Results for 'L. L. Machin'

986 found
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  1.  27
    Making the (Business) Case for Clinical Ethics Support in the UK.L. L. Machin & Mark Wilkinson - 2020 - HEC Forum 33 (4):371-391.
    This paper provides a series of reflections on making the case to senior leaders for the introduction of clinical ethics support services within a UK hospital Trust at a time when clinical ethics committees are dwindling in the UK. The paper provides key considerations for those building a case for clinical ethics support within hospitals by drawing upon published academic literature, and key reports from governmental and professional bodies. We also include extracts from documents relating to, and annual reports of, (...)
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  2.  22
    Engaging Tomorrow’s Doctors in Clinical Ethics: Implications for Healthcare Organisations.Laura L. Machin & Robin D. Proctor - 2020 - Health Care Analysis 29 (4):319-342.
    Clinical ethics can be viewed as a practical discipline that provides a structured approach to assist healthcare practitioners in identifying, analysing and resolving ethical issues that arise in practice. Clinical ethics can therefore promote ethically sound clinical and organisational practices and decision-making, thereby contributing to health organisation and system quality improvement. In order to develop students’ decision-making skills, as well as prepare them for practice, we decided to introduce a clinical ethics strand within an undergraduate medical curriculum. We designed a (...)
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  3.  16
    Identification and Description of Novel Mood Profile Clusters.L. Parsons-Smith Renée, C. Terry Peter & Machin M. Anthony - 2017 - Frontiers in Psychology 8.
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  4.  9
    Exploring the perceived benefits of ethics education for laboratory professionals.Khojasta Talash, Chloe Anthias & Laura L. Machin - 2022 - International Journal of Ethics Education 7 (1):201-212.
    Clinical laboratories face ethical challenges on a daily basis. The ethics training provided for clinical laboratory staff is variable, with some receiving no training. We aimed to explore the perceived benefits of ethics education for laboratory professionals. Ethics training was provided to approximately 60 laboratory professionals in a UK not-for-profit blood cancer organisation, with group discussions incorporated into the session. The session covered dominant ethical theories and principles, the defining moments in medical research ethics and the ethical aspects of laboratory (...)
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  5. The nonhuman condition: Radical democracy through new materialist lenses.Hans Asenbaum, Amanda Machin, Jean-Paul Gagnon, Diana Leong, Melissa Orlie & James Louis Smith - 2023 - Contemporary Political Theory (Online first):584-615.
    Radical democratic thinking is becoming intrigued by the material situatedness of its political agents and by the role of nonhuman participants in political interaction. At stake here is the displacement of narrow anthropocentrism that currently guides democratic theory and practice, and its repositioning into what we call ‘the nonhuman condition’. This Critical Exchange explores the nonhuman condition. It asks: What are the implications of decentering the human subject via a new materialist reading of radical democracy? Does this reading dilute political (...)
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  6.  18
    Towards a social semiotics of rhythm in popular music.David Machin - 2013 - Semiotica 2013 (197):119-140.
    Name der Zeitschrift: Semiotica - Journal of the International Association for Semiotic Studies / Revue de l'Association Internationale de Sémiotique Jahrgang: 2013 Heft: 197 Seiten: 119-140.
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  7. Building machine learning pipelines.H. Hapke & L. Nelson - 2020 - O’Reilly Media.
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  8. Smart contract based data trading mode using blockchain and machine learning.W. Xiong & L. Xiong - 2019 - IEEE Access 7.
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  9.  42
    Machine Translation.L. Jonathan Cohen & A. D. Booth - 1970 - Philosophical Quarterly 20 (79):187.
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  10.  21
    Mental machines.David L. Barack - 2019 - Biology and Philosophy 34 (6):63.
    Cognitive neuroscientists are turning to an increasingly rich array of neurodynamical systems to explain mental phenomena. In these explanations, cognitive capacities are decomposed into a set of functions, each of which is described mathematically, and then these descriptions are mapped on to corresponding mathematical descriptions of the dynamics of neural systems. In this paper, I outline a novel explanatory schema based on these explanations. I then argue that these explanations present a novel type of dynamicism for the philosophy of mind (...)
