Results for 'Electrochemical machining'

740 found
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  1.  98
    Experimental Research Work to Optimize Process Parameters Into Electro Chemical Abrasive Flow Machining Using Taguchi Methodology.Sandeep Singh & Sunil Kumar - 2017 - International Journal of Trend in Scientific Research and Development 1 (4):22-29.
    Electrochemical assisted abrasive flow finishing is a newly developed hybrid finishing process which is used to finish the internal parts of work piece having complicated geometry to large extent. In electrochemical assisted abrasive flow machining higher abrasion of the material was detected due to the combine effect of ECM and AFF processes. In Electrochemical aided abrasive flow machining a electrolyte is added to the prepared media .This media consist a kind of polymeric carrier and abrasive (...)
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  2. Experimental Research to Optimize Process Parameters in Machining of Non Conducting Material with Hybrid Non Conconventional Machining.Vikrant Sharma & Sunil Kumar - 2017 - International Journal of Trend in Scientific Research and Development 1 (4):107-116.
    Among all non conventional micro machining, electrochemical discharge machining ECDM is having high quality of material removal rate with zero residual stress. This machining has been accepted as a highly modern technology in micromachining. In this paper an effort has been done on micro drilling of glass using electrochemical discharge machining ECDM . A fixed tool and a step down transformer have been used to support the steady machining to increase the accuracy of (...)
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  3. The Infrasonics and Electronics of Bionics.Varanasi Ramabrahmam - 2009 - In Proceedings of Presentations at International Conference on Photonics, Nano-Technology and Computer Applications (ICOPNAC- 2009), 25-28 February 2009 Held at Center for Research and Development, PRIST UNIVERSITY,. pp. 20-39.
    The concepts developed using Upanishadic insight regarding human consciousness, mind and mental processes and their applications in information acquisition and transmission by, through and in human body will be used to model human cognitive processes. A sequential reversible process by the stepwise transformation of (i) infrasonic form of energy and transformation of information already stored in (ii) biochemical form within as memory, and retrieved as inner mental world into (iii) electrochemical and then into (iv) mechanical form while communicating and (...)
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  4. Can Machines Read Our Minds?Christopher Burr & Nello Cristianini - 2019 - Minds and Machines 29 (3):461-494.
    We explore the question of whether machines can infer information about our psychological traits or mental states by observing samples of our behaviour gathered from our online activities. Ongoing technical advances across a range of research communities indicate that machines are now able to access this information, but the extent to which this is possible and the consequent implications have not been well explored. We begin by highlighting the urgency of asking this question, and then explore its conceptual underpinnings, in (...)
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  5. Organisms ≠ Machines.Daniel J. Nicholson - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):669-678.
    The machine conception of the organism (MCO) is one of the most pervasive notions in modern biology. However, it has not yet received much attention by philosophers of biology. The MCO has its origins in Cartesian natural philosophy, and it is based on the metaphorical redescription of the organism as a machine. In this paper I argue that although organisms and machines resemble each other in some basic respects, they are actually very different kinds of systems. I submit that the (...)
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  6. The Machine Conception of the Organism in Development and Evolution: A Critical Analysis.Daniel J. Nicholson - 2014 - Studies in History and Philosophy of Biological and Biomedical Sciences 48:162-174.
    This article critically examines one of the most prevalent metaphors in modern biology, namely the machine conception of the organism (MCO). Although the fundamental differences between organisms and machines make the MCO an inadequate metaphor for conceptualizing living systems, many biologists and philosophers continue to draw upon the MCO or tacitly accept it as the standard model of the organism. This paper analyses the specific difficulties that arise when the MCO is invoked in the study of development and evolution. In (...)
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  7. Why Machines Cannot Be Moral.Robert Sparrow - 2021 - AI and Society:1-9.
    The fact that real-world decisions made by artificial intelligences are often ethically loaded has led a number of authorities to advocate the development of “moral machines”. I argue that the project of building “ethics” “into” machines presupposes a flawed understanding of the nature of ethics. Drawing on the work of the Australian philosopher, Raimond Gaita, I argue that ethical dilemmas are problems for particular people and not problems for everyone who faces a similar situation. Moreover, the force of an ethical (...)
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  8. Machines as Moral Patients We Shouldn’T Care About : The Interests and Welfare of Current Machines.John Basl - 2014 - Philosophy and Technology 27 (1):79-96.
