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Summary The Ethics of Artificial Intelligence is concerned with the moral-ethical implications of intelligent machines.1) As tools for the investigation of consciousness and other aspects of cognition contributing to moral status (either ascribed or achieved), some artificial intelligences (AIs) will both model aspects essential to moral agency as well as embody those aspects. This has deep implications for our understanding of moral agency, and so of systems of ethics in so far as these systems accord with experimental results. Moreover, this raises the issue of responsible and/or blameworthy AIs operating openly in general society. This has deep implications again for systems of ethics which must accommodate moral AIs. 2) As human social infrastructure (e.g. energy grids, mass-transit systems) are increasingly controlled by increasingly intelligent machines, dependence on AIs raises many moral ethical concerns. For example, who or what is responsible in the case of an accident due to system error? Moreover, 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 for example. These issues are also central to Ethics of AI. There are many other ethical issues associated with AI, too many to list here this list is expanding rapidly.Thus, it is an exciting subfield of moral theory and applied ethics with many controversial topics that are at the same time important in determining the shape of our collective technologically dependent future.
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  1. Seiya Abiko (1999). Lessons From Nursing Theories: Toward the Humanisation of Technology. [REVIEW] AI and Society 13 (1-2):164-175.
    The current viewpoint on technology seems to derive from the optimistic idea of the existence of pre-established harmony that any technological progress leads to people's health, and welfare. But history has shown us that this is not always the case, and that we must select the proper direction which leads to health and welfare. For that purpose, this article presents the viewpoint of technology as a kind of human care service, along with the lessons from nursing theories. Five leading nursing (...)
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  2. Jerold J. Abrams (2004). Pragmatism, Artificial Intelligence, and Posthuman Bioethics: Shusterman, Rorty, Foucault. [REVIEW] Human Studies 27 (3):241-258.
    Michel Foucault's early works criticize the development of modern democratic institutions as creating a surveillance society, which functions to control bodies by making them feel watched and monitored full time. His later works attempt to recover private space by exploring subversive techniques of the body and language. Following Foucault, pragmatists like Richard Shusterman and Richard Rorty have also developed very rich approaches to this project, extending it deeper into the literary and somatic dimensions of self-stylizing. Yet, for a debate centered (...)
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  3. Alison Adam (2008). Ethics for Things. Ethics and Information Technology 10 (2-3):149-154.
    This paper considers the ways that Information Ethics (IE) treats things. A number of critics have focused on IE’s move away from anthropocentrism to include non-humans on an equal basis in moral thinking. I enlist Actor Network Theory, Dennett’s views on ‹as if’ intentionality and Magnani’s characterization of ‹moral mediators’. Although they demonstrate different philosophical pedigrees, I argue that these three theories can be pressed into service in defence of IE’s treatment of things. Indeed the support they lend to the (...)
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  4. John Altmann, Artificial Brains & Holographic Bodies: Facing the Questions of Progress.
    This essay discusses the ambitious plans of one Dmitry Itskov who by 2045 wishes to see immortality achieved by way of Artificial Brains and Holographic Bodies. I discuss the ethical implications of such a possibility coming to pass.
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  5. Michael Anderson & Susan Leigh Anderson (2007). The Status of Machine Ethics: A Report From the AAAI Symposium. [REVIEW] Minds and Machines 17 (1):1-10.
    This paper is a summary and evaluation of work presented at the AAAI 2005 Fall Symposium on Machine Ethics that brought together participants from the fields of Computer Science and Philosophy to the end of clarifying the nature of this newly emerging field and discussing different approaches one could take towards realizing the ultimate goal of creating an ethical machine.
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  6. Susan Leigh Anderson (2008). Asimov's “Three Laws of Robotics” and Machine Metaethics. AI and Society 22 (4):477-493.
    Using Asimov’s “Bicentennial Man” as a springboard, a number of metaethical issues concerning the emerging field of machine ethics are discussed. Although the ultimate goal of machine ethics is to create autonomous ethical machines, this presents a number of challenges. A good way to begin the task of making ethics computable is to create a program that enables a machine to act an ethical advisor to human beings. This project, unlike creating an autonomous ethical machine, will not require that we (...)
