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Summary Ethical issues associated with AI are proliferating and rising to popular attention as intelligent machines become ubiquitous. For example, AIs can and do model aspects essential to moral agency and so offer tools for the investigation of consciousness and other aspects of cognition contributing to moral status (either ascribed or achieved). This has deep implications for our understanding of moral agency, and so of systems of ethics meant to account for and to provide for the development of such capacities. This raises the issue of responsible and/or blameworthy AIs operating openly in general society, with deep implications again for systems of ethics which must accommodate moral AIs. Consider also that human social infrastructure (e.g. energy grids, mass-transit systems) are increasingly moderated by increasingly intelligent machines. This alone raises many moral/ethical concerns. For example, who or what is responsible in the case of an accident due to system error, or due to design flaws, or due to proper operation outside of anticipated constraints? Finally, as AIs become increasingly intelligent, there seems some legitimate concern over the potential for AIs to manage human systems according to AI values, rather than as directly programmed by human designers. These issues often bare on the long-term safety of intelligent systems, and not only for individual human beings, but for the human race and life on Earth as a whole. These issues and many others are central to Ethics of AI. 
Key works Bostrom manuscriptMüller 2014
Introductions Müller 2013White 2015Gunkel 2012
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  1. Theodore Bach (2011). Structure-Mapping: Directions From Simulation to Theory. Philosophical Psychology 24 (1):23-51.
    The theory of mind debate has reached a “hybrid consensus” concerning the status of theory-theory and simulation-theory. Extant hybrid models either specify co-dependency and implementation relations, or distribute mentalizing tasks according to folk-psychological categories. By relying on a non-developmental framework these models fail to capture the central connection between simulation and theory. I propose a “dynamic” hybrid that is informed by recent work on the nature of similarity cognition. I claim that Gentner’s model of structure-mapping allows us to understand simulation (...)
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  2. Luca Barlassina (2013). Simulation is Not Enough: A Hybrid Model of Disgust Attribution on the Basis of Visual Stimuli. Philosophical Psychology 26 (3):401-419.
    Mindreading is the ability to attribute mental states to other individuals. According to the Theory-Theory (TT), mindreading is based on one's possession of a Theory of Mind. On the other hand, the Simulation Theory (ST) maintains that one arrives at the attribution of a mental state by simulating it in one's own mind. In this paper, I propose a ST-TT hybrid model of the ability to attribute disgust on the basis of visual stimuli such as facial expressions, body postures, etc. (...)
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  3. Archana Barua & Ananya Barua (2012). Gendering the Digital Body: Women and Computers. [REVIEW] AI and Society 27 (4):465-477.
    As we live in a culture where “everything can be commodified, measured and calculated and can be put in the competitive market for sale, detached from its roots and purpose,” there is need to redefine our humanness in terms of the changing nature of science, technology, and their deeper impact on human life. More than anything else, it is Information Technology that now has tremendous influence on all spheres of our life, and in a sense, IT has become the destiny (...)
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  4. Alain Bensoussan & Renaud Champion (2016). Droit de la robotique: Livre blanc. SYMOP.
    Histoire et utilisation du robot Bien que la robotique soit un marché économique relativement jeune et en pleine croissance, la genèse des robots remonte à l’Antiquité. Le premier robot à être déployé sur des lignes d’assemblage est Unimate, utilisé dès 1961 par General Motors. La robotique, en se di usant dans tous les pans de notre économie, va impacter les business modèles de nombreuses industries comme l’automobile et l’aéronautique mais aussi la construction ou l’agriculture. Aujourd’hui les robots industriels et de (...)
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  5. Michael T. Black (1993). Consensus and Authenticity in Representation: Simulation as Participative Theatre. [REVIEW] AI and Society 7 (1):40-51.
    Representation was invented as an issue during the 17th century in response to specific developments in the technology of simulation. It remains an issue of central importance today in the design of information systems and approaches to artificial intelligence. Our cultural legacy of thought about representation is enormous but as inhibiting as it is productive. The challenge to designers of representative technology is to reshape this legacy by enlarging the politics rather than the technics of simulation.