    In order to determine whether current (or future) machines have a welfare that we as agents ought to take into account in our moral deliberations, we must determine which capacities give rise to interests and whether current machines have those capacities. After developing an account of moral patiency, I argue that current machines should be treated as mere machines. That is, current machines should be treated as if they lack those capacities that would give rise to psychological interests. Therefore, they (...)
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  9. Time Travel and Time Machines.Chris Smeenk & Christian Wuthrich - 2011 - In Craig Callender (ed.), The Oxford Handbook of Philosophy of Time. Oxford: Oxford University Press. pp. 577-630.
    This paper is an enquiry into the logical, metaphysical, and physical possibility of time travel understood in the sense of the existence of closed worldlines that can be traced out by physical objects. We argue that none of the purported paradoxes rule out time travel either on grounds of logic or metaphysics. More relevantly, modern spacetime theories such as general relativity seem to permit models that feature closed worldlines. We discuss, in the context of Gödel's infamous argument for the ideality (...)
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  10. Machine Morality, Moral Progress, and the Looming Environmental Disaster.Ben Kenward & Thomas Sinclair - forthcoming - Cognitive Computation and Systems.
    The creation of artificial moral systems requires us to make difficult choices about which of varying human value sets should be instantiated. The industry-standard approach is to seek and encode moral consensus. Here we argue, based on evidence from empirical psychology, that encoding current moral consensus risks reinforcing current norms, and thus inhibiting moral progress. However, so do efforts to encode progressive norms. Machine ethics is thus caught between a rock and a hard place. The problem is particularly acute when (...)
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  11. Why Machine-Information Metaphors Are Bad for Science and Science Education.Massimo Pigliucci & Maarten Boudry - 2011 - Science & Education 20 (5-6):471.
    Genes are often described by biologists using metaphors derived from computa- tional science: they are thought of as carriers of information, as being the equivalent of ‘‘blueprints’’ for the construction of organisms. Likewise, cells are often characterized as ‘‘factories’’ and organisms themselves become analogous to machines. Accordingly, when the human genome project was initially announced, the promise was that we would soon know how a human being is made, just as we know how to make airplanes and buildings. Impor- tantly, (...)
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  12. Machine Learning and Irresponsible Inference: Morally Assessing the Training Data for Image Recognition Systems.Owen King - 2019 - In Matteo Vincenzo D'Alfonso & Don Berkich (eds.), On the Cognitive, Ethical, and Scientific Dimensions of Artificial Intelligence. Springer Verlag. pp. 265-282.
    Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which they (...)
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  13. Minds and Machines.Hilary Putnam - 1960 - In Sidney Hook (ed.), Dimensions of Minds. New York, USA: New York University Press. pp. 138-164.
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  14.  48
    Clinical Applications of Machine Learning Algorithms: Beyond the Black Box.David S. Watson, Jenny Krutzinna, Ian N. Bruce, Christopher E. M. Griffiths, Iain B. McInnes, Michael R. Barnes & Luciano Floridi - 2019 - British Medical Journal 364:I886.
    Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.
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  15. A Machine That Knows Its Own Code.Samuel A. Alexander - 2014 - Studia Logica 102 (3):567-576.
    We construct a machine that knows its own code, at the price of not knowing its own factivity.
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  16.  44
    Fair Machine Learning Under Partial Compliance.Jessica Dai, Sina Fazelpour & Zachary Lipton - 2021 - In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society. pp. 55–65.
    Typically, fair machine learning research focuses on a single decision maker and assumes that the underlying population is stationary. However, many of the critical domains motivating this work are characterized by competitive marketplaces with many decision makers. Realistically, we might expect only a subset of them to adopt any non-compulsory fairness-conscious policy, a situation that political philosophers call partial compliance. This possibility raises important questions: how does partial compliance and the consequent strategic behavior of decision subjects affect the allocation outcomes? (...)
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  17. Languages, Machines, and Classical Computation.Luis M. Augusto - 2021 - London, UK: College Publications.
    3rd ed, 2021. A circumscription of the classical theory of computation building up from the Chomsky hierarchy. With the usual topics in formal language and automata theory.
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  18. Machine Intentionality, the Moral Status of Machines, and the Composition Problem.David Leech Anderson - 2012 - In Vincent C. Müller (ed.), Philosophy & Theory of Artificial Intelligence. Springer. pp. 312-333.
