Search results for 'computing' (try it on Scholar)

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  1. Matti Tedre (2011). Computing as a Science: A Survey of Competing Viewpoints. [REVIEW] Minds and Machines 21 (3):361-387.score: 18.0
    Since the birth of computing as an academic discipline, the disciplinary identity of computing has been debated fiercely. The most heated question has concerned the scientific status of computing. Some consider computing to be a natural science and some consider it to be an experimental science. Others argue that computing is bad science, whereas some say that computing is not a science at all. This survey article presents viewpoints for and against computing as (...)
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  2. Edward J. O'Boyle (2002). An Ethical Decision-Making Process for Computing Professionals. Ethics and Information Technology 4 (4):267-277.score: 18.0
    Our comments focus on the ACMCode of Ethics and situate the Code within ageneral ethical decision-making process tospecify the five steps which logically precedehuman action in ethical matters and determinethat action, and the individual differencetraits in these five steps which bear upon theresolution of an ethical problem and lead tomorally responsible action. Our main purpose isto present a cognitive moral processing modelwhich computing professionals can use to betterunderstand their professional rights andduties. It is clear that the Code providessubstantial guidance (...)
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  3. Soraj Hongladarom (2013). Ubiquitous Computing, Empathy and the Self. AI and Society 28 (2):227-236.score: 18.0
    The paper discusses ubiquitous computing and the conception of the self, especially the question how the self should be understood in the environment pervaded by ubiquitous computing, and how ubiquitous computing makes possible direct empathy where each person or self connected through the network has direct access to others’ thoughts and feelings. Starting from a conception of self, which is essentially distributed, composite and constituted through information, the paper argues that when a number of selves are connected (...)
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  4. Uri Pincas (2011). Program Verification and Functioning of Operative Computing Revisited: How About Mathematics Engineering? [REVIEW] Minds and Machines 21 (2):337-359.score: 18.0
    The issue of proper functioning of operative computing and the utility of program verification, both in general and of specific methods, has been discussed a lot. In many of those discussions, attempts have been made to take mathematics as a model of knowledge and certitude achieving, and accordingly infer about the suitable ways to handle computing. I shortly review three approaches to the subject, and then take a stance by considering social factors which affect the epistemic status of (...)
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  5. Lukáš Sekanina (2007). Evolved Computing Devices and the Implementation Problem. Minds and Machines 17 (3):311-329.score: 18.0
    The evolutionary circuit design is an approach allowing engineers to realize computational devices. The evolved computational devices represent a distinctive class of devices that exhibits a specific combination of properties, not visible and studied in the scope of all computational devices up till now. Devices that belong to this class show the required behavior; however, in general, we do not understand how and why they perform the required computation. The reason is that the evolution can utilize, in addition to the (...)
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  6. James H. Fetzer (2000). Computing is at Best a Special Kind of Thinking. In The Proceedings of the Twentieth World Congress of Philosophy, Volume 9: Philosophy of Mind. Charlottesville: Philosophy Doc Ctr. 103-113.score: 18.0
    When computing is defined as the causal implementation of algorithms and algorithms are defined as effective decision procedures, human thought is mental computation only if it is governed by mental algorithms. An examination of ordinary thinking, however, suggests that most human thought processes are non-algorithmic. Digital machines, moreover, are mark-manipulating or string-processing systems whose marks or strings do not stand for anything for those systems, while minds are semiotic (or “signusing”) systems for which signs stand for other things for (...)
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  7. Robert Rosenberger (2013). The Importance of Generalized Bodily Habits for a Future World of Ubiquitous Computing. AI and Society 28 (3):289-296.score: 18.0
    In a future world of ubiquitous computing, in which humans interact with computerized technologies even more frequently and in even more situations than today, interface design will have increased importance. One feature of interface that I argue will be especially relevant is what I call abstract relational strategies. This refers to an approach (in both a bodily and conceptual sense) toward the use of a technology, an approach that is general enough to be applied in many different concrete scenarios. (...)