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  6. Russell Blackford & Damien Broderick (eds.) (2014). Intelligence Unbound: The Future of Uploaded and Machine Minds. Wiley-Blackwell.
    _Intelligence Unbound_ explores the prospects, promises, and potential dangers of machine intelligence and uploaded minds in a collection of state-of-the-art essays from internationally recognized philosophers, AI researchers, science fiction authors, and theorists. Compelling and intellectually sophisticated exploration of the latest thinking on Artificial Intelligence and machine minds Features contributions from an international cast of philosophers, Artificial Intelligence researchers, science fiction authors, and more Offers current, diverse perspectives on machine intelligence and uploaded minds, emerging topics of tremendous interest Illuminates the nature (...)
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  7. Nick Bostrom (2005). Transhumanist Values. Journal of Philosophical Research 30 (Supplement):3-14.
    Transhumanism is a loosely defined movement that has developed gradually over the past two decades. [1] It promotes an interdisciplinary approach to understanding and evaluating the opportunities for enhancing the human condition and the human organism opened up by the advancement of technology. Attention is given to both present technologies, like genetic engineering and information technology, and anticipated future ones, such as molecular nanotechnology and artificial intelligence.
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  8. Xindi Cai & I. I. Wunsch (2007). Computer Go: A Grand Challenge to AI. In Wlodzislaw Duch & Jacek Mandziuk (eds.), Challenges for Computational Intelligence. Springer 443--465.
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  9. Mar Cello Guarim (2011). Computational Neural Modeling and the Philosophy of Ethics Reflections on the Particularism-Generalism Debate. In M. Anderson S. Anderson (ed.), Machine Ethics. Cambridge Univ. Press
  10. Christopher A. Chung & Michael Alfred (2009). Design, Development, and Evaluation of an Interactive Simulator for Engineering Ethics Education (Seee). Science and Engineering Ethics 15 (2):189-199.
    Societal pressures, accreditation organizations, and licensing agencies are emphasizing the importance of ethics in the engineering curriculum. Traditionally, this subject has been taught using dogma, heuristics, and case study approaches. Most recently a number of organizations have sought to increase the utility of these approaches by utilizing the Internet. Resources from these organizations include on-line courses and tests, videos, and DVDs. While these individual approaches provide a foundation on which to base engineering ethics, they may be limited in developing a (...)
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  11. Luc Ciompi & Martin Baatz (2008). The Energetic Dimension of Emotions: An Evolution-Based Computer Simulation with General Implications. Biological Theory 3 (1):42-50.
    Viewed from an evolutionary standpoint, emotions can be understood as situation-specific patterns of energy consumption related to behaviors that have been selected by evolution for their survival value, such as environmental exploration, flight or fight, and socialization. In the present article, the energy linked with emotions is investigated by a strictly energy-based simulation of the evolution of simple autonomous agents provided with random cognitive and motor capacities and operating among food and predators. Emotions are translated into evolving patterns of energy (...)
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  12. Andy Clark (1996). Linguistic Anchors in the Sea of Thought? Pragmatics and Cognition 4 (1):93-103.
    Andy Clark is currently Professor of Philosophy and Director of the Philosophy/Neuroscience/Psychology program at Washington University in St. Louis, Missouri. He is the author of two books MICROCOGNITION (MIT Press/Bradford Books 1989) and ASSOCIATIVE ENGINES (MIT Press/Bradford Books, 1993) as well as numerous papers and four edited volumes. He is an ex- committee member of the British Society for the Philosophy of Science and of the Society for Artificial Intelligence and the Simulation of Behavior. Awards include a visiting Fellowship at (...)
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  13. Kenneth M. Colby, Peter M. Colby & Robert J. Stoller (1990). Dialogues in Natural Language with Guru, a Psychologic Inference Engine. Philosophical Psychology 3 (2 & 3):171 – 186.