    According to the most popular theories of intentionality, a family of theories we will refer to as “functional intentionality,” a machine can have genuine intentional states so long as it has functionally characterizable mental states that are causally hooked up to the world in the right way. This paper considers a detailed description of a robot that seems to meet the conditions of functional intentionality, but which falls victim to what I call “the composition problem.” One obvious way to escape (...)
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  19. Understanding From Machine Learning Models.Emily Sullivan - forthcoming - British Journal for the Philosophy of Science:axz035.
    Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding misguided? In (...)
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  20.  82
    Can Machines Be People? Reflections on the Turing Triage Test.Robert Sparrow - 2012 - In Patrick Lin, Keith Abney & George Bekey (eds.), Robot Ethics: The Ethical and Social Implications of Robotics. MIT Press. pp. 301-315.
    In, “The Turing Triage Test”, published in Ethics and Information Technology, I described a hypothetical scenario, modelled on the famous Turing Test for machine intelligence, which might serve as means of testing whether or not machines had achieved the moral standing of people. In this paper, I: (1) explain why the Turing Triage Test is of vital interest in the context of contemporary debates about the ethics of AI; (2) address some issues that complexify the application of this test; and, (...)
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  21. Making Moral Machines: Why We Need Artificial Moral Agents.Paul Formosa & Malcolm Ryan - forthcoming - AI and Society.
    As robots and Artificial Intelligences become more enmeshed in rich social contexts, it seems inevitable that we will have to make them into moral machines equipped with moral skills. Apart from the technical difficulties of how we could achieve this goal, we can also ask the ethical question of whether we should seek to create such Artificial Moral Agents (AMAs). Recently, several papers have argued that we have strong reasons not to develop AMAs. In response, we develop a comprehensive analysis (...)
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  22.  46
    Semiotic Machine.Mihai Nadin - unknown
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  23. The Experience Machine and Mental State Theories of Well-Being.Jason Kawall - 1999 - Journal of Value Inquiry 33 (3):381-387.
    It is argued that Nozick's experience machine thought experiment does not pose a particular difficulty for mental state theories of well-being. While the example shows that we value many things beyond our mental states, this simply reflects the fact that we value more than our own well-being. Nor is a mental state theorist forced to make the dubious claim that we maintain these other values simply as a means to desirable mental states. Valuing more than our mental states is compatible (...)
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  24. Building Machines That Learn and Think About Morality.Christopher Burr & Geoff Keeling - 2018 - In Proceedings of the Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB 2018). Society for the Study of Artificial Intelligence and Simulation of Behaviour.
    Lake et al. propose three criteria which, they argue, will bring artificial intelligence (AI) systems closer to human cognitive abilities. In this paper, we explore the application of these criteria to a particular domain of human cognition: our capacity for moral reasoning. In doing so, we explore a set of considerations relevant to the development of AI moral decision-making. Our main focus is on the relation between dual-process accounts of moral reasoning and model-free/model-based forms of machine learning. We also discuss (...)
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  25. The Experience Machine.Ben Bramble - 2016 - Philosophy Compass 11 (3):136-145.
    In this paper, I reconstruct Robert Nozick's experience machine objection to hedonism about well-being. I then explain and briefly discuss the most important recent criticisms that have been made of it. Finally, I question the conventional wisdom that the experience machine, while it neatly disposes of hedonism, poses no problem for desire-based theories of well-being.
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  26. The Experience Machine and the Experience Requirement.Jennifer Hawkins - 2016 - In Guy Fletcher (ed.), The Routledge Handbook of Philosophy of Well-Being. New York, NY, USA: Routledge. pp. 355-365.
    In this article I explore various facets of Nozick’s famous thought experiment involving the experience machine. Nozick’s original target is hedonism—the view that the only intrinsic prudential value is pleasure. But the argument, if successful, undermines any experientialist theory, i.e. any theory that limits intrinsic prudential value to mental states. I first highlight problems arising from the way Nozick sets up the thought experiment. He asks us to imagine choosing whether or not to enter the machine and uses our choice (...)
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  27. The Mismeasure of Machine: Synthetic Biology and the Trouble with Engineering Metaphors.Maarten Boudry & Massimo Pigliucci - 2013 - Studies in History and Philosophy of Biological and Biomedical Sciences (4):660-668.
    The scientific study of living organisms is permeated by machine and design metaphors. Genes are thought of as the ‘‘blueprint’’ of an organism, organisms are ‘‘reverse engineered’’ to discover their func- tionality, and living cells are compared to biochemical factories, complete with assembly lines, transport systems, messenger circuits, etc. Although the notion of design is indispensable to think about adapta- tions, and engineering analogies have considerable heuristic value (e.g., optimality assumptions), we argue they are limited in several important respects. In (...)