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  8. Viola Schiaffonati & Mario Verdicchio (forthcoming). Computing and Experiments. Philosophy and Technology:1-18.score: 18.0
    The question about the scientific nature of computing has been widely debated with no universal consensus reached about its disciplinary status. Positions vary from acknowledging computing as the science of computers to defining it as a synthetic engineering discipline. In this paper, we aim at discussing the nature of computing from a methodological perspective. We consider, in particular, the nature and role of experiments in this field, whether they can be considered close to the traditional experimental scientific (...)
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  9. Chris Boyne (1994). Notes Towards a Definition of Human-Centred Computing. AI and Society 8 (1):60-70.score: 18.0
    Current usage of the expression “human-centred” in computing contexts suffers from a lack of clarity, and involves internal contradictions. It is not enough to base the concept of human-centredness on ideas of social utility, collaborative working or human controllability. However, the concept of human action (which embodies reference to human freedom) provides a theoretical underpinning to human-centredness by combining, from a human standpoint, concern with process and concern with goals. This has consequences for the design process, prompting us to (...)
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  10. Liesbeth De Mol & Giuseppe Primiero (forthcoming). Facing Computing as Technique: Towards a History and Philosophy of Computing. Philosophy and Technology:1-6.score: 18.0
    We present the methodological principles underlying the scientific activities of the DHST Commission on the History and Philosophy of Computing. This volume collects refereed selected papers from the First International Conference organized by the Commission.
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  11. Lauri Forsman (1998). Proactive Management of Distributed Organisational Computing: Prevention Always Pays, Doesn't It? [REVIEW] AI and Society 12 (4):328-345.score: 18.0
    Organisations have eagerly adopted the new opportunities provided by distributed computing technology. These opportunities have also created new dependency on the technology and threats of technical problems. Information technology (IT) management has to choose its position towards these new technical risks. Should the problems be prevented proactively in advance or settled reactively afterwards?This paper draws conclusions from an action research case study aimed at proactive versus reactive end-user support. Between 1994 and 1997 one of the business units in Nokia (...)
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  12. Peter Ford Dominey (2013). Recurrent Temporal Networks and Language Acquisition—From Corticostriatal Neurophysiology to Reservoir Computing. Frontiers in Psychology 4.score: 18.0
    One of the most paradoxical aspects of human language is that it is so unlike any other form of behavior in the animal world, yet at the same time, it has developed in a species that is not far removed from ancestral species that do not possess language. While aspects of non-human primate and avian interaction clearly constitute communication, this communication appears distinct from the rich, combinatorial and abstract quality of human language. So how does the human primate brain allow (...)
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  13. Joan Truckenbrod (1993). Women and the Social Construction of the Computing Culture: Evolving New Forms of Computing. [REVIEW] AI and Society 7 (4):345-357.score: 18.0
    Women have been excluded from the mainstream development of computer hardware and software. Consequently there is an imbalance in the masculine and feminine characteristics, functioning and applications of computing. A masculine approach is encoded into the technical personality of computing, and in the skills and knowledge necessary to utilise computers. The feminine perspective broadens the scope and objectives of computing. This paper examines the current computing culture, and proposes new models for computing that embrace the (...)
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  14. Rodney Van Meter (forthcoming). Quantum Computing's Classical Problem, Classical Computing's Quantum Problem. Foundations of Physics:1-10.score: 18.0
    Tasked with the challenge to build better and better computers, quantum computing and classical computing face the same conundrum: the success of classical computing systems. Small quantum computing systems have been demonstrated, and intermediate-scale systems are on the horizon, capable of calculating numeric results or simulating physical systems far beyond what humans can do by hand. However, to be commercially viable, they must surpass what our wildly successful, highly advanced classical computers can already do. At the (...)
