Results for 'Yue-jin Ai'

999 found
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  1.  18
    Task-Irrelevant Emotional Faces Impair Response Adjustments in a Double-Step Saccade Task.Zhenlan Jin, Shulin Yue, Junjun Zhang & Ling Li - 2017 - Cognition and Emotion 32 (6):1347-1354.
    ABSTRACTCognitive control enables us to adjust behaviours according to task demands, and emotion influences the cognitive control. We examined how task-irrelevant emotional stimuli impact the ability to inhibit a prepared response and then programme another appropriate response. In the study, either a single target or two sequential targets appeared after emotional face images. Subjects were required to freely viewed the emotional faces and make a saccade quickly upon target onset, but inhibit their initial saccades and redirect gaze to the second (...)
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  2. Zhongguo Jin Shi Wen Hua Si Chao =.Hua Ai - 2008 - Anhui da Xue Chu Ban She.
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  3. Yi Zhi Yu Chao Yue: Shubenhua Mei Xue Si Xiang Yan Jiu = Beyong the Will: A Study of Schopenhauer's Philosophy and Aesthetics.Huimin Jin - 1999 - Zhongguo She Hui Ke Xue Chu Ban She.
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  4. The Development of a Schema for Semantic Annotation: Gain Brought by a Formal Ontological Method.Ai Kawazoe, Lihua Jin, Mika Shigematsu, Daisuke Bekki, Roberto Barrero, Kiyosu Taniguchi & Nigel Collier - 2009 - Applied Ontology 4 (1):5-20.
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  5.  20
    The Influence of Emotion on Fairness-Related Decision Making: A Critical Review of Theories and Evidence.Ya Zheng, Zhong Yang, Chunlan Jin, Yue Qi & Xun Liu - 2017 - Frontiers in Psychology 8.
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  6.  6
    The Relationship Between the Dark Triad and Internet Adaptation Among Adolescents in China: Internet Use Preference as a Mediator.Can Can Jin, Bo Chen Wang & Ai Tong Ji - 2019 - Frontiers in Psychology 10.
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  7.  7
    Caregiver Depression and Early Child Development: A Mixed-Methods Study From Rural China.Ai Yue, Jiaqi Gao, Meredith Yang, Lena Swinnen, Alexis Medina & Scott Rozelle - 2018 - Frontiers in Psychology 9.
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  8.  19
    The Art of Lamentation in the Works of Pan Yue: "Mourning the Eternally Departed".C. M. Lai & Pan Yue - 1994 - Journal of the American Oriental Society 114 (3):409-425.
  9. Ai Silin Lun Wen Xuan.Silin Ai - 2011 - Zhonghua Shu Ju.
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  10. Jin Jingfang Ru Xue Lun Ji.Jingfang Jin - 2010 - Sichuan da Xue Chu Ban She.
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  11. Jin Kaicheng Wen Xuan.Kaicheng Jin - 2010 - Beijing da Xue Chu Ban She.
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  12. Jin Yuelin Hui Yi Lu.Yuelin Jin - 2011 - Beijing da Xue Chu Ban She.
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  13. Jin Yuelin Quan Ji.Yuelin Jin - 2013 - Ren Min Chu Ban She.
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  14. Jin Yuelin Xuan Ji =.Yuelin Jin - 2005 - Jilin Ren Min Chu Ban She.
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  15. Logics in Ai European Workshop Jelia '92, Berlin, Germany, September 7-10, 1992 : Proceedings'.David A. Pearce, Gerd Wagner & European Workshop on Logics in Ai - 1992
     
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  16. Doctrinal Developments in the Mozi Jian Ai Triad.Chris Fraser - unknown
    doctrines of the three Mohist factions mentioned in the Hanfeizi and Zhuangzi (Yu Yue; see his preface to Mozi Jian Gu). The digest theory: Most of the essays can be attributed to three different..
     
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  17. Chang Chü-Shêng Hsien Shêng Ch'i Shih Shêng Jin Chi Nien Lun Wên Chi.Shih Hu, Yüan-chi Chang, Yüan-P'ei Ts'ai & Yün-wu Wang - 1937 - Shang Wu Yin Shu Kuan.
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  18. Transparent, Explainable, and Accountable AI for Robotics.Sandra Wachter, Brent Mittelstadt & Luciano Floridi - 2017 - Science (Robotics) 2 (6):eaan6080.