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  28. Machines Learning Values.Steve Petersen - 2020 - In S. Matthew Liao (ed.), Ethics of Artificial Intelligence. New York, USA: Oxford University Press.
    Whether it would take one decade or several centuries, many agree that it is possible to create a *superintelligence*---an artificial intelligence with a godlike ability to achieve its goals. And many who have reflected carefully on this fact agree that our best hope for a "friendly" superintelligence is to design it to *learn* values like ours, since our values are too complex to program or hardwire explicitly. But the value learning approach to AI safety faces three particularly philosophical puzzles: first, (...)
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  29. The Mismeasure of Machine: Synthetic Biology and the Trouble with Engineering Metaphors.Maarten Boudry & Massimo Pigliucci - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):660-668.
    The scientific study of living organisms is permeated by machine and design metaphors. Genes are thought of as the ‘‘blueprint’’ of an organism, organisms are ‘‘reverse engineered’’ to discover their functionality, and living cells are compared to biochemical factories, complete with assembly lines, transport systems, messenger circuits, etc. Although the notion of design is indispensable to think about adaptations, and engineering analogies have considerable heuristic value (e.g., optimality assumptions), we argue they are limited in several important respects. In particular, the (...)
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  30. Do Machines Have Prima Facie Duties?Gary Comstock - 2015 - In Machine Medical Ethics. London: Springer. pp. 79-92.
    A properly programmed artificially intelligent agent may eventually have one duty, the duty to satisfice expected welfare. We explain this claim and defend it against objections.
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  31.  54
    External Human–Machine Interfaces for Autonomous Vehicle-to-Pedestrian Communication: A Review of Empirical Work. [REVIEW]Alexandros Rouchitsas & Håkan Alm - 2019 - Frontiers in Psychology 10.
    Interaction between drivers and pedestrians is often facilitated by informal communicative cues, like hand gestures, facial expressions, and eye contact. In the near future, however, when semi- and fully autonomous vehicles are introduced into the traffic system, drivers will gradually assume the role of mere passengers, who are casually engaged in non-driving-related activities and, therefore, unavailable to participate in traffic interaction. In this novel traffic environment, advanced communication interfaces will need to be developed that inform pedestrians of the current state (...)
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  32.  16
    Machine-Believers Learning Faiths & Knowledges: The New Gospel of Artificial Intelligence.Virgil W. Brower - 2021 - Internationales Jahrbuch Für Medienphilosophie 7 (1):97-121.
    One is occasionally reminded of Foucault's proclamation in a 1970 interview that "perhaps, one day this century will be known as Deleuzian." Less often is one compelled to update and restart with a supplementary counter-proclamation of the mathematician, David Lindley: "the twenty-first century would be a Bayesian era..." The verb tenses of both are conspicuous. // To critically attend to what is today often feared and demonized, but also revered, deployed, and commonly referred to as algorithm(s), one cannot avoid the (...)
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  33. Desired Machines: Cinema and the World in Its Own Image.Jimena Canales - 2011 - Science in Context 24 (3):329-359.
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  34. Why Machines Can Neither Think nor Feel.Douglas C. Long - 1994 - In Dale W. Jamieson (ed.), Language, Mind and Art. Kluwer Academic Publishers.
    Over three decades ago, in a brief but provocative essay, Paul Ziff argued for the thesis that robots cannot have feelings because they are "mechanisms, not organisms, not living creatures. There could be a broken-down robot but not a dead one. Only living creatures can literally have feelings."[i] Since machines are not living things they cannot have feelings. In the first half of my paper I review Ziff's arguments against the idea that robots could be conscious, especially his appeal to (...)
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  35. In Defense of Happiness: A Response to the Experience Machine.Matthew Silverstein - 2000 - Social Theory and Practice 26 (2):279-300.
    Many philosophers believe that Robert Nozick's experience machine argument poses an insurmountable obstacle to hedonism as a theory of well-being. After an initial attempt to demonstrate that the persuasiveness of this argument rests on a key ambiguity, I argue that the intuitions to which the thought experiment appeals are not nearly as clear as many philosophers suppose they are. I believe that a careful consideration of the origin of those intuitions -- especially in light of the so-called "paradox of hedonism" (...)