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  15. Joanna Berzowska (2006). Personal Technologies: Memory and Intimacy Through Physical Computing. [REVIEW] AI and Society 20 (4):446-461.score: 18.0
    In this paper, I present an overview of personal and intimate technologies within a pedagogical context. I describe two courses that I have developed for Computation Arts at Concordia University: “Tangible Media and Physical Computing” and “Second Skin and Soft Wear.” Each course deals with different aspects of physical computing and tangible media in a Fine Arts context. In both courses, I introduce concepts of soft computation and intimate reactive artifacts as artworks. I emphasize the concept of memory (...)
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  16. Chris Hables Gray (1988). The Strategic Computing Program at Four Years: Implications and Intimations. [REVIEW] AI and Society 2 (2):141-149.score: 18.0
    Examining the Strategic Computing Program after four years, in the context of the crucial recognition that it is only a small part of the whole range of military artificial intelligence applications, suggests a number of clear implications and intimations about such crucial questions as: 1) the current roles of industry and the universities in developing high technology war; 2) the effects on political and military policy of high-tech weapons systems; and 3) the importance of advanced military computing to (...)
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  17. Eric Hatleback & Jonathan M. Spring (forthcoming). Exploring a Mechanistic Approach to Experimentation in Computing. Philosophy and Technology:1-19.score: 18.0
    The mechanistic approach in philosophy of science contributes to our understanding of experimental design. Applying the mechanistic approach to experimentation in computing is beneficial for two reasons. It connects the methodology of experimentation in computing with the methodology of experimentation in established sciences, thereby strengthening the scientific reputability of computing and the quality of experimental design therein. Furthermore, it pinpoints the idiosyncrasies of experimentation in computing: computing deals closely with both natural and engineered mechanisms. Better (...)
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  18. Geoffrey K. Pullum (1987). Natural Language Interfaces and Strategic Computing. AI and Society 1 (1):47-58.score: 18.0
    Modern weaponry is often too complex for unaided human operation, and is largely or totally controlled by computers. But modern software, particularly artificial intelligence software, exhibits such complexity and inscrutability that there are grave dangers associated with its use in non-benign applications. Recent efforts to make computer systems more accessible to military personnel through natural language processing systems, as proposed in the Strategic Computing Initiative of the Defense Advanced Research Projects Agency, increases rather than decreases the dangers of unpredictable (...)
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  19. Jacqueline G. Ord (1995). The Ethics of NHS Computing: A Terminal Case. [REVIEW] AI and Society 9 (1):80-90.score: 16.0
    Value in the British National Health Service have shifted away from patient care towards financial control. However, in the quest for efficiency , huge amounts of NHS money have been wasted on computer system which failed. In this paper, I draw on a case study to explore some of the ethical issues which underlie this kind of waste of resources. Issues include the gap between public pronouncements and personal experience, the chaos of which lies behind the facade of rationality, and (...)
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  20. Włodzisław Duch (2005). Brain-Inspired Conscious Computing Architecture. Journal of Mind and Behavior 26 (1-2):1-21.score: 15.0
    What type of artificial systems will claim to be conscious and will claim to experience qualia? The ability to comment upon physical states of a brain-like dynamical system coupled with its environment seems to be sufficient to make claims. The flow of internal states in such system, guided and limited by associative memory, is similar to the stream of consciousness. Minimal requirements for an artificial system that will claim to be conscious were given in form of specific architecture named articon. (...)