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  7. Oskamp Anja (1999). Richard Susskind, the Future of Law, Facing Challenges of Information Technology. Artificial Intelligence and Law 7 (4).
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  8. Ronald C. Arkin (2002). Robot Ethics. Ethics and Information Technology 4 (4):305-318.
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  9. Peter M. Asaro (2006). What Should We Want From a Robot Ethic. International Review of Information Ethics 6 (12):9-16.
    There are at least three things we might mean by "ethics in robotics": the ethical systems built into robots, the ethics of people who design and use robots, and the ethics of how people treat robots. This paper argues that the best approach to robot ethics is one which addresses all three of these, and to do this it ought to consider robots as socio-technical systems. By so doing, it is possible to think of a continuum of agency that lies (...)
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  10. Kevin D. Ashley & Will Bridewell (2010). Emerging AI & Law Approaches to Automating Analysis and Retrieval of Electronically Stored Information in Discovery Proceedings. Artificial Intelligence and Law 18 (4):311-320.
    This article provides an overview of, and thematic justification for, the special issue of the journal of Artificial Intelligence and Law entitled “E-Discovery”. In attempting to define a characteristic “AI & Law” approach to e-discovery, and since a central theme of AI & Law involves computationally modeling legal knowledge, reasoning and decision making, we focus on the theme of representing and reasoning with litigators’ theories or hypotheses about document relevance through a variety of techniques including machine learning. We also identify (...)
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  11. Hutan Ashrafian (2015). AIonAI: A Humanitarian Law of Artificial Intelligence and Robotics. Science and Engineering Ethics 21 (1):29-40.
    The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to their specification of preventing human harm, (...)
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  12. Hutan Ashrafian (2015). Artificial Intelligence and Robot Responsibilities: Innovating Beyond Rights. Science and Engineering Ethics 21 (2):317-326.
    The enduring innovations in artificial intelligence and robotics offer the promised capacity of computer consciousness, sentience and rationality. The development of these advanced technologies have been considered to merit rights, however these can only be ascribed in the context of commensurate responsibilities and duties. This represents the discernable next-step for evolution in this field. Addressing these needs requires attention to the philosophical perspectives of moral responsibility for artificial intelligence and robotics. A contrast to the moral status of animals may be (...)
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  13. 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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  14. Alexander Barzel (1998). The Perplexing Conclusion: The Essential Difference Between Natural and Artificial Intelligence is Human Beings' Ability to Deceive. Journal of Applied Philosophy 15 (2):165–178.
    As opposed to the computer, the human being can intentionally mislead in many different ways, can behave chaotically, and whenever he has the motivation can choose also by improvisation, non‐consequent misleading, and spontaneous manners of reasoning and articulation. Human perception and the elaboration of the experience are existentially interest‐related, and distorted if found necessary. The arbitrariness is unlimited; human beings can initiate and produce absurd combinations, contextual failures and deceptive expressions, and do so also by intonation and body‐language. These are (...)
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  15. John Basl (2013). The Ethics of Creating Artificial Consciousness. APA Newsletter on Philosophy and Computers 13 (1):23-29.
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  16. Colin Beardon (1994). Computers, Postmodernism and the Culture of the Artificial. AI and Society 8 (1):1-16.
    The term ‘the artificial’ can only be given a precise meaning in the context of the evolution of computational technology and this in turn can only be fully understood within a cultural setting that includes an epistemological perspective. The argument is illustrated in two case studies from the history of computational machinery: the first calculating machines and the first programmable computers. In the early years of electronic computers, the dominant form of computing was data processing which was a reflection of (...)
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  17. 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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  18. Brian P. Bloomfield & Theo Vurdubakis (2003). Imitation Games: Turing, Menard, Van Meegeren. [REVIEW] Ethics and Information Technology 5 (1):27-38.