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  36.  35
    Machines with Human-Like Commonsense.Antonio Lieto - 2021 - 18th Japanese Society for Artificial Intelligence General-Purpose Artificial Intelligence Meeting Group (SIG-AGI).
    I will review the main problems concerning commonsense reasoning in machines and I will present resent two different applications - namaly: the Dual PECCS linguistic categorization system and the TCL reasoning framework that have been developed to address, respectively, the problem of typicality effects and the one of commonsense compositionality, in a way that is integrated or compliant with different cognitive architectures thus extending their knowledge processing capabilities In doing so I will show how such aspects are better dealt with (...)
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  37. Rethinking Machine Ethics in the Era of Ubiquitous Technology.Jeffrey White (ed.) - 2015 - IGI.
    Table of Contents Foreword .................................................................................................... ......................................... xiv Preface .................................................................................................... .............................................. xv Acknowledgment .................................................................................................... .......................... xxiii Section 1 On the Cusp: Critical Appraisals of a Growing Dependency on Intelligent Machines Chapter 1 Algorithms versus Hive Minds and the Fate of Democracy ................................................................... 1 Rick Searle, IEET, USA Chapter 2 We Can Make Anything: Should We? .................................................................................................. 15 Chris Bateman, University of Bolton, UK Chapter 3 Grounding Machine Ethics within the Natural System ........................................................................ 30 Jared Gassen, JMG Advising, USA Nak Young Seong, Independent Scholar, South (...)
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  38. Creativity and the Machine. How Technology Reshapes Language.Fabio Fossa - 2017 - Odradek 3 (1-2):178-208.
    In scientific communications, journal articles, and philosophical aesthetic debates the words “art”, “creativity”, and “machine” are put together more and more frequently. Since some machines are designed to, or happens to, imitate human artistic creativity, it seems natural to use the same words to talk about human artists and machines which imitate them. However, the evolution of language in light of technology may conceal specific features of the phenomena it is supposed to describe. This makes it difficult to understand what (...)
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  39. “Man-Machines and Embodiment: From Cartesian Physiology to Claude Bernard’s ‘Living Machine’”.Charles T. Wolfe & Philippe Huneman - forthcoming - In Justin E. H. Smith (ed.), Embodiment, Oxford Philosophical Concepts. Oxford University Press.
    A common and enduring early modern intuition is that materialists reduce organisms in general and human beings in particular to automata. Wasn’t a famous book of the time entitled L’Homme-Machine? In fact, the machine is employed as an analogy, and there was a specifically materialist form of embodiment, in which the body is not reduced to an inanimate machine, but is conceived as an affective, flesh-and-blood entity. We discuss how mechanist and vitalist models of organism exist in a more complementary (...)
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  40. Machine Intelligence: A Chimera.Mihai Nadin - 2019 - AI and Society 34 (2):215-242.
    The notion of computation has changed the world more than any previous expressions of knowledge. However, as know-how in its particular algorithmic embodiment, computation is closed to meaning. Therefore, computer-based data processing can only mimic life’s creative aspects, without being creative itself. AI’s current record of accomplishments shows that it automates tasks associated with intelligence, without being intelligent itself. Mistaking the abstract for the concrete has led to the religion of “everything is an output of computation”—even the humankind that conceived (...)
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  41. Machine Art or Machine Artists? Dennett, Danto, and the Expressive Stance.Adam Linson - 2016 - In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library). Berlin: Springer. pp. 441-456.
    As art produced by autonomous machines becomes increasingly common, and as such machines grow increasingly sophisticated, we risk a confusion between art produced by a person but mediated by a machine, and art produced by what might be legitimately considered a machine artist. This distinction will be examined here. In particular, my argument seeks to close a gap between, on one hand, a philosophically grounded theory of art and, on the other hand, theories concerned with behavior, intentionality, expression, and creativity (...)
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  42. Logically Possible Machines.Eric Steinhart - 2002 - Minds and Machines 12 (2):259-280.
    I use modal logic and transfinite set-theory to define metaphysical foundations for a general theory of computation. A possible universe is a certain kind of situation; a situation is a set of facts. An algorithm is a certain kind of inductively defined property. A machine is a series of situations that instantiates an algorithm in a certain way. There are finite as well as transfinite algorithms and machines of any degree of complexity (e.g., Turing and super-Turing machines and more). There (...)
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  43.  75
    Human Induction in Machine Learning: A Survey of the Nexus.Petr Spelda & Vit Stritecky - forthcoming - ACM Computing Surveys.