    To create fair and accountable AI and robotics, we need precise regulation and better methods to certify, explain, and audit inscrutable systems.
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  19.  18
    Classical AI Linguistic Understanding and the Insoluble Cartesian Problem.Rodrigo González - 2019 - AI and Society.
    This paper examines an insoluble Cartesian problem for classical AI, namely, how linguistic understanding involves knowledge and awareness of u’s meaning, a cognitive process that is irreducible to algorithms. As analyzed, Descartes’ view about reason and intelligence has paradoxically encouraged certain classical AI researchers to suppose that linguistic understanding suffices for machine intelligence. Several advocates of the Turing Test, for example, assume that linguistic understanding only comprises computational processes which can be recursively decomposed into algorithmic mechanisms. Against this background, in (...)
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  20.  37
    Pathologies of AI: Responsible Use of Artificial Intelligence in Professional Work. [REVIEW]Ronald Stamper - 1988 - AI and Society 2 (1):3-16.
    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 of terms (...)
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  21.  34
    The AI Elephant.Liu Feng - 1989 - AI and Society 3 (4):336-345.
    The paper presents a Chinese philosophical point of view of AI, and presents a novel system of the AI machine. There are two basic relations or contradictions which drive computer developments forward. One is between software and hardware and the other is between data structure and system organization. It is suggested that a description of a future AI system should primarily start from these contradictions.
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  22.  38
    From AI to Cybernetics.Keizo Sato - 1991 - AI and Society 5 (2):155-161.
    Well-known critics of AI such as Hubert Dreyfus and Michael Polanyi tend to confuse cybernetics with AI. Such a confusion is quite misleading and should not be overlooked. In the first place, cybernetics is not vulnerable to criticism of AI as cognitivistic and behaviouristic. In the second place, AI researchers are recommended to consider the cybernetics approach as a way of overcoming the limitations of cognitivism and behaviourism.
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  23.  37
    AI in Medicine: A Japanese Perspective. [REVIEW]Dr Toshiyuki Furukawa - 1990 - AI and Society 4 (3):196-213.
    This article is concerned with the history and current state of research activities into medical expert systems (MES) in Japan. A brief review of expert systems' work over the last ten years is provided and here is a discussion on future directions of artificial intelligence (AI) applications in medicine, which we expect the Japanese AI community in medicine (AIM) to undertake.
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  24. AI Winter.Steven Umbrello - forthcoming - In Michael Klein & Philip Frana (eds.), Encyclopedia of Artificial Intelligence: The Past, Present, and Future of AI. Santa Barbara, USA: ABC-CLIO.
    Coined in 1984 at the American Association of Artificial intelligence (now the Association for the Advancement of Artificial Intelligence or AAAI), the various boom and bust periods of AI research and funding lead AI researchers Marvin Minsky and Roger Schank to refer to the then-impending bust period as an AI Winter. Canadian AI researcher Daniel Crevier describes the phenomenon as a domino effect that begins with cynicism in the AI research community that then trickles to mass media and finally to (...)
     
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  25.  66
    The Intelligence Left in AI.Denis L. Baggi - 2000 - AI and Society 14 (3-4):348-378.
    In its forty years of existence, Artificial Intelligence has suffered both from the exaggerated claims of those who saw it as the definitive solution of an ancestral dream — that of constructing an intelligent machine-and from its detractors, who described it as the latest fad worthy of quacks. Yet AI is still alive, well and blossoming, and has left a legacy of tools and applications almost unequalled by any other field-probably because, as the heir of Renaissance thought, it represents a (...)
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  26.  48
    AI Methods in Bioethics.Joshua August Skorburg, Walter Sinnott-Armstrong & Vincent Conitzer - 2020 - American Journal of Bioethics: Empirical Bioethics 1 (11):37-39.
    Commentary about the role of AI in bioethics for the 10th anniversary issue of AJOB: Empirical Bioethics.
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  27. Making AI Meaningful Again.Jobst Landgrebe & Barry Smith - 2019 - Synthese:arXiv:1901.02918v1.
    Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial (...)
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  28. Why AI Doomsayers Are Like Sceptical Theists and Why It Matters.John Danaher - 2015 - Minds and Machines 25 (3):231-246.