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  11. Neural reuse: A fundamental organizational principle of the brain.Michael L. Anderson - 2010 - Behavioral and Brain Sciences 33 (4):245.
    An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role of neural plasticity (...)
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  12. Engineering machine consciousness.L. S. Coles - 1993 - AI Expert 8:34-41.
     
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  13.  50
    Predictive Power of “A Minima” Models in Biology.L. Almeida & J. Demongeot - 2012 - Acta Biotheoretica 60 (1-2):3-19.
    Many apparently complex mechanisms in biology, especially in embryology and molecular biology, can be explained easily by reasoning at the level of the “efficient cause” of the observed phenomenology: the mechanism can then be explained by a simple geometrical argument or a variational principle, leading to the solution of an optimization problem, for example, via the co-existence of a minimization and a maximization problem . Passing from a microscopic level to the macroscopic level often involves an averaging effect that gives (...)
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  14.  32
    Mental machines.David L. Barack - 2019 - Biology and Philosophy 34 (6):63.
    Cognitive neuroscientists are turning to an increasingly rich array of neurodynamical systems to explain mental phenomena. In these explanations, cognitive capacities are decomposed into a set of functions, each of which is described mathematically, and then these descriptions are mapped on to corresponding mathematical descriptions of the dynamics of neural systems. In this paper, I outline a novel explanatory schema based on these explanations. I then argue that these explanations present a novel type of dynamicism for the philosophy of mind (...)
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  15.  14
    Mental machines.David L. Barack - 2019 - Biology and Philosophy 34 (6):63.
    Cognitive neuroscientists are turning to an increasingly rich array of neurodynamical systems to explain mental phenomena. In these explanations, cognitive capacities are decomposed into a set of functions, each of which is described mathematically, and then these descriptions are mapped on to corresponding mathematical descriptions of the dynamics of neural systems. In this paper, I outline a novel explanatory schema based on these explanations. I then argue that these explanations present a novel type of dynamicism for the philosophy of mind (...)
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  16. Virtual machines and consciousness.Aaron Sloman & Ronald L. Chrisley - 2003 - Journal of Consciousness Studies 10 (4-5):133-172.
    Replication or even modelling of consciousness in machines requires some clarifications and refinements of our concept of consciousness. Design of, construction of, and interaction with artificial systems can itself assist in this conceptual development. We start with the tentative hypothesis that although the word “consciousness” has no well-defined meaning, it is used to refer to aspects of human and animal informationprocessing. We then argue that we can enhance our understanding of what these aspects might be by designing and building virtual-machine (...)
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  17.  83
    Machines, Consciousness, and Thought.Robert L. Arrington - 1999 - Idealistic Studies 29 (3):231-243.
  18. Machines and the Moral Community.Erica L. Neely - 2013 - Philosophy and Technology 27 (1):97-111.
    A key distinction in ethics is between members and nonmembers of the moral community. Over time, our notion of this community has expanded as we have moved from a rationality criterion to a sentience criterion for membership. I argue that a sentience criterion is insufficient to accommodate all members of the moral community; the true underlying criterion can be understood in terms of whether a being has interests. This may be extended to conscious, self-aware machines, as well as to any (...)
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  19.  57
    Representationalism and the metonymic fallacy.L. Böök - 1999 - Synthese 118 (1):13-30.
    Representationalism in cognitive science holds that semantic meaning should be explained by representations in the mind or brain. In this paper it is argued that semantic meaning should instead be explained by an abstract theory of semantic machines -- machines with predicative capability. The concept of a semantic machine (like that of a Turing machine or of Dennett's intentional systems ) is not a physical concept -- although it has physical implementations. The predicative competence of semantic machines is defined in (...)
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  20.  79
    Machine consciousness.Igor L. Aleksander - 2006 - In Steven Laureys (ed.), Boundaries of Consciousness. Elsevier.