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  21. J. D. Weinland & W. S. Schlauch (1937). An Examination of the Computing Ability of Mr. Salo Finkelstein. Journal of Experimental Psychology 21 (4):382.score: 15.0
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  22. Anand Ranganathan & Roy H. Campbell (2007). What is the Complexity of a Distributed Computing System? Complexity 12 (6):37-45.score: 15.0
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  23. Jenifer S. Winter (2008). Emerging Policy Problems Related to Ubiquitous Computing: Negotiating Stakeholders' Visions of the Future. Knowledge, Technology and Policy 21 (4):191-203.score: 15.0
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  24. Gordana Dodig-Crncovic & Raffaela Giovagnoli (2013). Computing Nature. Springer.score: 14.0
    The articles in this volume present a selection of works from the Symposium on Natu-ral/Unconventional Computing at AISB/IACAP (British Society for the Study of Artificial Intelligence and the Simulation of Behaviour and The International Association for Computing and Philosophy) World Congress 2012, held at the University of Birmingham, celebrating Turing centenary. This book is about nature considered as the totality of physical existence, the universe. By physical we mean all phenomena - objects and processes - that are possible (...)
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  25. Hava T. Siegelmann (2003). Neural and Super-Turing Computing. Minds and Machines 13 (1):103-114.score: 14.0
    ``Neural computing'' is a research field based on perceiving the human brain as an information system. This system reads its input continuously via the different senses, encodes data into various biophysical variables such as membrane potentials or neural firing rates, stores information using different kinds of memories (e.g., short-term memory, long-term memory, associative memory), performs some operations called ``computation'', and outputs onto various channels, including motor control commands, decisions, thoughts, and feelings. We show a natural model of neural (...) that gives rise to hyper-computation. Rigorous mathematical analysis is applied, explicating our model's exact computational power and how it changes with the change of parameters. Our analog neural network allows for supra-Turing power while keeping track of computational constraints, and thus embeds a possible answer to the superiority of the biological intelligence within the framework of classical computer science. We further propose it as standard in the field of analog computation, functioning in a role similar to that of the universal Turing machine in digital computation. In particular an analog of the Church-Turing thesis of digital computation is stated where the neural network takes place of the Turing machine. (shrink)
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  26. Jon Cogburn & Mark Silcox (2005). Computing Machinery and Emergence: The Aesthetics and Metaphysics of Video Games. Minds and Machines 15 (1):73-89.score: 14.0
    We build on some of Daniel Dennett’s ideas about predictive indispensability to characterize properties of video games discernable by people as computationally emergent if, and only if: (1) they can be instantiated by a computing machine, and (2) there is no algorithm for detecting instantiations of them. We then use this conception of emergence to provide support to the aesthetic ideas of Stanley Fish and to illuminate some aspects of the Chomskyan program in cognitive science.
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  27. James H. Fetzer (1997). Thinking and Computing: Computers as Special Kinds of Signs. [REVIEW] Minds and Machines 7 (3):345-364.score: 14.0
    Cognitive science has been dominated by the computational conception that cognition is computation across representations. To the extent to which cognition as computation across representations is supposed to be a purposive, meaningful, algorithmic, problem-solving activity, however, computers appear to be incapable of cognition. They are devices that can facilitate computations on the basis of semantic grounding relations as special kinds of signs. Even their algorithmic, problem-solving character arises from their interpretation by human users. Strictly speaking, computers as such — apart (...)
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  28. Luciano Floridi (1999). Philosophy and Computing: An Introduction. Routledge.score: 14.0
    This accessible book explores the development, history and future of Information and Communication Technology using examples from philosophy. Luciano Floridi offers both an introduction to these technologies and a philosophical analysis of the problems they pose. The book examines a wide range of areas of technology, including the digital revolution, the Web and Internet, Artificial Intelligence and CD-ROMS. We see how the relationship between philosophy and computing provokes many crucial philosophical questions. Ultimately, Philosophy and Computing outlines what the (...)
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  29. Dina Goldin & Peter Wegner (2008). The Interactive Nature of Computing: Refuting the Strong Church–Turing Thesis. [REVIEW] Minds and Machines 18 (1):17-38.score: 14.0
    The classical view of computing positions computation as a closed-box transformation of inputs (rational numbers or finite strings) to outputs. According to the interactive view of computing, computation is an ongoing interactive process rather than a function-based transformation of an input to an output. Specifically, communication with the outside world happens during the computation, not before or after it. This approach radically changes our understanding of what is computation and how it is modeled. The acceptance of interaction as (...)
