15 found
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  1.  68
    The Uncanny Advantage of Using Androids in Cognitive and Social Science Research.Karl F. MacDorman & Hiroshi Ishiguro - 2006 - Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies / Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies 7 (3):297-337.
    The development of robots that closely resemble human beings can contribute to cognitive research. An android provides an experimental apparatus that has the potential to be controlled more precisely than any human actor. However, preliminary results indicate that only very humanlike devices can elicit the broad range of responses that people typically direct toward each other. Conversely, to build androids capable of emulating human behavior, it is necessary to investigate social activity in detail and to develop models of the cognitive (...)
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  2. Does Japan Really Have Robot Mania? Comparing Attitudes by Implicit and Explicit Measures.Karl F. MacDorman, Sandosh K. Vasudevan & Chin-Chang Ho - 2009 - AI and Society 23 (4):485-510.
    Japan has more robots than any other country with robots contributing to many areas of society, including manufacturing, healthcare, and entertainment. However, few studies have examined Japanese attitudes toward robots, and none has used implicit measures. This study compares attitudes among the faculty of a US and a Japanese university. Although the Japanese faculty reported many more experiences with robots, implicit measures indicated both faculties had more pleasant associations with humans. In addition, although the US faculty reported people were more (...)
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  3.  19
    Individual Differences Predict Sensitivity to the Uncanny Valley.Karl F. MacDorman & Steven O. Entezari - 2015 - Interaction Studies 16 (2):141-172.
    It can be creepy to notice that something human-looking is not real. But can sensitivity to this phenomenon, known as the uncanny valley, be predicted from superficially unrelated traits? Based on results from at least 489 participants, this study examines the relation between nine theoretically motivated trait indices and uncanny valley sensitivity, operationalized as increased eerie ratings and decreased warmth ratings for androids presented in videos. Animal Reminder Sensitivity, Neuroticism, its Anxiety facet, and Religious Fundamentalism significantly predicted uncanny valley sensitivity. (...)
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  4.  21
    Reducing Consistency in Human Realism Increases the Uncanny Valley Effect; Increasing Category Uncertainty Does Not.Karl F. MacDorman & Debaleena Chattopadhyay - 2016 - Cognition 146:190-205.
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  5. Extending the Medium Hypothesis: The Dennett-Mangan Controversy and Beyond.Karl F. MacDorman - 2004 - Journal of Mind and Behavior 25 (3):237-257.
    Mangan’s hypothesis, that consciousness is an information-bearing medium, presents an alternative to Dennett’s brand of functionalism, and Dennett’s counterattacks have yet to address Mangan’s main assertion. The medium hypothesis does not entail Cartesian theater assumptions concerning the localization, causal status, and “filling in” of consciousness in the brain. In principle, it is compatible with distributed information transfer between different media, epiphenomenalism, and gaps in visual experience. However, Mangan’s strongest empirical argument, based on consciousness’ limited “bandwidth,” does not necessarily show that (...)
     
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  6.  26
    Toward Social Mechanisms of Android Science.Karl F. MacDorman & Hiroshi Ishiguro - 2006 - Interaction Studies 7 (2):289-296.
  7.  9
    An Account of Consciousness in Physical and Functional Terms: A Target for Research in the Neurosciences.G. Sommerhoff & Karl F. MacDorman - 1994 - Integrative Physiological and Behavioral Science 29:151-81.
  8.  94
    Life After the Symbol System Metaphor.Karl F. MacDorman - 2007 - Interaction Studies 8 (1):143-158.
    After reviewing the papers in this special issue, I must conclude that brains are not syntactic engines, but control systems that orient to biological, interindividual, and cultural norms. By themselves, syntactic constraints both underdetermine and overdetermine cognitive operations. So, rather than serving as the basis for general cognition, they are just another kind of empirically acquired constraint. In humans, symbols emerge from a particular sensorimotor activity through a process of contextual broadening that depends on the coordination of conscious and nonconscious (...)
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  9.  13
    How to Ground Symbols Adaptively.Karl F. MacDorman - 1997 - In S. O'Nuillain, Paul McKevitt & E. MacAogain (eds.), Two Sciences of Mind. John Benjamins. pp. 9--135.
  10.  36
    Introduction to the Special Issue on Psychological Benchmarks of Human–Robot Interaction.Karl F. MacDorman & Peter H. Kahn Jr - 2007 - Interaction Studies 8 (3):359-362.
  11.  22
    Toward Social Mechanisms of Android Science: A CogSci 2005 Workshop: 25 and 26 July 2005, Stresa, Italy.Karl F. MacDorman & Hiroshi Ishiguro - 2006 - Interaction Studies: Social Behaviour and Communication in Biological and Artificial Systems 7 (2):289-296.
  12.  19
    Opening Pandora’s Uncanny Box: Reply to Commentaries on “The Uncanny Advantage of Using Androids in Social and Cognitive Science Research”.Karl F. MacDorman & Hiroshi Ishiguro - 2006 - Interaction Studies: Social Behaviour and Communication in Biological and Artificial Systems 7 (3):361-368.
  13.  11
    Introduction to the Special Issue on Psychological Benchmarks of Human–Robot Interaction.Karl F. MacDorman & Peter H. Kahn - 2007 - Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies / Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies 8 (3):359-362.
  14.  4
    Opening Pandora’s Uncanny Box.Karl F. MacDorman & Hiroshi Ishiguro - 2006 - Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies / Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies 7 (3):361-368.
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  15.  19
    Feature Learning, Multiresolution Analysis, and Symbol Grounding.Karl F. MacDorman - 1998 - Behavioral and Brain Sciences 21 (1):32-33.
    Cognitive theories based on a fixed feature set suffer from frame and symbol grounding problems. Flexible features and other empirically acquired constraints (e.g., analog-to-analog mappings) provide a framework for letting extrinsic relations influence symbol manipulation. By offering a biologically plausible basis for feature learning, nonorthogonal multiresolution analysis and dimensionality reduction, informed by functional constraints, may contribute to a solution to the symbol grounding problem.
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