    The aim of this project was to explore the possibility of constructing a psychologic inference engine that might enhance introspective self-awareness by delivering inferences about a user based on what he said in interactive dialogues about his closest opposite-sex relation. To implement this aim, we developed a computer program (guru) with the capacity to simulate human conversation in colloquial natural language. The psychologic inferences offered represent the authors' simulations of their commonsense psychology responses to expected user-input expressions. The heuristics of (...)
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  14. J. Decety (2002). Neurophysiological Evidence for Simulation and Action. In Jérôme Dokic & Joëlle Proust (eds.), Simulation and Knowledge of Action. John Benjamins
  15. Aaron Dewitt (2012). Group Agency and Epistemic Dependency. Episteme 9 (3):235-244.
    Modern epistemic questions have largely been focused around the individual and her ability to acquire knowledge autonomously. More recently epistemologists have begun to look more broadly in providing accounts of knowledge by considering its social context, where the individual depends on others for true beliefs. Hardwig explains the effect of this shift starkly, arguing that to reject epistemic dependency is to deny certain true beliefs widely held throughout society and, more specifically, it is to deny that science and scholarship can (...)
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  16. Jérôme Dokic (2002). Reply to 'the Scope and Limit of Mental Simulation'. In Jérôme Dokic & Joëlle Proust (eds.), Simulation and Knowledge of Action. John Benjamins
  17. Jérôme Dokic & Joëlle Proust (eds.) (2002). Simulation and Knowledge of Action. John Benjamins.
    CHAPTER Simulation theory and mental concepts Alvin I. Goldman Rutgers University. Folk psychology and the TT-ST debate The study of folk psychology, ...
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  18. Hubert Dreyfus, Heidegger and Foucault on the Subject, Agencycourses.
    of autonomous agency. Yet neither denies the importance of human freedom. In Heidegger's early work the subject is reinterpreted as Dasein -- a non autonomous, culturally bound (or thrown) way of being, that can yet change the field of possibilities in which it acts. In middle Heidegger, thinkers alone have the power to disclose a new world, while in later Heidegger, anyone is free to step back from the current world, to enter one of a plurality of worlds, and, thereby, (...)
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  19. Fady Farah & François Rousselot (2007). DARES: Documents Annotation and Recombining System—Application to the European Law. [REVIEW] Artificial Intelligence and Law 15 (2):83-102.
    Accessing legislation via the Internet is more and more frequent. As a result, systems that allow consultation of law texts are becoming more and more powerful. This paper presents DARES, a generic system which can be adapted to any domain to handle documents production needs. It is based on an annotation engine which allows obtaining XML documents inputs as required by the system, and on an XML fragments recombining system. The latter operates using a fragment manipulation functions toolbox to generate (...)
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  20. Andreas Fischer, Assessment of Problem Solving Skills by Means of Multiple Complex Systems – Validity of Finite Automata and Linear Dynamic Systems.
    The assessment of highly domain-general problem solving skills is increasingly important as problem solving is increasingly demanded by modern workplaces and increasingly present in international large-scale assessments such as the Programme for International Student Assessment. This thesis is about the computer-based assessment of problem solving skills based on Multiple Complex Systems : The main idea of the MCS approach is to present multiple computer-simulations of “minimally complex” problems in order to reliably assess certain problem solving skills. In each simulation, the (...)
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  21. Justin C. Fisher (2006). Does Simulation Theory Really Involve Simulation? Philosophical Psychology 19 (4):417 – 432.
    This paper contributes to an ongoing debate regarding the cognitive processes involved when one person predicts a target person's behavior and/or attributes a mental state to that target person. According to simulation theory, a person typically performs these tasks by employing some part of her brain as a simulation of what is going on in a corresponding part of the brain of the target person. I propose a general intuitive analysis of what 'simulation' means. Simulation is a particular way of (...)
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  22. Luciano Floridi (2004). Open Problems in the Philosophy of Information. Metaphilosophy 35 (4):554-582.
