychology, and artificial intelligence from classical civilization to ...
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  47. Pavel Prudkov (2010). A View on Human Goal-Directed Activity and the Construction of Artificial Intelligence. Minds and Machines 20 (3):363-383.score: 24.0
    Although activity aimed at the construction of artificial intelligence started about 60 years ago however, contemporary intelligent systems are effective in very narrow domains only. One of the reasons for this situation appears to be serious problems in the theory of intelligence. Intelligence is a characteristic of goal-directed systems and two classes of goal-directed systems can be derived from observations on animals and humans, one class is systems with innately and jointly determined goals and means. The other (...)
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  48. Birger Siebert (2005). Prospects for a Cultural-Historical Psychology of Intelligence. Studies in East European Thought 57 (3-4):305 - 317.score: 24.0
    The ideas of cultural-historical psychology have led to a new understanding of the human psyche as developing in the process of the subject acting in social and historical contexts. Such a “non-classical” reinterpretation of psychological concepts should be based on a theoretical and philosophical framework in order to explain genetic sources of these concepts. For this purpose, Il’enkov’s philosophy is of great significance. This is illustrated by discussing a possible cultural-historical understanding of the concept of intelligence.
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  49. Roman Yampolskiy & Joshua Fox (2013). Safety Engineering for Artificial General Intelligence. Topoi 32 (2):217-226.score: 24.0
    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, we (...)
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  50. Hutan Ashrafian (forthcoming). Artificial Intelligence and Robot Responsibilities: Innovating Beyond Rights. Science and Engineering Ethics:1-10.score: 24.0
    The enduring innovations in artificial intelligence and robotics offer the promised capacity of computer consciousness, sentience and rationality. The development of these advanced technologies have been considered to merit rights, however these can only be ascribed in the context of commensurate responsibilities and duties. This represents the discernable next-step for evolution in this field. Addressing these needs requires attention to the philosophical perspectives of moral responsibility for artificial intelligence and robotics. A contrast to the moral status of animals (...)
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