    For many, the very idea of an artificialintelligence has always been ethicallytroublesome. The putative ability of machinesto mimic human intelligence appears to callinto question the stability of taken forgranted boundaries between subject/object,identity/similarity, free will/determinism,reality/simulation, etc. The artificiallyintelligent object thus appears to threaten thehuman subject with displacement and redundancy.This article takes as its starting point AlanTuring''s famous ''imitation game,'' (the socalled ''Turing Test''), here treated as aparable of the encounter between human originaland machine copy – the born and the made. Thecultural (...)
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  19. 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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  20. Selmer Bringsjord (2007). Ethical Robots: The Future Can Heed Us. [REVIEW] AI and Society 22 (4):539-550.
    Bill Joy’s deep pessimism is now famous. Why the Future Doesn’t Need Us, his defense of that pessimism, has been read by, it seems, everyone—and many of these readers, apparently, have been converted to the dark side, or rather more accurately, to the future-is-dark side. Fortunately (for us; unfortunately for Joy), the defense, at least the part of it that pertains to AI and robotics, fails. Ours may be a dark future, but we cannot know that on the basis of (...)
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  21. Jeff Buechner & Herman T. Tavani (2011). Trust and Multi-Agent Systems: Applying the Diffuse, Default Model of Trust to Experiments Involving Artificial Agents. [REVIEW] Ethics and Information Technology 13 (1):39-51.
    We argue that the notion of trust, as it figures in an ethical context, can be illuminated by examining research in artificial intelligence on multi-agent systems in which commitment and trust are modeled. We begin with an analysis of a philosophical model of trust based on Richard Holton’s interpretation of P. F. Strawson’s writings on freedom and resentment, and we show why this account of trust is difficult to extend to artificial agents (AAs) as well as to other non-human entities. (...)
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  22. Alan Bundy (1987). AI Bridges and Dreams. AI and Society 1 (1):62-71.
  23. Terrell Ward Bynum (2006). Flourishing Ethics. Ethics and Information Technology 8 (4):157-173.
    This essay describes a new ethical theory that has begun to coalesce from the works of several scholars in the international computer ethics community. I call the new theory ‚Flourishing Ethics’ because of its Aristotelian roots, though it also includes ideas suggestive of Taoism and Buddhism. In spite of its roots in ancient ethical theories, Flourishing Ethics is informed and grounded by recent scientific insights into the nature of living things, human nature and the fundamental nature of the universe – (...)
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  24. David J. Chalmers, Robert M. French & Douglas R. Hofstadter (1992). High-Level Perception, Representation, and Analogy:A Critique of Artificial Intelligence Methodology. Journal of Experimental and Theoretical Artificial Intellige 4 (3):185 - 211.
    High-level perception--”the process of making sense of complex data at an abstract, conceptual level--”is fundamental to human cognition. Through high-level perception, chaotic environmen- tal stimuli are organized into the mental representations that are used throughout cognitive pro- cessing. Much work in traditional artificial intelligence has ignored the process of high-level perception, by starting with hand-coded representations. In this paper, we argue that this dis- missal of perceptual processes leads to distorted models of human cognition. We examine some existing artificial-intelligence models--”notably (...)
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  25. Paul M. Churchland & Patricia S. Churchland (1983). Stalking the Wild Epistemic Engine. Noûs 17 (March):5-18.
  26. Steve Clarke (2005). Future Technologies, Dystopic Futures and the Precautionary Principle. Ethics and Information Technology 7 (3):121-126.
    It is sometimes suggested that new research in such areas as artificial intelligence, nanotechnology and genetic engineering should be halted or otherwise restricted because of concerns about possible catastrophic scenarios. Proponents of such restrictions typically invoke the precautionary principle, understood as a tool of policy formulation, as part of their case. Here I examine the application of the precautionary principle to possible catastrophic scenarios. I argue, along with Sunstein (Risk and Reason: Safety, Law and the Environment. Cambridge University Press, Cambridge, (...)
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  27. 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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  28. Mariella Combi (1992). The Imaginary, the Computer, Artificial Intelligence: A Cultural Anthropological Approach. [REVIEW] AI and Society 6 (1):41-49.