    The philosophy of information (PI) is a new area of research with its own field of investigation and methodology. This article, based on the Herbert A. Simon Lecture of Computing and Philosophy I gave at Carnegie Mellon University in 2001, analyses the eighteen principal open problems in PI. Section 1 introduces the analysis by outlining Herbert Simon's approach to PI. Section 2 discusses some methodological considerations about what counts as a good philosophical problem. The discussion centers on Hilbert's famous analysis (...)
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  23. Tom Froese (2007). On the Role of AI in the Ongoing Paradigm Shift Within the Cognitive Sciences. In M. Lungarella (ed.), 50 Years of AI. Springer-Verlag
    This paper supports the view that the ongoing shift from orthodox to embodied-embedded cognitive science has been significantly influenced by the experimental results generated by AI research. Recently, there has also been a noticeable shift toward enactivism, a paradigm which radicalizes the embodied-embedded approach by placing autonomous agency and lived subjectivity at the heart of cognitive science. Some first steps toward a clarification of the relationship of AI to this further shift are outlined. It is concluded that the success of (...)
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  24. Liane Gabora (2002). Amplifying Phenomenal Information: Toward a Fundamental Theory of Consciousness. Journal of Consciousness Studies 9 (8):3-29.
    from non-conscious components by positing that consciousness is a universal primitive. For example, the double aspect theory of information holds that infor- mation has a phenomenal aspect. How then do you get from phenomenal infor- mation to human consciousness? This paper proposes that an entity is conscious to the extent it amplifies information, first by trapping and integrating it through closure, and second by maintaining dynamics at the edge of chaos through simul- taneous processes of divergence and convergence. The origin (...)
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  25. Ismo Kantola (2013). On the Re-Materialization of the Virtual. AI and Society 28 (2):189-198.
    The so-called new economy based on the global network of digitalized communication was welcomed as a platform of innovations and as a vehicle of advancement of democracy. The concept of virtuality captures the essence of the new economy: efficiency and free access. In practice, the new economy has developed into an heterogenic entity dominated by practices such as propagation of trust and commitment to standards and standard-like technological solutions; entrenchment of locally strategic subsystems; surveillance of unwanted behavior. Five empirical cases (...)
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  26. Gerben Meynen (2011). Generalized Anxiety Disorder and Online Intelligence: A Phenomenological Account of Why Worrying is Unhelpful. Philosophy, Ethics, and Humanities in Medicine 6 (1):7-.
    Worrying is the central feature of generalized anxiety disorder . Many people worry from time to time, but in GAD the worrying is prolonged and difficult to control. Worrying is a specific way of coping with perceived threats and feared situations. Meanwhile, it is not considered to be a helpful coping strategy, and the phenomenological account developed in this paper aims to show why. It builds on several phenomenological notions and in particular on Michael Wheeler's application of these notions to (...)
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  27. Greg Michaelson & Ruth Aylett (2011). Special Issue on Social Impact of AI: Killer Robots or Friendly Fridges. [REVIEW] AI and Society 26 (4):317-318.
  28. Donald Michie (1995). Consciousness as an Engineering Issue, Part. Journal of Consciousness Studies 2 (1):52-66.
    Consciousness has been widely regarded as the central arena for the mental solution of problems. A variant view locates the business end of problem solving elsewhere, with conscious intervention only for intermittent monitoring and goal-setting. In this scenario conscious awareness, with `intelligent' processes generally, is largely specialized to the construction and communication of appropriate after-the-event histories and explanations.The first part of the paper traces a long march undertaken by main-stream artificial intelligence basing itself on the first assumption. Disappointment with the (...)
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  29. Donald Michie (1994). Consciousness as an Engineering Issue (Parts 1 and 2). Journal of Consciousness Studies 1 (1):192-95.
    Consciousness has been widely regarded as the central arena for the mental solution of problems. A variant view locates the business end of problem solving elsewhere, with conscious intervention only for intermittent monitoring and goal-setting. In this scenario conscious awareness, with `intelligent' processes generally, is largely specialized to the construction and communication of appropriate after-the-event histories and explanations.The first part of the paper traces a long march undertaken by main-stream artificial intelligence basing itself on the first assumption. Disappointment with the (...)
