Results for 'Joy Chew Oon Ai'

998 found
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  1.  40
    Civics and Moral Education in Singapore: Lessons for Citizenship Education?Joy Chew Oon Ai - 1998 - Journal of Moral Education 27 (4):505-524.
    Abstract Civics and Moral Educationwas implemented as a new moral education programme in Singapore schools in 1992. This paper argues that the underlying theme is that of citizenship training and that new measures are under way to strengthen the capacity of the school system to transmit national values for economic and political socialisation. The motives and motivation for retaining a formal moral education programme have remained strong. A discussion of the structure and content of key modules in Civics and Moral (...)
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  2. Ai Silin Lun Wen Xuan.Silin Ai - 2011 - Zhonghua Shu Ju.
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  3. 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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  4. Ethical Robots: The Future Can Heed Us. [REVIEW]Selmer Bringsjord - 2008 - AI and Society 22 (4):539-550.
    Bill Joy’s deep pessimism is now famous. Why the Future Doesn’t Need Us, his defense of that pessimism, has been read by, it seems, everyone—and many of these readers, apparently, have been converted to the dark side, or rather more accurately, to the future-is-dark side. Fortunately (for us; unfortunately for Joy), the defense, at least the part of it that pertains to AI and robotics, fails. Ours may be a dark future, but we cannot know that on the basis of (...)
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  5. 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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  6.  17
    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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  7.  33
    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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  8.  32
    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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  9. 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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  10.  35
    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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  11.  35
    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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  12.  63
    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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  13. 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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  14. 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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  15. 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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  16. 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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  17.  46
    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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  18.  32
    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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  19. 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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  20. 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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  21. 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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  22.  22
    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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  23.  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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  24. 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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  25. 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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  26.  55
    Grande Sertão: Veredas by João Guimarães Rosa.Felipe W. Martinez, Nancy Fumero & Ben Segal - 2013 - Continent 3 (1):27-43.
    INTRODUCTION BY NANCY FUMERO What is a translation that stalls comprehension? That, when read, parsed, obfuscates comprehension through any language – English, Portuguese. It is inevitable that readers expect fidelity from translations. That language mirror with a sort of precision that enables the reader to become of another location, condition, to grasp in English in a similar vein as readers of Portuguese might from João Guimarães Rosa’s GRANDE SERTÃO: VEREDAS. There is the expectation that translations enable mobility. That what was (...)
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  27.  71
    Joy.Hilary Kathleen Sloan - 2011 - Journal of Value Inquiry 45 (4):419-431.
    Joy is often mentioned in discussion of theories of hedonism, happiness, desire, or religion, but is rarely considered in itself. Consequently, much about the nature of joy remains unclear. Is it, for example, a distinctive state? A feeling? An emotion? Why is it experienced? Does it have a functional role? Through discussion of joy's nature, role, and importance, it will be demonstrated that joy can indeed be defined: as an intense, positively-valenced emotion, whose inherent connection to the desire for self-preservation (...)
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  28.  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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  29.  8
    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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  30.  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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  31.  7
    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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  32.  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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  33.  29
    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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  34. 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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  35. Designing AI for Social Good: Seven Essential Factors.Josh Cowls, Thomas C. King, Mariarosaria Taddeo & Luciano Floridi - manuscript
    The idea of Artificial Intelligence for Social Good (henceforth AI4SG) is gaining traction within information societies in general and the AI community in particular. It has the potential to address social problems effectively through the development of AI-based solutions. Yet, to date, there is only limited understanding of what makes AI socially good in theory, what counts as AI4SG in practice, and how to reproduce its initial successes in terms of policies (Cath et al. 2018). This article addresses this gap (...)
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  36. Supporting Human Autonomy in AI Systems.Rafael Calvo, Dorian Peters, Karina Vold & Richard M. Ryan - forthcoming - In Christopher Burr & Luciano Floridi (eds.), Ethics of Digital Well-being: A Multidisciplinary Approach.
    Autonomy has been central to moral and political philosophy for millenia, and has been positioned as a critical aspect of both justice and wellbeing. Research in psychology supports this position, providing empirical evidence that autonomy is critical to motivation, personal growth and psychological wellness. Responsible AI will require an understanding of, and ability to effectively design for, human autonomy (rather than just machine autonomy) if it is to genuinely benefit humanity. Yet the effects on human autonomy of digital experiences are (...)