  21.  5
    La culture Atlantide.Michaël La Chance - 2003 - [Saint-Laurent, QC]: Fides.
    Notre culture est atlantidienne par deux aspects : elle se veut insulaire, elle voue un culte au spectacle. Atlantide était aux Athéniens ce qu'Hollywood, Disney & Co sont au monde occidental. La crise relève d'une tension entre le spectacle et la vie, nous multiplions les tentatives de camoufler la crise dans un grand discours pseudo-culturel spectaculaire, par une pléthore de " créations " ou d'" événements " superficiels et dérisoires. Pendant des siècles, l'art et la science ont travaillé de concert (...)
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  22.  7
    Selection of relevant features and examples in machine learning.Avrim L. Blum & Pat Langley - 1997 - Artificial Intelligence 97 (1-2):245-271.
  23.  39
    What Sorts of Machines Can Understand the Symbols They Use?Aaron Sloman & L. Jonathan Cohen - 1986 - Aristotelian Society Supplementary Volume 60 (1):61-96.
  24. Susan Blackmore, The Meme Machine.L. Gabora & A. Brown - 1999 - Journal of Consciousness Studies 6 (5):77-85.
  25.  19
    Tools, Machines and Marvels.Stephen R. L. Clark - 1995 - Royal Institute of Philosophy Supplement 38:159-176.
    Technology, according to Derry and Williams's Short History, ‘comprises all that bewilderingly varied body of knowledge and devices by which man progressively masters his natural environment’. Their casual, and unconscious, sexism is not unrelated to my present topic. Women enter the story as spinners, burden bearers and, at long last, typists. ‘The tying of a bundle on the back or the dragging of it along upon the outspread twigs of a convenient branch are contributions [and by implication the only contributions] (...)
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  26.  30
    L'univers est‐il rationnel?L. Rougier - 1955 - Dialectica 9 (3‐4):263-272.
    RésuméLa notion de «rationalité de l'Univers » a varié au cours du temps, le long dialogue de l'esprit et de la nature ayant toujours abouti à ce que Le Roy appelait « l'évolution de l'évidence et la plasticité de la raison ».L'échec de l'explication mécanique de l'Univers a conduit James Jeans à déclarer que le monde ressemble plutôt « à une grande pensée » qu'à une grande machine », car on ne peut en donner qu'une description mathématique. En réalité, la (...)
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  27. Why everything doesn't realize every computation.Ronald L. Chrisley - 1994 - Minds and Machines 4 (4):403-20.
    Some have suggested that there is no fact to the matter as to whether or not a particular physical system relaizes a particular computational description. This suggestion has been taken to imply that computational states are not real, and cannot, for example, provide a foundation for the cognitive sciences. In particular, Putnam has argued that every ordinary open physical system realizes every abstract finite automaton, implying that the fact that a particular computational characterization applies to a physical system does not (...)
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  28. Donald Gillies, Artificial Intelligence and Scientific Method.L. Darden - 2000 - Minds and Machines 10 (2):301-304.
  29.  31
    Why everything doesn't realize every computation.Ronald L. Chrisley - 1994 - Minds and Machines 4 (4):403-420.
    Some have suggested that there is no fact to the matter as to whether or not a particular physical system relaizes a particular computational description. This suggestion has been taken to imply that computational states are not real, and cannot, for example, provide a foundation for the cognitive sciences. In particular, Putnam has argued that every ordinary open physical system realizes every abstract finite automaton, implying that the fact that a particular computational characterization applies to a physical system does not (...)
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  30.  29
    Just a Cog in the Machine? The Individual Responsibility of Researchers in Nanotechnology is a Duty to Collectivize.Shannon L. Spruit, Gordon D. Hoople & David A. Rolfe - 2016 - Science and Engineering Ethics 22 (3):871-887.