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  30. Paolo Milazzo (2014). Membrane Computing: From Biology to Computation and Back. Isonomia: Online Philosophical Journal of the University of Urbino:1-15.
    Natural Computing is a field of research in Computer Science aimed at reinterpreting biological phenomena as computing mechanisms. This allows unconventional computing architectures to be proposed in which computations are performed by atoms, DNA strands, cells, insects or other biological elements. Membrane Computing is a branch of Natural Computing in which biological phenomena of interest are related with interactions between molecules inside cells. The research in Membrane Computing has lead to very important theoretical results that show how, in principle, cells (...)
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  31. Jason Millar, Technological Moral Proxies and the Ethical Limits of Automating Decision-Making In Robotics and Artificial Intelligence.
    Humans have been automating increasingly sophisticated behaviours for some time now. We have machines that lift and move things, that perform complex calculations, and even machines that build other machines. More recently, technological advances have allowed us to automate increasingly sophisticated decision-making processes. We have machines that decide when and how to use lethal force, when and how to perform life-saving medical interventions, and when and how to maneuver cars in chaotic traffic. Clearly, some automated decision-making processes have serious ethical (...)
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  32. Benjamin Mitchell-Yellin (2014). In Defense of the Platonic Model: A Reply to Buss. Ethics 124 (2):342-357.
    Sarah Buss has recently argued that endorsement theories of autonomy face three problems: they conflate autonomous agency with agency simpliciter, they face a vicious regress, and they get the extension of autonomous actions wrong. I argue that one such theory, Gary Watson’s Platonic Model, is not subject to any of these problems. I conclude that Buss has not given us reason to reject the Platonic Model and that it may be compatible with her own theory of accountability.
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  33. Laurens Mommers, Wim Voermans, Wouter Koelewijn & Hugo Kielman (2009). Understanding the Law: Improving Legal Knowledge Dissemination by Translating the Contents of Formal Sources of Law. [REVIEW] Artificial Intelligence and Law 17 (1):51-78.
    Considerable attention has been given to the accessibility of legal documents, such as legislation and case law, both in legal information retrieval (query formulation, search algorithms), in legal information dissemination practice (numerous examples of on-line access to formal sources of law), and in legal knowledge-based systems (by translating the contents of those documents to ready-to-use rule and case-based systems). However, within AI & law, it has hardly ever been tried to make the contents of sources of law, and the relations (...)
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  34. Hans Moravec, Bodies, Robots, Minds.
    Serious attempts to build thinking machines began after the second world war. One line of research, called Cybernetics, used electronic circuitry imitating nervous systems to make machines that learned to recognize simple patterns, and turtle-like robots that found their way to recharging plugs. A different approach, named Artificial Intelligence, harnessed the arithmetic power of post-war computers to abstract reasoning, and by the 1960s made computers prove theorems in logic and geometry, solve calculus problems and play good games of checkers. At (...)
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  35. Alvaro Moreno, Alife Models as Epistemic Artefacts.
    Both the irreducible complexity of biological phenomena and the aim of a universalized biology (life-as-it-could-be) have lead to a deep methodological shift in the study of life; represented by the appearance of ALife, with its claim that computational modelling is the main tool for studying the general principles of biological phenomenology. However this methodological shift implies important questions concerning the aesthetic, engineering and specially the epistemological status of computational models in scientific research: halfway between the well established categories of theory (...)
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  36. Hiroaki Morio & Christopher Buchholz (2009). How Anonymous Are You Online? Examining Online Social Behaviors From a Cross-Cultural Perspective. AI and Society 23 (2):297-307.
    Communication on the Internet is often described as “anonymous”, yet the usage of the term is often confusing, even in academia. Three levels of anonymity, visual anonymity, dissociation of real and online identities, and lack of identifiability, are thought to have different effects on various components of interpersonal motivation. Specifically, we propose that cross-cultural differences in interpersonal motivation (autonomy vs. affiliation) are illustrated by choices individuals make when deciding whether or not to remain anonymous while communicating online. Autonomy is often (...)