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  37. Toward an Ethics of AI Assistants: An Initial Framework.John Danaher - 2018 - Philosophy and Technology 31 (4):629-653.
    Personal AI assistants are now nearly ubiquitous. Every leading smartphone operating system comes with a personal AI assistant that promises to help you with basic cognitive tasks: searching, planning, messaging, scheduling and so on. Usage of such devices is effectively a form of algorithmic outsourcing: getting a smart algorithm to do something on your behalf. Many have expressed concerns about this algorithmic outsourcing. They claim that it is dehumanising, leads to cognitive degeneration, and robs us of our freedom and autonomy. (...)
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  38.  14
    AI and the Path to Envelopment: Knowledge as a First Step Towards the Responsible Regulation and Use of AI-Powered Machines.Scott Robbins - forthcoming - AI and Society:1-10.
    With Artificial Intelligence entering our lives in novel ways—both known and unknown to us—there is both the enhancement of existing ethical issues associated with AI as well as the rise of new ethical issues. There is much focus on opening up the ‘black box’ of modern machine-learning algorithms to understand the reasoning behind their decisions—especially morally salient decisions. However, some applications of AI which are no doubt beneficial to society rely upon these black boxes. Rather than requiring algorithms to be (...)
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  39.  8
    In AI We Trust? Perceptions About Automated Decision-Making by Artificial Intelligence.Theo Araujo, Natali Helberger, Sanne Kruikemeier & Claes H. De Vreese - forthcoming - AI and Society:1-13.
    Fueled by ever-growing amounts of data and advances in artificial intelligence, decision-making in contemporary societies is increasingly delegated to automated processes. Drawing from social science theories and from the emerging body of research about algorithmic appreciation and algorithmic perceptions, the current study explores the extent to which personal characteristics can be linked to perceptions of automated decision-making by AI, and the boundary conditions of these perceptions, namely the extent to which such perceptions differ across media, health, and judicial contexts. Data (...)
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  40.  43
    15 Challenges for AI: Or What AI Can’T Do.Thilo Hagendorff & Katharina Wezel - forthcoming - AI and Society:1-11.
    The current “AI Summer” is marked by scientific breakthroughs and economic successes in the fields of research, development, and application of systems with artificial intelligence. But, aside from the great hopes and promises associated with artificial intelligence, there are a number of challenges, shortcomings and even limitations of the technology. For one, these challenges arise from methodological and epistemological misconceptions about the capabilities of artificial intelligence. Secondly, they result from restrictions of the social context in which the development of applications (...)
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  41.  26
    Non-Artificial Non-Intelligence: Amazon’s Alexa and the Frictions of AI.Tero Karppi & Yvette Granata - 2019 - AI and Society 34 (4):867-876.
    This paper examines a case where Amazon’s cloud-based AI assistant Alexa accidentally ordered a dollhouse for a 6-year-old girl. In the press, the case was defined as a technical recognition problem. Building on this idea, we argue that the dollhouse case helps us to analyze the limits of current AI applications. By drawing on the writings of Gilles Deleuze and François Laruelle, we argue that these limits are not merely technical but more deeply embedded in the structures where the thinking (...)
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  42. The Facets of Artificial Intelligence: A Framework to Track the Evolution of AI.Fernando Martínez-Plumed, Bao Sheng Loe, Peter Flach, Sean O. O. HEigeartaigh, Karina Vold & José Hernández-Orallo - 2018 - In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence Evolution of the contours of AI. pp. 5180-5187.
    We present nine facets for the analysis of the past and future evolution of AI. Each facet has also a set of edges that can summarise different trends and contours in AI. With them, we first conduct a quantitative analysis using the information from two decades of AAAI/IJCAI conferences and around 50 years of documents from AI topics, an official database from the AAAI, illustrated by several plots. We then perform a qualitative analysis using the facets and edges, locating AI (...)
     
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  43.  43
    From Alan Turing to Modern AI: Practical Solutions and an Implicit Epistemic Stance.George F. Luger & Chayan Chakrabarti - 2017 - AI and Society 32 (3):321-338.