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  30. James A. Stieb (2008). A Critique of Positive Responsibility in Computing. Science and Engineering Ethics 14 (2):219-233.score: 14.0
    It has been claimed that (1) computer professionals should be held responsible for an undisclosed list of “undesirable events” associated with their work and (2) most if not all computer disasters can be avoided by truly understanding responsibility. Programmers, software developers, and other computer professionals should be defended against such vague, counterproductive, and impossible ideals because these imply the mandatory satisfaction of social needs and the equation of ethics with a kind of altruism. The concept of social needs is debatable (...)
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  31. Bruno J. Strasser (2010). Collecting, Comparing, and Computing Sequences: The Making of Margaret O. Dayhoff's "Atlas of Protein Sequence and Structure", 1954–1965. [REVIEW] Journal of the History of Biology 43 (4):623 - 660.score: 14.0
    Collecting, comparing, and computing molecular sequences are among the most prevalent practices in contemporary biological research. They represent a specific way of producing knowledge. This paper explores the historical development of these practices, focusing on the work of Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley, who produced the first computer-based collection of protein sequences, published in book format in 1965 as the Atlas of Protein Sequence and Structure. While these practices are generally associated with the rise (...)
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  32. Federico Gobbo & Marco Benini (forthcoming). The Minimal Levels of Abstraction in the History of Modern Computing. Philosophy and Technology:1-17.score: 14.0
    From the advent of general purpose, Turing-complete machines, the relation between operators, programmers and users with computers can be observed as interconnected informational organisms (inforgs), henceforth analysed with the method of levels of abstraction (LoAs), risen within the philosophy of information (PI). In this paper, the epistemological levellism proposed by L. Floridi in the PI to deal with LoAs will be formalised in constructive terms using category theory, so that information itself is treated as structure-preserving functions instead of Cartesian products. (...)
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  33. Eva Turner (2001). The Case for Responsibility of the IT Industry to Promote Equality for Women in Computing. Science and Engineering Ethics 7 (2):247-260.score: 14.0
    This paper investigates the relationship between the role that information technology (IT) has played in the development of women’s employment, the possibility of women having a significant influence on the technology’s development, and the way that the IT industry perceives women as computer scientists, users and consumers. The industry’s perception of women and men is investigated through the portrayal of them in computing advertisements. While women are increasingly updating their technological skills and know-how, and through this process are entering (...)
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  34. Gordana Dodig Crnkovic & Mark Burgin (eds.) (forthcoming). INFORMATION AND COMPUTATION. World Scientific.score: 12.0
    The book focuses on relations between information and computation. Information is a basic structure of the world, while computation is a process of the dynamic change of information. In order for anything to exist for an individual, the individual must get information on it, either by means of perception or by re-organization of the existing information into new patterns and networks in the brain. With the advent of World Wide Web and a prospect of semantic web, the ways of information (...)
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  35. Katarina Britz & Chris Brink (1995). Computing Verisimilitude. Notre Dame Journal of Formal Logic 36 (1):30-43.score: 12.0
    This paper continues the power ordering approach to verisimilitude. We define a parameterized verisimilar ordering of theories in the finite propositional case, both semantically and syntactically. The syntactic definition leads to an algorithm for computing verisimilitude. Since the power ordering approach to verisimilitude can be translated into a standard notion of belief revision, the algorithm thereby also allows the computation of membership of a belief-revised theory.