    The role of the cultural anthropologist in studying the results of information technology and artificial intelligence should be to contribute and reaffirm a sense of life which considers the human being in his or her totality, and to recognize the role of diversity and the imaginary. Technical revolutions have also proved to be cultural revolutions.The skills required by one culture, the identification and creation of problems and the solutions are interrelated. These interrelationships are worked out in a cultural context endowed (...)
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  29. B. Jack Copeland (ed.) (2005). Alan Turing's Automatic Computing Engine: The Master Codebreaker's Struggle to Build the Modern Computer. OUP Oxford.
    The mathematical genius Alan Turing (1912-1954) was one of the greatest scientists and thinkers of the 20th century. Now well known for his crucial wartime role in breaking the ENIGMA code, he was the first to conceive of the fundamental principle of the modern computer-the idea of controlling a computing machine's operations by means of a program of coded instructions, stored in the machine's 'memory'. In 1945 Turing drew up his revolutionary design for an electronic computing machine-his Automatic Computing Engine (...)
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  30. B. Jack Copeland & Diane Proudfoot (2000). What Turing Did After He Invented the Universal Turing Machine. Journal of Logic, Language and Information 9 (4):491-509.
    Alan Turing anticipated many areas of current research incomputer and cognitive science. This article outlines his contributionsto Artificial Intelligence, connectionism, hypercomputation, andArtificial Life, and also describes Turing's pioneering role in thedevelopment of electronic stored-program digital computers. It locatesthe origins of Artificial Intelligence in postwar Britain. It examinesthe intellectual connections between the work of Turing and ofWittgenstein in respect of their views on cognition, on machineintelligence, and on the relation between provability and truth. Wecriticise widespread and influential misunderstandings of theChurch–Turing thesis (...)
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  31. Roberto Cordeschi & Guglielmo Tamburrini (2005). Intelligent Machines and Warfare: Historical Debates and Epistemologically Motivated Concerns. In L. Magnani (ed.), European Computing and Philosophy Conference (ECAP 2004). College Publications
    The early examples of self-directing robots attracted the interest of both scientific and military communities. Biologists regarded these devices as material models of animal tropisms. Engineers envisaged the possibility of turning self-directing robots into new “intelligent” torpedoes during World War I. Starting from World War II, more extensive interactions developed between theoretical inquiry and applied military research on the subject of adaptive and intelligent machinery. Pioneers of Cybernetics were involved in the development of goal-seeking warfare devices. But collaboration occasionally turned (...)
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  32. Gordana Dodig Crnkovic & Baran Çürüklü (2012). Robots: Ethical by Design. Ethics and Information Technology 14 (1):61-71.
    Among ethicists and engineers within robotics there is an ongoing discussion as to whether ethical robots are possible or even desirable. We answer both of these questions in the positive, based on an extensive literature study of existing arguments. Our contribution consists in bringing together and reinterpreting pieces of information from a variety of sources. One of the conclusions drawn is that artifactual morality must come in degrees and depend on the level of agency, autonomy and intelligence of the machine. (...)
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  33. John Danaher (forthcoming). Why AI Doomsayers Are Like Sceptical Theists and Why It Matters. Minds and Machines:1-16.
    An advanced artificial intelligence (a “superintelligence”) could pose a significant existential risk to humanity. Several research institutes have been set-up to address those risks. And there is an increasing number of academic publications analysing and evaluating their seriousness. Nick Bostrom’s Superintelligence: Paths, Dangers, Strategies represents the apotheosis of this trend. In this article, I argue that in defending the credibility of AI risk, Bostrom makes an epistemic move that is analogous to one made by so-called sceptical theists in the debate (...)
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  34. Peter Danielson (2010). Designing a Machine to Learn About the Ethics of Robotics: The N-Reasons Platform. [REVIEW] Ethics and Information Technology 12 (3):251-261.