    Responsible Research and Innovation provides a framework for judging the ethical qualities of innovation processes, however guidance for researchers on how to implement such practices is limited. Exploring RRI in the context of nanotechnology, this paper examines how the dispersed and interdisciplinary nature of the nanotechnology field somewhat hampers the abilities of individual researchers to control the innovation process. The ad-hoc nature of the field of nanotechnology, with its fluid boundaries and elusive membership, has thus far failed to establish a (...)
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  31.  8
    Behavior and Its Causes: Philosophical Foundations of Operant Psychology.T. L. Smith - 2013 - Springer Verlag.
    This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data-processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will (...)
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  32. Synaptic Perturbation and Consciousness.Stephen L. Thaler - 2014 - International Journal of Machine Consciousness 6 (2):75-107.
    By allowing one artificial neural network to govern the synaptic noise injected into another based upon its appraisal of patterns nucleating from such disturbances, a contemplative form of artifici...
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  33. Machine Intelligence 1.N. L. Collins, D. Michie & E. Dale - 1968 - British Journal for the Philosophy of Science 19 (3):271-274.
  34.  64
    Ontological aspects of information modeling.Robert L. Ashenhurst - 1996 - Minds and Machines 6 (3):287-394.
    Information modeling (also known as conceptual modeling or semantic data modeling) may be characterized as the formulation of a model in which information aspects of objective and subjective reality are presented (the application), independent of datasets and processes by which they may be realized (the system).A methodology for information modeling should incorporate a number of concepts which have appeared in the literature, but should also be formulated in terms of constructs which are understandable to and expressible by the system user (...)
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  35.  18
    Constraints and Preferences in Inductive Learning: An Experimental Study of Human and Machine Performance.Douglas L. Medin, William D. Wattenmaker & Ryszard S. Michalski - 1987 - Cognitive Science 11 (3):299-339.
    The paper examines constraints and preferences employed by people in learning decision rules from preclassified examples. Results from four experiments with human subjects were analyzed and compared with artificial intelligence (AI) inductive learning programs. The results showed the people's rule inductions tended to emphasize category validity (probability of some property, given a category) more than cue validity (probability that an entity is a member of a category given that it has some property) to a greater extent than did the AI (...)
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  36. Visual cognition and cognitive modeling.L. Magnani, S. Civita & G. Previde Massara - 1994 - In V. Cantoni (ed.), Human and Machine Vision: Analogies and Divergences. Plenum Publishers. pp. 229--243.
     
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  37.  35
    Judicial analytics and the great transformation of American Law.Daniel L. Chen - 2019 - Artificial Intelligence and Law 27 (1):15-42.
    Predictive judicial analytics holds the promise of increasing efficiency and fairness of law. Judicial analytics can assess extra-legal factors that influence decisions. Behavioral anomalies in judicial decision-making offer an intuitive understanding of feature relevance, which can then be used for debiasing the law. A conceptual distinction between inter-judge disparities in predictions and inter-judge disparities in prediction accuracy suggests another normatively relevant criterion with regards to fairness. Predictive analytics can also be used in the first step of causal inference, where the (...)
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  38.  73
    From Beast-Machine to Man-Machine: Animal Soul in French Letters from Descartes to La Mettrie. [REVIEW]H. A. L. - 1941 - Journal of Philosophy 38 (10):276-277.
  39.  64
    Cognitive Carpentry: A Blueprint for how to Build a Person.John L. Pollock - 1995 - MIT Press.
    "A sequel to Pollock's How to Build a Person, this volume builds upon that theoretical groundwork for the implementation of rationality through artificial ...
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  40.  12
    Gödels disjunctie.L. Horsten - 1998 - Tijdschrift Voor Filosofie 60 (1):83 - 105.
    In his Gibbs lecture, Gödel argued for the thesis that either the human mind is not a Turing machine, or there exist absolutely undecidable mathematical propositions. He believed that this disjunction can be deduced with mathematical certainty from certain results in mathematical logic. He thought that his disjunctive thesis is of great philosophical importance. First, Gödel's argument for his disjunctive thesis is discussed. It is argued that thisargument contains an ambiguity. But when it is made precise in a certain way, (...)