    An advanced artificial intelligence could pose a significant existential risk to humanity. Several research institutes have been set-up to address those risks. And there is an increasing number of academic publications analysing and evaluating their seriousness. Nick Bostrom’s superintelligence: paths, dangers, strategies represents the apotheosis of this trend. In this article, I argue that in defending the credibility of AI risk, Bostrom makes an epistemic move that is analogous to one made by so-called sceptical theists in the debate about the (...)
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  29. New Developments in the Philosophy of AI.Vincent Müller - 2016 - In Fundamental Issues of Artificial Intelligence. Springer.
    The philosophy of AI has seen some changes, in particular: 1) AI moves away from cognitive science, and 2) the long term risks of AI now appear to be a worthy concern. In this context, the classical central concerns – such as the relation of cognition and computation, embodiment, intelligence & rationality, and information – will regain urgency.
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  30.  25
    Thinking About ‘Ethics’ in the Ethics of AI.Pak-Hang Wong & Judith Simon - 2020 - IDEES 48.
    A major international consultancy firm identified ‘AI ethicist’ as an essential position for companies to successfully implement artificial intelligence (AI) at the start of 2019. It declares that AI ethicists are needed to help companies navigate the ethical and social issues raised by the use of AI. Top 5 AI hires companies need to succeed in 2019. The view that AI is beneficial but nonetheless potentially harmful to individuals and society is widely shared by the industry, academia, governments, and civil (...)
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  31. Friendly Superintelligent AI: All You Need is Love.Michael Prinzing - 2017 - In Vincent Müller (ed.), The Philosophy & Theory of Artificial Intelligence. Berlin: Springer. pp. 288-301.
    There is a non-trivial chance that sometime in the (perhaps somewhat distant) future, someone will build an artificial general intelligence that will surpass human-level cognitive proficiency and go on to become "superintelligent", vastly outperforming humans. The advent of superintelligent AI has great potential, for good or ill. It is therefore imperative that we find a way to ensure-long before one arrives-that any superintelligence we build will consistently act in ways congenial to our interests. This is a very difficult challenge in (...)
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  32.  24
    Functional Dissociation of the Posterior and Anterior Insula in Moral Disgust.Xiaoping Ying, Jing Luo, Chi-yue Chiu, Yanhong Wu, Yan Xu & Jin Fan - 2018 - Frontiers in Psychology 9.
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  33.  51
    Feminist AI: Can We Expect Our AI Systems to Become Feminist?Galit Wellner & Tiran Rothman - forthcoming - Philosophy and Technology:1-15.
    The rise of AI-based systems has been accompanied by the belief that these systems are impartial and do not suffer from the biases that humans and older technologies express. It becomes evident, however, that gender and racial biases exist in some AI algorithms. The question is where the bias is rooted—in the training dataset or in the algorithm? Is it a linguistic issue or a broader sociological current? Works in feminist philosophy of technology and behavioral economics reveal the gender bias (...)
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  34.  38
    A Tale of Two Deficits: Causality and Care in Medical AI.Melvin Chen - forthcoming - Philosophy and Technology.
    In this paper, two central questions will be addressed: ought we to implement medical AI technology in the medical domain? If yes, how ought we to implement this technology? I will critically engage with three options that exist with respect to these central questions: the Neo-Luddite option, the Assistive option, and the Substitutive option. I will first address key objections on behalf of the Neo-Luddite option: the Objection from Bias, the Objection from Artificial Autonomy, the Objection from Status Quo, and (...)
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  35. Philosophy and Theory of Artificial Intelligence, 3–4 October (Report on PT-AI 2011).Vincent C. Müller - 2011 - The Reasoner 5 (11):192-193.
    Report for "The Reasoner" on the conference "Philosophy and Theory of Artificial Intelligence", 3 & 4 October 2011, Thessaloniki, Anatolia College/ACT, http://www.pt-ai.org. --- Organization: Vincent C. Müller, Professor of Philosophy at ACT & James Martin Fellow, Oxford http://www.sophia.de --- Sponsors: EUCogII, Oxford-FutureTech, AAAI, ACM-SIGART, IACAP, ECCAI.
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  36. Hubert L. Dreyfus’s Critique of Classical AI and its Rationalist Assumptions.Setargew Kenaw - 2008 - Minds and Machines 18 (2):227-238.