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  37. Margaret Morrison (2009). Models, Measurement and Computer Simulation: The Changing Face of Experimentation. Philosophical Studies 143 (1):33-57.
    The paper presents an argument for treating certain types of computer simulation as having the same epistemic status as experimental measurement. While this may seem a rather counterintuitive view it becomes less so when one looks carefully at the role that models play in experimental activity, particularly measurement. I begin by discussing how models function as “measuring instruments” and go on to examine the ways in which simulation can be said to constitute an experimental activity. By focussing on the connections (...)
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  38. Abbe Mowshowitz (2008). Technology as Excuse for Questionable Ethics. AI and Society 22 (3):271-282.
    By endowing technology with the attributes of autonomous agency, human beings are ethically sidelined. Individuals are relieved of responsibility. The suggestion of being in the grip of irresistible forces provides an excuse for rejecting responsibility for oneself and others, thus creating conditions for inappropriate or antisocial behavior. It also impedes the search for solutions to pressing social problems associated with applications of technology. Failure to assign and accept responsibility for decisions to deploy “conventional” technology will inevitably impede our ability to (...)
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  39. Ryan Muldoon (2007). Robust Simulations. Philosophy of Science 74 (5):873-883.
    As scientists begin to study increasingly complex questions, many have turned to computer simulation to assist in their inquiry. This methodology has been challenged by both analytic modelers and experimentalists. A primary objection of analytic modelers is that simulations are simply too complicated to perform model verification. From the experimentalist perspective it is that there is no means to demonstrate the reality of simulation. The aim of this paper is to consider objections from both of these perspectives, and to argue (...)
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  40. Robert C. Muller (1993). Enhancing Creativity, Innovation and Cooperation. AI and Society 7 (1):4-39.
    The paper explores the creative thinking process and throws light on creativity enhancement. From the perspective of possible creativity enhancement both the characteristics of creativity and the creative thinking process are discussed, together with an analysis of the process and its common factors. Constraints on innovation (as a special type of creativity), innovation management and the acceptance of change are discussed; creativity between cooperating individuals is also examined. Some possible computer-based tools to enhance creativity, including innovation, are discussed. A framework (...)
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  41. Vincent C. Müller (2016). New Developments in the Philosophy of AI. In Fundamental Issues of Artificial Intelligence. Springer
    The philosophy of AI has seen some changes, in particular: 1) AI moves away from cognitive science, and 2) the long term risks of AI now appear to be a worthy concern. In this context, the classical central concerns – such as the relation of cognition and computation, embodiment, intelligence & rationality, and information – will regain urgency.
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  42. Vincent C. Müller (ed.) (2016). Fundamental Issues of Artificial Intelligence. Springer.
    PT-AI 2013: This volume offers a look at the fundamental issues of present and future AI, especially from cognitive science, computer science, neuroscience and philosophy. This work examines the conditions for artificial intelligence, how these relate to the conditions for intelligence in humans and other natural agents, as well as ethical and societal problems that artificial intelligence raises or will raise. The key issues this volume investigates include the relation of AI and cognitive science, ethics of AI and robotics, brain (...)
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  43. Vincent C. Müller (2014). Editorial: Risks of General Artificial Intelligence. Journal of Experimental and Theoretical Artificial Intelligence 26 (3):297-301.
    This is the editorial for a special volume of JETAI, featuring papers by Omohundro, Armstrong/Sotala/O’Heigeartaigh, T Goertzel, Brundage, Yampolskiy, B. Goertzel, Potapov/Rodinov, Kornai and Sandberg. - If the general intelligence of artificial systems were to surpass that of humans significantly, this would constitute a significant risk for humanity – so even if we estimate the probability of this event to be fairly low, it is necessary to think about it now. We need to estimate what progress we can expect, what (...)
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  44. Vincent C. Müller (ed.) (2014). Risks of Artificial General Intelligence. Taylor & Francis (JETAI).