    We can learn about human ethics from machines. We discuss the design of a working machine for making ethical decisions, the N-Reasons platform, applied to the ethics of robots. This N-Reasons platform builds on web based surveys and experiments, to enable participants to make better ethical decisions. Their decisions are better than our existing surveys in three ways. First, they are social decisions supported by reasons. Second, these results are based on weaker premises, as no exogenous expertise (aside from that (...)
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  35. Ezio Di Nucci & Filippo Santoni de Sio (forthcoming). Who’s Afraid of Robots? Fear of Automation and the Ideal of Direct Control. In Fiorella Battaglia & Natalie Weidenfeld (eds.), Roboethics in Film. Pisa University Press
    We argue that lack of direct and conscious control is not, in principle, a reason to be afraid of machines in general and robots in particular: in order to articulate the ethical and political risks of increasing automation one must, therefore, tackle the difficult task of precisely delineating the theoretical and practical limits of sustainable delegation to robots.
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  36. Eric Dietrich (2011). Homo Sapiens 2.0 Why We Should Build the Better Robots of Our Nature. In M. Anderson S. Anderson (ed.), Machine Ethics. Cambridge Univ. Press
    It is possible to survey humankind and be proud, even to smile, for we accomplish great things. Art and science are two notable worthy human accomplishments. Consonant with art and science are some of the ways we treat each other. Sacrifice and heroism are two admirable human qualities <span class='Hi'>that</span> pervade human interaction. But, as everyone knows, all this goodness is more than balanced by human depravity. Moral corruption infests our being. Why?
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  37. Gordana Dodig Crnkovic & Baran Çürüklü (2012). Robots: Ethical by Design. [REVIEW] Ethics and Information Technology 14 (1):61-71.
    Among ethicists and engineers within robotics there is an ongoing discussion as to whether ethical robots are possible or even desirable. We answer both of these questions in the positive, based on an extensive literature study of existing arguments. Our contribution consists in bringing together and reinterpreting pieces of information from a variety of sources. One of the conclusions drawn is that artifactual morality must come in degrees and depend on the level of agency, autonomy and intelligence of the machine. (...)
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  38. Go Eguchi & Laurence L. Leff (2002). Rule-Based XML. Artificial Intelligence and Law 10 (4):283-294.
    Legal contracts and litigation documents common to the American legal system were encoded in the eXtensible Markup Language (XML). XML also represents rules about the contracts and litigation procedure. In addition to an expert system tool that allows one to make inferences with that engine, a Graphical User Interface (GUI) generates the XML representing the rules. A rulebase is developed by marking up examples of the XML to be interpreted and the XML to be generated, analogously to Query By Example. (...)
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  39. Richard Ennals (2009). Wendell Wallach and Colin Allen: Moral Machines: Teaching Robots Right From Wrong. [REVIEW] AI and Society 24 (2):207-208.
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  40. 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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  41. Philippe Gagnon (2012). The Problem of Trans-Humanism in the Light of Philosophy and Theology. In James B. Stump & Alan G. Padgett (eds.), The Blackwell Companion to Science and Christianity, pp. 393-405. Blackwell 393-405.
    Transhumanism is a means of advocating a re-engineering of conditions that surround human existence at both ends. The problem set before us in this chapter is to inquire into what determined its appearance, in particular in the humanism it seeks to overcome. We look at the spirit of overcoming itself, and the impatience with the Self, in order to try to understand why it seeks a saving power in technology. We then consider how the evolutionary account of the production of (...)
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  42. Jean-Gabriel Ganascia (2007). Modelling Ethical Rules of Lying with Answer Set Programming. Ethics and Information Technology 9 (1):39-47.
    There has been considerable discussion in the past about the assumptions and basis of different ethical rules. For instance, it is commonplace to say that ethical rules are defaults rules, which means that they tolerate exceptions. Some authors argue that morality can only be grounded in particular cases while others defend the existence of general principles related to ethical rules. Our purpose here is not to justify either position, but to try to model general ethical rules with artificial intelligence formalisms (...)
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  43. Petros A. M. Gelepithis (1999). AI and Human Society. AI and Society 13 (3):312-321.