    This paper deals with the rationalist assumptions behind researches of artificial intelligence (AI) on the basis of Hubert Dreyfus’s critique. Dreyfus is a leading American philosopher known for his rigorous critique on the underlying assumptions of the field of artificial intelligence. Artificial intelligence specialists, especially those whose view is commonly dubbed as “classical AI,” assume that creating a thinking machine like the human brain is not a too far away project because they believe that human intelligence works on the basis (...)
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  37. Theory and Philosophy of AI (Minds and Machines, 22/2 - Special Volume).Vincent C. Müller (ed.) - 2012 - Springer.
    Invited papers from PT-AI 2011. - Vincent C. Müller: Introduction: Theory and Philosophy of Artificial Intelligence - Nick Bostrom: The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents - Hubert L. Dreyfus: A History of First Step Fallacies - Antoni Gomila, David Travieso and Lorena Lobo: Wherein is Human Cognition Systematic - J. Kevin O'Regan: How to Build a Robot that Is Conscious and Feels - Oron Shagrir: Computation, Implementation, Cognition.
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  38.  9
    Differentially Expressed Genes Extracted by the Tensor Robust Principal Component Analysis Method.Yue Hu, Jin-Xing Liu, Ying-Lian Gao, Sheng-Jun Li & Juan Wang - 2019 - Complexity 2019:1-13.
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  39.  38
    AI and the Conquest of Complexity in Law.L. Wolfgang Bibel - 2004 - Artificial Intelligence and Law 12 (3):159-180.
    The paper identifies some of the problems with legal systems and outlines the potential of AI technology for overcoming them. For expository purposes, this outline is based on a simplified epistemology of the primary functions of law. Social and philosophical impediments from the side of the legal community to taking advantage of the potential of this technology are discussed and strategic recommendations are given.
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  40.  23
    Artificial Intelligence and the Body: Dreyfus, Bickhard, and the Future of AI.Daniel Susser - 2013 - In Vincent C. Müller (ed.), Philosophy and Theory of Artificial Intelligence. Berlin: Springer. pp. 277-287.
    For those who find Dreyfus’s critique of AI compelling, the prospects for producing true artificial human intelligence are bleak. An important question thus becomes, what are the prospects for producing artificial non-human intelligence? Applying Dreyfus’s work to this question is difficult, however, because his work is so thoroughly human-centered. Granting Dreyfus that the body is fundamental to intelligence, how are we to conceive of non-human bodies? In this paper, I argue that bringing Dreyfus’s work into conversation with the work of (...)
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  41. Could a Created Being Ever Be Creative? Some Philosophical Remarks on Creativity and AI Development.Y. J. Erden - 2010 - Minds and Machines 20 (3):349-362.
    Creativity has a special role in enabling humans to develop beyond the fulfilment of simple primary functions. This factor is significant for Artificial Intelligence (AI) developers who take replication to be the primary goal, since moves toward creating autonomous artificial-beings beg questions about their potential for creativity. Using Wittgenstein’s remarks on rule-following and language-games, I argue that although some AI programs appear creative, to call these programmed acts creative in our terms is to misunderstand the use of this word in (...)
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  42. Comments on “The Replication of the Hard Problem of Consciousness in AI and Bio-AI”.Blake H. Dournaee - 2010 - Minds and Machines 20 (2):303-309.
    In their joint paper entitled The Replication of the Hard Problem of Consciousness in AI and BIO-AI (Boltuc et al. Replication of the hard problem of conscious in AI and Bio- AI: An early conceptual framework 2008), Nicholas and Piotr Boltuc suggest that machines could be equipped with phenomenal consciousness, which is subjective consciousness that satisfies Chalmer’s hard problem (We will abbreviate the hard problem of consciousness as H-consciousness ). The claim is that if we knew the inner workings of (...)
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  43.  95
    Did Searle Attack Strong Strong AI or Weak Strong AI?Aaron Sloman - 1986 - In Artificial Intelligence and its Applications. Chichester.
    John Searle's attack on the Strong AI thesis, and the published replies, are all based on a failure to distinguish two interpretations of that thesis, a strong one, which claims that the mere occurrence of certain process patterns will suffice for the occurrence of mental states, and a weak one which requires that the processes be produced in the right sort of way. Searle attacks strong strong AI, while most of his opponents defend weak strong AI. This paper explores some (...)