    Special Issue “Risks of artificial general intelligence”, Journal of Experimental and Theoretical Artificial Intelligence, 26/3 (2014), ed. Vincent C. Müller. http://www.tandfonline.com/toc/teta20/26/3# - Risks of general artificial intelligence, Vincent C. Müller, pages 297-301 - Autonomous technology and the greater human good - Steve Omohundro - pages 303-315 - - - The errors, insights and lessons of famous AI predictions – and what they mean for the future - Stuart Armstrong, Kaj Sotala & Seán S. Ó hÉigeartaigh - pages 317-342 - - (...)
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  45. Vincent C. Müller (ed.) (2013). Philosophy and Theory of Artificial Intelligence. Springer.
    Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set (...)
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  46. Vincent C. Müller (2009). Would You Mind Being Watched by Machines? Privacy Concerns in Data Mining. AI and Society 23 (4):529-544.
    "Data mining is not an invasion of privacy because access to data is only by machines, not by people": this is the argument that is investigated here. The current importance of this problem is developed in a case study of data mining in the USA for counterterrorism and other surveillance purposes. After a clarification of the relevant nature of privacy, it is argued that access by machines cannot warrant the access to further information, since the analysis will have to be (...)
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  47. Vincent C. Müller (2006). Πενήντα χρόνια τεχνητής νοημοσύνης: γιατί δεν επιτύχαμε ακόμα; [Fifty years of artificial intelligence: Why have we not succeeded yet?]. Cogito 4:48-49.
    1 Οι Αρχές - 2 Η δοκιμασία του Turing - 3 Η κλασική τεχνητή νοημοσύνη - 4 Η τεχνητή νοημοσύνη σήμερα - 5 Η τεχνητή νοημοσύνη του μέλλοντος - Με τις τεχνολογίες του παρόντος μάλλον θα δυσκολευτούμε να φτάσουμε στην κατασκευή μηχανών με τεχνητή νοημοσύνη. Κατά την γνώμη μου, θα δούμε άλλες τεχνικές λύσεις με την κλασική τεχνητή νοημοσύνη και μέθοδο «από κάτω προς τα πάνω», αλλά δεν περιμένω να υπάρξει ριζοσπαστική πρόοδος πριν μάθουμε πολλά παραπάνω για τον εγκέφαλό μας. (...)
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  48. Vincent C. Müller (2004). “Der Mann mit Eigenschaften”, review of Joseph LeDoux: Im Netz der Persönlichkeit: Wie unser Selbst entsteht [Synaptic Self],. [REVIEW] Süddeutsche Zeitung 2014 (14.01.2004):14.
    Review of Joseph LeDoux: Das Netz der Persönlichkeit. Wie unser Selbst entsteht. Walter Verlag, Düsseldorf 2003. 510 Seiten (mit Abbildungen), 39,90 Euro. - Der eine Mensch ist mißtrauisch, der nächste leichtgläubig, diese ist warmherzig, jene kaltschnäuzig. Viele haben Charakter, manche sogar Persönlichkeit. Wie kommt es dazu? In seinem neuen Buch untersucht der Neurowissenschaftler Joseph LeDoux wie unser Selbst entsteht. In dem sehr lesbaren und angenehm übersetzten Werk wird anschaulich und detailliert berichtet, wie sich in unserem Gehirn die Charakteristika eines Individuums (...)
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  49. Vincent C. Müller & Nick Bostrom (2016). Future Progress in Artificial Intelligence: A Survey of Expert Opinion. In Fundamental Issues of Artificial Intelligence. Springer 553-571.
    There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. We thus (...)
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  50. Vincent C. Müller & Nick Bostrom (2014). Future Progress in Artificial Intelligence: A Poll Among Experts. AI Matters 1 (1):9-11.
    [This is the short version of: Müller, Vincent C. and Bostrom, Nick (forthcoming 2016), ‘Future progress in artificial intelligence: A survey of expert opinion’, in Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library 377; Berlin: Springer).] - - - In some quarters, there is intense concern about high–level machine intelligence and superintelligent AI coming up in a few dec- ades, bringing with it significant risks for human- ity; in other quarters, these issues are ignored or considered science (...)
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