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  41.  82
    Platonic Dualism.L. P. Gerson - 1986 - The Monist 69 (3):352-369.
    Gilbert Ryle in The Concept of Mind pronounced the “official doctrine” regarding the nature of the mind and the body as “hailing chiefly from Descartes.” That doctrine, anathematized by Ryle as “the dogma of the ghost in the machine,” is said to hold that every human being is composed of a body and a mind, that the body is physical whereas the mind is not, and that the mind may continue to exist when the body is destroyed. Ryle’s famous attack (...)
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  42.  92
    Axioms and tests for the presence of minimal consciousness in agents I: Preamble.Igor L. Aleksander & B. Dunmall - 2003 - Journal of Consciousness Studies 10 (4-5):7-18.
    This paper relates to a formal statement of the mechanisms that are thought minimally necessary to underpin consciousness. This is expressed in the form of axioms. We deem this to be useful if there is ever to be clarity in answering questions about whether this or the other organism is or is not conscious. As usual, axioms are ways of making formal statements of intuitive beliefs and looking, again formally, at the consequences of such beliefs. The use of this style (...)
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  43.  22
    Tools, Machines and Marvels.Stephen R. L. Clark - 1995 - Royal Institute of Philosophy Supplement 38:159-176.
    Technology, according to Derry and Williams's Short History, ‘comprises all that bewilderingly varied body of knowledge and devices by which man progressively masters his natural environment’. Their casual, and unconscious, sexism is not unrelated to my present topic. Women enter the story as spinners, burden bearers and, at long last, typists. ‘The tying of a bundle on the back or the dragging of it along upon the outspread twigs of a convenient branch are contributions [and by implication the only contributions] (...)
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  44. Information, machines, and men.J. L. Massey - 1967 - In Frederick J. Crosson (ed.), Philosophy And Cybernetics. Notre Dame: University of Notre Dame Press. pp. 37--69.
  45.  87
    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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  46.  19
    Consideration and Disclosure of Group Risks in Genomics and Other Data-Centric Research: Does the Common Rule Need Revision?Carolyn Riley Chapman, Gwendolyn P. Quinn, Heini M. Natri, Courtney Berrios, Patrick Dwyer, Kellie Owens, Síofra Heraty & Arthur L. Caplan - forthcoming - American Journal of Bioethics:1-14.
    Harms and risks to groups and third-parties can be significant in the context of research, particularly in data-centric studies involving genomic, artificial intelligence, and/or machine learning technologies. This article explores whether and how United States federal regulations should be adapted to better align with current ethical thinking and protect group interests. Three aspects of the Common Rule deserve attention and reconsideration with respect to group interests: institutional review board (IRB) assessment of the risks/benefits of research; disclosure requirements in the informed (...)
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  47.  47
    Acting, intending, and artificial intelligence.L. Hauser - 1994 - Behavior and Philosophy 22 (1):22-28.
    Hauser considers John Searle's attempt to distinguish acts from movements. On Searle's account, the difference between me raising my arm and my arm's just going up (e.g., if you forcibly raise it), is the causal involvement of my intention to raise my arm in the former, but not the latter, case. Yet, we distinguish a similar difference between a robot's raising its arm and its robot arm just going up (e.g., if you manually raise it). Either robots are rightly credited (...)
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  48.  52
    What Sorts of Machines Can Understand the Symbols They Use?Aaron Sloman & L. Jonathan Cohen - 1986 - Aristotelian Society Supplementary Volume 60 (1):61-96.
  49.  25
    Correlation by calculating machine.C. L. Constance - 1932 - Journal of Experimental Psychology 15 (4):458.
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  50.  37
    A cognitive architecture with incremental levels of machine consciousness inspired by cognitive neuroscience.Klaus Raizer, André L. O. Paraense & Ricardo R. Gudwin - 2012 - International Journal of Machine Consciousness 4 (2):335-352.
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