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  36. Gordana Dodig-Crnkovic, Semantics of Information as Interactive Computation. Proceedings of the Fifth International Workshop on Philosophy and Informatics 2008.score: 12.0
    Computers today are not only the calculation tools - they are directly (inter)acting in the physical world which itself may be conceived of as the universal computer (Zuse, Fredkin, Wolfram, Chaitin, Lloyd). In expanding its domains from abstract logical symbol manipulation to physical embedded and networked devices, computing goes beyond Church-Turing limit (Copeland, Siegelman, Burgin, Schachter). Computational processes are distributed, reactive, interactive, agent-based and concurrent. The main criterion of success of computation is not its termination, but the adequacy of (...)
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  37. Zenon W. Pylyshyn (1989). Computing and Cognitive Science. In Michael I. Posner (ed.), Foundations of Cognitive Science. MIT Press.score: 12.0
    influence. One of the principal characteristics that distinguishes Cognitive Science from more traditional studies of cognition within Psychology, is the extent to which it has been influenced by both the ideas and the techniques of computing. It may come as a surprise to the outsider, then, to discover that there is no unanimity within the discipline on either (a) the nature (and in some cases the desireabilty) of the influence and (b) what computing is –- or at least (...)
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  38. Andrew Pickering (2009). Beyond Design: Cybernetics, Biological Computers and Hylozoism. Synthese 168 (3):469 - 491.score: 12.0
    The history of British cybernetics offers us a different form of science and engineering, one that does not seek to dominate nature through knowledge. I want to say that one can distinguish two different paradigms in the history of science and technology: the one that Heidegger despised, which we could call the Modern paradigm, and another, cybernetic, nonModern, paradigm that he might have approved of. This essay focusses on work in the 1950s and early 1960s by two of Britain’s leading (...)
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  39. Gualtiero Piccinini (2007). Computing Mechanisms. Philosophy of Science 74 (4):501-526.score: 12.0
    This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism is a mechanism whose function is to generate output strings from input strings and (possibly) internal states, in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of (...), namely, doing justice to the practices of computer scientists and computability theorists. It is also an application of recent literature on mechanisms, because it assimilates computational explanation to mechanistic explanation. The account can be used to individuate computing mechanisms and the functions they compute and to taxonomize computing mechanisms based on their computing power. (shrink)
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  40. James Moor & Terrell Ward Bynum (eds.) (2002). Cyberphilosophy: The Intersection of Philosophy and Computing. Blackwell Pub..score: 12.0
    This cutting edge volume provides an overview of the dynamic new field of cyberphilosophy – the intersection of philosophy and computing.
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  41. Michael E. Cuffaro (2013). On the Physical Explanation for Quantum Computational Speedup. Dissertation, The University of Western Ontarioscore: 12.0
    The aim of this dissertation is to clarify the debate over the explanation of quantum speedup and to submit, for the reader's consideration, a tentative resolution to it. In particular, I argue, in this dissertation, that the physical explanation for quantum speedup is precisely the fact that the phenomenon of quantum entanglement enables a quantum computer to fully exploit the representational capacity of Hilbert space. This is impossible for classical systems, joint states of which must always be representable as product (...)
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  42. Vincent C. Müller (2009). Symbol Grounding in Computational Systems: A Paradox of Intentions. [REVIEW] Minds and Machines 19 (4):529-541.score: 12.0
    The paper presents a paradoxical feature of computational systems that suggests that computationalism cannot explain symbol grounding. If the mind is a digital computer, as computationalism claims, then it can be computing either over meaningful symbols or over meaningless symbols. If it is computing over meaningful symbols its functioning presupposes the existence of meaningful symbols in the system, i.e. it implies semantic nativism. If the mind is computing over meaningless symbols, no intentional cognitive processes are available prior (...)
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  43. Gordana Dodig-Crnkovic (2011). Significance of Models of Computation, From Turing Model to Natural Computation. Minds and Machines 21 (2):301-322.score: 12.0
    The increased interactivity and connectivity of computational devices along with the spreading of computational tools and computational thinking across the fields, has changed our understanding of the nature of computing. In the course of this development computing models have been extended from the initial abstract symbol manipulating mechanisms of stand-alone, discrete sequential machines, to the models of natural computing in the physical world, generally concurrent asynchronous processes capable of modelling living systems, their informational structures and dynamics on (...)