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  44.  9
    Diffusion Tensor Imaging Detects Microstructural Differences of Visual Pathway in Patients With Primary Open-Angle Glaucoma and Ocular Hypertension.Xiang-Yuan Song, Zhen Puyang, Ai-hua Chen, Jin Zhao, Xiao-Jiao Li, Ya-Ying Chen, Wei-jun Tang & Yu-yan Zhang - 2018 - Frontiers in Human Neuroscience 12.
  45.  9
    Did Searle Attack Strong Strong or Weak Strong AI.Aaron Sloman - 1986 - In A. G. Cohn and & R. J. Thomas (eds.), Artificial Intelligence and its Applications. John Wiley and Sons.
    John Searle's attack on the Strong AI thesis, and the published replies, are all based on a failure to distinguish two interpretations of that thesis, a strong one, which claims that the mere occurrence of certain process patterns will suffice for the occurrence of mental states, and a weak one which requires that the processes be produced in the right sort of way. Searle attacks strong strong AI, while most of his opponents defend weak strong AI. This paper explores some (...)
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  46.  8
    Beyond the Middle Finger: Plato, Schiller and the Political Aesthetics of Ai Weiwei.Jason Miller - 2016 - Critical Horizons 17 (3-4):304-323.
    The photograph of Ai Weiwei’s middle finger set against the backdrop of Tiananmen Square has become an icon of politically subversive art. But can we see beyond the middle finger? Here I argue that current theories of political aesthetics operate on an oversimplified dichotomy between two competing paradigms of political art, and that this threatens a more nuanced engagement with contemporary artistic practices. In the first part, I re-examine both the antagonistic relation between art and politics exemplified in Plato's verdict (...)
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  47.  29
    Utilising Appreciative Inquiry (AI) in Creating a Shared Meaning of Ethics in Organisations.L. J. van Vuuren & F. Crous - 2005 - Journal of Business Ethics 57 (4):399-412.
    . The management of ethics within organisations typically occurs within a problem-solving frame of reference. This often results in a reactive, problem-based and externally induced approach to managing ethics. Although basing ethics management interventions on dealing with and preventing current and possible future unethical behaviour are often effective in that it ensures compliance with rules and regulations, the approach is not necessarily conducive to the creation of sustained ethical cultures. Nor does the approach afford (mainly internal) stakeholders the opportunity to (...)
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  48.  30
    AI and Law: What About the Future? [REVIEW]Anja Oskamp, Maaike Tragter & Cees Groendijk - 1995 - Artificial Intelligence and Law 3 (3):209-215.
    The introduction of results of AI and Law research in actual legal practice advances disturbingly slow. One of the problems is that most research can be classified as either theoretical or pragmatic, while combinations of these two are scarce. This interferes with the need for feedback as well as with the need of getting support, both financially and from actual legal practice. The conclusion of this paper is that an emphasis on research that generates operational and sophisticated systems is necessary (...)
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  49.  25
    Die Starke KI-TheseThe Strong AI-Thesis.Stephan Zelewski - 1991 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 22 (2):337-348.
    Summary The controversy about the strong AI-thesis was recently revived by two interrelated contributions stemming from J. R. Searle on the one hand and from P. M. and P. S. Churchland on the other hand. It is shown that the strong AI-thesis cannot be defended in the formulation used by the three authors. It violates some well accepted criterions of scientific argumentation, especially the rejection of essentialistic definitions. Moreover, Searle's ‘proof’ is not conclusive. Though it may be reconstructed in a (...)
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  50. The Debate on the Ethics of AI in Health Care: A Reconstruction and Critical Review.Jessica Morley, Caio C. V. Machado, Christopher Burr, Josh Cowls, Indra Joshi, Mariarosaria Taddeo & Luciano Floridi - manuscript
    Healthcare systems across the globe are struggling with increasing costs and worsening outcomes. This presents those responsible for overseeing healthcare with a challenge. Increasingly, policymakers, politicians, clinical entrepreneurs and computer and data scientists argue that a key part of the solution will be ‘Artificial Intelligence’ (AI) – particularly Machine Learning (ML). This argument stems not from the belief that all healthcare needs will soon be taken care of by “robot doctors.” Instead, it is an argument that rests on the classic (...)
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