    This paper considers the impact of the AI R&D programme on human society and the individual human being on the assumption that a full realisation of the engineering objective of AI, namely, construction of human-level, domain-independent intelligent entities, is possible. Our assumption is essentially identical tothe maximum progress scenario of the Office of Technology Assessment, US Congress.Specifically, the first section introduces some of the significant issues on the relational nexus among work, education and the human-machine boundary. In particular, based on (...)
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  44. Joanna Golinska-Pilarek, Angel Mora & Emilio Munoz Velasco (2008). An ATP of a Relational Proof System for Order of Magnitude Reasoning with Negligibility, Non-Closeness and Distance. In Tu-Bao Ho & Zhi-Hua Zhou (eds.), PRICAI 2008: Trends in Artificial Intelligence. Springer 128--139.
    We introduce an Automatic Theorem Prover (ATP) of a dual tableau system for a relational logic for order of magnitude qualitative reasoning, which allows us to deal with relations such as negligibility, non-closeness and distance. Dual tableau systems are validity checkers that can serve as a tool for verification of a variety of tasks in order of magnitude reasoning, such as the use of qualitative sum of some classes of numbers. In the design of our ATP, we have introduced some (...)
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  45. Jaap C. Hage, Ronald Leenes & Arno R. Lodder (1993). Hard Cases: A Procedural Approach. [REVIEW] Artificial Intelligence and Law 2 (2):113-167.
    Much work on legal knowledge systems treats legal reasoning as arguments that lead from a description of the law and the facts of a case, to the legal conclusion for the case. The reasoning steps of the inference engine parallel the logical steps by means of which the legal conclusion is derived from the factual and legal premises. In short, the relation between the input and the output of a legal inference engine is a logical one. The truth of the (...)
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  46. J. Storrs Hall (2006). Nano-Enabled AI. International Journal of Applied Philosophy 20 (2):247-261.
    Improvements in computational hardware enabled by nanotechnology promise a dual revolution in coming decades: machines which are both more intelligent and more numerous than human beings. This possibility raises substantial concern over the moral nature of such intelligent machines. An analysis of the prospects involves at least two key philosophical issues. The first, intentionality in formal systems, turns on whether a “mere machine” can be a mind whose thoughts have true meaning and understanding. Second, what is the moral nature of (...)
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  47. Thomas Hellström (2013). On the Moral Responsibility of Military Robots. Ethics and Information Technology 15 (2):99-107.
    This article discusses mechanisms and principles for assignment of moral responsibility to intelligent robots, with special focus on military robots. We introduce the concept autonomous power as a new concept, and use it to identify the type of robots that call for moral considerations. It is furthermore argued that autonomous power, and in particular the ability to learn, is decisive for assignment of moral responsibility to robots. As technological development will lead to robots with increasing autonomous power, we should be (...)
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  48. Deborah G. Johnson & Thomas M. Powers (2009). Ethics and Technology: A Program for Future Research. In M. Winston and R. Edelbach (ed.), Society, Ethics, and Technology, 4th edition.
    This chapter is reprinted from our lead essay in the Encyclopedia of Science, Technology, and Ethics, ed. C. Mitcham, Gale, 2005.
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  49. Deborah G. Johnson & Thomas M. Powers (2008). Computers as Surrogate Agents. In M. J. van den Joven & J. Weckert (eds.), Information Technology and Moral Philosophy. Cambridge University Press 251.
  50. Deborah G. Johnson & Thomas M. Powers (2005). Computer Systems and Responsibility: A Normative Look at Technological Complexity. [REVIEW] Ethics and Information Technology 7 (2):99-107.
    In this paper, we focus attention on the role of computer system complexity in ascribing responsibility. We begin by introducing the notion of technological moral action (TMA). TMA is carried out by the combination of a computer system user, a system designer (developers, programmers, and testers), and a computer system (hardware and software). We discuss three sometimes overlapping types of responsibility: causal responsibility, moral responsibility, and role responsibility. Our analysis is informed by the well-known accounts provided by Hart and Hart (...)
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