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  44. Amit Hagar, Quantum Computing. Stanford Encyclopedia of Philosophy.score: 12.0
    Combining physics, mathematics and computer science, quantum computing has developed in the past two decades from a visionary idea to one of the most fascinating areas of quantum mechanics. The recent excitement in this lively and speculative domain of research was triggered by Peter Shor (1994) who showed how a quantum algorithm could exponentially "speed up" classical computation and factor large numbers into primes much more rapidly (at least in terms of the number of computational steps involved) than any (...)
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  45. Bernard Gert (1999). Common Morality and Computing. Ethics and Information Technology 1 (1):53-60.score: 12.0
    This article shows how common morality can be helpful in clarifying the discussion of ethical issues that arise in computing. Since common morality does not always provide unique answers to moral questions, not all such issues can be resolved, however common morality does provide a clear answer to the question whether one can illegally copy software for a friend.
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  46. Gordana Dodig Crnkovic & Susan Stuart (eds.) (2007). Computation, Information, Cognition: The Nexus and the Liminal. Cambridge Scholars Press.score: 12.0
    Written by world-leading experts, this book draws together a number of important strands in contemporary approaches to the philosophical and scientific questions that emerge when dealing with the issues of computing, information, cognition and the conceptual issues that arise at their intersections. It discovers and develops the connections at the borders and in the interstices of disciplines and debates. This volume presents a range of essays that deal with the currently vigorous concerns of the philosophy of information, ontology creation (...)
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  47. Matthew W. Parker (2009). Computing the Uncomputable; or, the Discrete Charm of Second-Order Simulacra. Synthese 169 (3):447 - 463.score: 12.0
    We examine a case in which non-computable behavior in a model is revealed by computer simulation. This is possible due to differing notions of computability for sets in a continuous space. The argument originally given for the validity of the simulation involves a simpler simulation of the simulation , still further simulations thereof, and a universality conjecture. There are difficulties with that argument, but there are other, heuristic arguments supporting the qualitative results. It is urged, using this example, that absolute (...)
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  48. Gualtiero Piccinini (2004). The Functional Account of Computing Mechanisms. PhilSci Archive.score: 12.0
    This paper offers an account of what it is for a physical system to be a computing mechanism—a mechanism that performs computations. A computing mechanism is any mechanism whose functional analysis ascribes it the function of generating outputs strings from input strings in accordance with a general rule that applies to all strings. This account is motivated by reasons that are endogenous to the philosophy of computing, but it may also be seen as an application of recent (...)
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  49. Michael E. Gorman (2008). Trading Zones, Moral Imagination and Socially Sensitive Computing. Foundations of Science 13 (1):89-97.score: 12.0
    As computating technologies become ubiquitous and at least partly autonomous, they will have increasing impact on societies, both in the developed and developing worlds. This article outlines a framework for guiding emerging technologies in directions that promise social as well as technical progress. Multiple stakeholders will have to be engaged in dialogues over new technological directions, forming trading zones in which knowledge and resources are exchanged. Such discussions will have to incorporate cultural and individual values.
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  50. Rodrick Wallace (2006). Pitfalls in Biological Computing: Canonical and Idiosyncratic Dysfunction of Conscious Machines. Mind and Matter 4 (1):91-113.score: 12.0
    The central paradigm of arti?cial intelligence is rapidly shifting toward biological models for both robotic devices and systems performing such critical tasks as network management, vehicle navigation, and process control. Here we use a recent mathematical analysis of the necessary conditions for consciousness in humans to explore likely failure modes inherent to a broad class of biologically inspired computing machines. Analogs to developmental psychopathology, in which regulatory mechanisms for consciousness fail progressively and subtly understress, and toinattentional blindness, where a (...)
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