    As our epistemic ambitions grow, the common and scientific endeavours are becoming increasingly dependent on Machine Learning (ML). The field rests on a single experimental paradigm, which consists of splitting the available data into a training and testing set and using the latter to measure how well the trained ML model generalises to unseen samples. If the model reaches acceptable accuracy, an a posteriori contract comes into effect between humans and the model, supposedly allowing its deployment to target environments. Yet (...)
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  44. The Experience Machine: Existential Reflections on Virtual Worlds.Stefano Gualeni - 2016 - Journal of Virtual Worlds Research 9 (3).
    Problems and questions originally raised by Robert Nozick in his famous thought experiment ‘The Experience Machine’ are frequently invoked in the current discourse concerning virtual worlds. Having conceptualized his Gedankenexperiment in the early seventies, Nozick could not fully anticipate the numerous and profound ways in which the diffusion of computer simulations and video games came to affect the Western world. -/- This article does not articulate whether or not the virtual worlds of video games, digital simulations, and virtual technologies currently (...)
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  45. Exploring Machine Learning Techniques for Coronary Heart Disease Prediction.Hisham Khdair - 2021 - International Journal of Advanced Computer Science and Applications 12 (5):28-36.
    Coronary Heart Disease (CHD) is one of the leading causes of death nowadays. Prediction of the disease at an early stage is crucial for many health care providers to protect their patients and save lives and costly hospitalization resources. The use of machine learning in the prediction of serious disease events using routine medical records has been successful in recent years. In this paper, a comparative analysis of different machine learning techniques that can accurately predict the occurrence of CHD events (...)
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  46. The Motivations and Risks of Machine Ethics.Stephen Cave, Rune Nyrup, Karina Vold & Adrian Weller - 2019 - Proceedings of the IEEE 107 (3):562-574.
    Many authors have proposed constraining the behaviour of intelligent systems with ‘machine ethics’ to ensure positive social outcomes from the development of such systems. This paper critically analyses the prospects for machine ethics, identifying several inherent limitations. While machine ethics may increase the probability of ethical behaviour in some situations, it cannot guarantee it due to the nature of ethics, the computational limitations of computational agents and the complexity of the world. In addition, machine ethics, even if it were to (...)
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  47. Consequences of Unexplainable Machine Learning for the Notions of a Trusted Doctor and Patient Autonomy.Michal Klincewicz & Lily Frank - 2020 - Proceedings of the 2nd EXplainable AI in Law Workshop (XAILA 2019) Co-Located with 32nd International Conference on Legal Knowledge and Information Systems (JURIX 2019).
    This paper provides an analysis of the way in which two foundational principles of medical ethics–the trusted doctor and patient autonomy–can be undermined by the use of machine learning (ML) algorithms and addresses its legal significance. This paper can be a guide to both health care providers and other stakeholders about how to anticipate and in some cases mitigate ethical conflicts caused by the use of ML in healthcare. It can also be read as a road map as to what (...)
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  48.  37
    Machinic Thinking.Alistair Welchman - 1997 - In Keith Ansell Pearson (ed.), Deleuze and Philosophy: The Difference Engineer. London, UK: pp. 211-227.
    This paper argues that the transcendence (most obviously theological) has skewed much of Western thinking by forcing material complexity to be interpreted as the intervention of something immaterial. Contemporary terms in the anglophone world that can play this role are: intentionality (privatised teleology), representation and semantics. Deleuze launches a powerful critique of residually theological reasoning that has wide application in both philosophy and science. This critique converges with and deepens, perhaps surprisingly for a French philosopher, similar critiques that are being (...)
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  49.  58
    The Explanation Game: A Formal Framework for Interpretable Machine Learning.David S. Watson & Luciano Floridi - 2020 - Synthese 198 (10):1–⁠32.
    We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...)
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  50. The Role of Imagination in Social Scientific Discovery: Why Machine Discoverers Will Need Imagination Algorithms.Michael Stuart - 2019 - In Mark Addis, Fernand Gobet & Peter Sozou (eds.), Scientific Discovery in the Social Sciences. Springer Verlag.
    When philosophers discuss the possibility of machines making scientific discoveries, they typically focus on discoveries in physics, biology, chemistry and mathematics. Observing the rapid increase of computer-use in science, however, it becomes natural to ask whether there are any scientific domains out of reach for machine discovery. For example, could machines also make discoveries in qualitative social science? Is there something about humans that makes us uniquely suited to studying humans? Is there something about machines that would bar them from (...)
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