    It has been just over 100 years since the birth of Alan Turing and more than 65 years since he published in Mind his seminal paper, Computing Machinery and Intelligence. In the Mind paper, Turing asked a number of questions, including whether computers could ever be said to have the power of “thinking”. Turing also set up a number of criteria—including his imitation game—under which a human could judge whether a computer could be said to be “intelligent”. Turing’s paper, as (...)
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  44. AI, Concepts, and the Paradox of Mental Representation, with a Brief Discussion of Psychological Essentialism.Eric Dietrich - 2001 - J. Of Exper. And Theor. AI 13 (1):1-7.
    Mostly philosophers cause trouble. I know because on alternate Thursdays I am one -- and I live in a philosophy department where I watch all of them cause trouble. Everyone in artificial intelligence knows how much trouble philosophers can cause (and in particular, we know how much trouble one philosopher -- John Searle -- has caused). And, we know where they tend to cause it: in knowledge representation and the semantics of data structures. This essay is about a recent case (...)
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  45. AI, Situatedness, Creativity, and Intelligence; or the Evolution of the Little Hearing Bones.Eric Dietrich - 1996 - J. Of Experimental and Theoretical AI 8 (1):1-6.
    Good sciences have good metaphors. Indeed, good sciences are good because they have good metaphors. AI could use more good metaphors. In this editorial, I would like to propose a new metaphor to help us understand intelligence. Of course, whether the metaphor is any good or not depends on whether it actually does help us. (What I am going to propose is not something opposed to computationalism -- the hypothesis that cognition is computation. Noncomputational metaphors are in vogue these days, (...)
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  46.  7
    Interperforming in AI: Question of ‘Natural’ in Machine Learning and Recurrent Neural Networks.Tolga Yalur - forthcoming - AI and Society:1-9.
    This article offers a critical inquiry of contemporary neural network models as an instance of machine learning, from an interdisciplinary perspective of AI studies and performativity. It shows the limits on the architecture of these network systems due to the misemployment of ‘natural’ performance, and it offers ‘context’ as a variable from a performative approach, instead of a constant. The article begins with a brief review of machine learning-based natural language processing systems and continues with a concentration on the relevant (...)
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  47. AI and the Mechanistic Forces of Darkness.Eric Dietrich - 1995 - J. Of Experimental and Theoretical AI 7 (2):155-161.
    Under the Superstition Mountains in central Arizona toil those who would rob humankind o f its humanity. These gray, soulless monsters methodically tear away at our meaning, our subjectivity, our essence as transcendent beings. With each advance, they steal our freedom and dignity. Who are these denizens of darkness, these usurpers of all that is good and holy? None other than humanity’s arch-foe: The Cognitive Scientists -- AI researchers, fallen philosophers, psychologists, and other benighted lovers of computers. Unless they are (...)
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  48. On the Role of AI in the Ongoing Paradigm Shift Within the Cognitive Sciences.Tom Froese - 2007 - In M. Lungarella (ed.), 50 Years of AI. Springer Verlag.
    This paper supports the view that the ongoing shift from orthodox to embodied-embedded cognitive science has been significantly influenced by the experimental results generated by AI research. Recently, there has also been a noticeable shift toward enactivism, a paradigm which radicalizes the embodied-embedded approach by placing autonomous agency and lived subjectivity at the heart of cognitive science. Some first steps toward a clarification of the relationship of AI to this further shift are outlined. It is concluded that the success of (...)
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  49. Surprised by Joy: The Shape of My Early Life.C. S. Lewis - 1995 - Houghton Mifflin Harcourt.
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  50.  11
    Culture, the Process of Knowledge, Perception of the World and Emergence of AI.Badrudin Amershi - forthcoming - AI and Society:1-14.
    Considering the technological development today, we are facing an emerging crisis. We are in the midst of a scientific revolution, which promises to radically change not only the way we live and work—but beyond that challenge the stability of the very foundations of our civilization and the international political order. All our attention and effort is thus focused on cushioning its impacts on life and society. Looking back in history, it would be pertinent to ask whether this process is a (...)
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