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  1. The responsibility gap: Ascribing responsibility for the actions of learning automata.Andreas Matthias - 2004 - Ethics and Information Technology 6 (3):175-183.
    Traditionally, the manufacturer/operator of a machine is held (morally and legally) responsible for the consequences of its operation. Autonomous, learning machines, based on neural networks, genetic algorithms and agent architectures, create a new situation, where the manufacturer/operator of the machine is in principle not capable of predicting the future machine behaviour any more, and thus cannot be held morally responsible or liable for it. The society must decide between not using this kind of machine any more (which is not a (...)
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  • The Ethics of AI Ethics: An Evaluation of Guidelines.Thilo Hagendorff - 2020 - Minds and Machines 30 (1):99-120.
    Current advances in research, development and application of artificial intelligence systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies. Designed as a semi-systematic evaluation, this paper analyzes and compares 22 guidelines, highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of AI ethics. Finally, (...)
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  • AI4People—an ethical framework for a good AI society: opportunities, risks, principles, and recommendations.Luciano Floridi, Josh Cowls, Monica Beltrametti, Raja Chatila, Patrice Chazerand, Virginia Dignum, Christoph Luetge, Robert Madelin, Ugo Pagallo, Francesca Rossi, Burkhard Schafer, Peggy Valcke & Effy Vayena - 2018 - Minds and Machines 28 (4):689-707.
    This article reports the findings of AI4People, an Atomium—EISMD initiative designed to lay the foundations for a “Good AI Society”. We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations—to assess, to develop, to incentivise, and to support good AI—which in some cases may be undertaken directly by national or supranational policy makers, while in others may be led by other (...)
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  • Principles of Biomedical Ethics: Marking Its Fortieth Anniversary.James Childress & Tom Beauchamp - 2019 - American Journal of Bioethics 19 (11):9-12.
    Volume 19, Issue 11, November 2019, Page 9-12.
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  • Embedded ethics: some technical and ethical challenges.Vincent Bonnemains, Claire Saurel & Catherine Tessier - 2018 - Ethics and Information Technology 20 (1):41-58.
    This paper pertains to research works aiming at linking ethics and automated reasoning in autonomous machines. It focuses on a formal approach that is intended to be the basis of an artificial agent’s reasoning that could be considered by a human observer as an ethical reasoning. The approach includes some formal tools to describe a situation and models of ethical principles that are designed to automatically compute a judgement on possible decisions that can be made in a given situation and (...)
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  • What does it mean to embed ethics in data science? An integrative approach based on the microethics and virtues.Louise Bezuidenhout & Emanuele Ratti - 2021 - AI and Society 36:939–953.
    In the past few years, scholars have been questioning whether the current approach in data ethics based on the higher level case studies and general principles is effective. In particular, some have been complaining that such an approach to ethics is difficult to be applied and to be taught in the context of data science. In response to these concerns, there have been discussions about how ethics should be “embedded” in the practice of data science, in the sense of showing (...)
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  • A vision of Responsible Innovation.Rene Von Schomberg - 2017 - In L. Asveld, R. Van Dam-Mieras, T. Swierstra, S. Lavrijssen, K. Linse & J. Van Den Hoven (eds.), Responsible Innovation. Springer International Publishing. pp. 51-74.
    This Article outlines a vision of responsible innovation and outlines a public policy and implementation strategy for it.
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  • Responsible Artificial Intelligence: How to Develop and Use Ai in a Responsible Way.Virginia Dignum - 2019 - Springer Verlag.
    In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. Throughout (...)
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  • Specifying, balancing, and interpreting bioethical principles.Henry S. Richardson - 2000 - Journal of Medicine and Philosophy 25 (3):285 – 307.
    The notion that it is useful to specify norms progressively in order to resolve doubts about what to do, which I developed initially in a 1990 article, has been only partly assimilated by the bioethics literature. The thought is not just that it is helpful to work with relatively specific norms. It is more than that: specification can replace deductive subsumption and balancing. Here I argue against two versions of reliance on balancing that are prominent in recent bioethical discussions. Without (...)
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  • Computer knows best? The need for value-flexibility in medical AI.Rosalind J. McDougall - 2019 - Journal of Medical Ethics 45 (3):156-160.
    Artificial intelligence is increasingly being developed for use in medicine, including for diagnosis and in treatment decision making. The use of AI in medical treatment raises many ethical issues that are yet to be explored in depth by bioethicists. In this paper, I focus specifically on the relationship between the ethical ideal of shared decision making and AI systems that generate treatment recommendations, using the example of IBM’s Watson for Oncology. I argue that use of this type of system creates (...)
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  • The responsibility gap: Ascribing responsibility for the actions of learning automata. [REVIEW]Andreas Matthias - 2004 - Ethics and Information Technology 6 (3):175-183.
    Traditionally, the manufacturer/operator of a machine is held (morally and legally) responsible for the consequences of its operation. Autonomous, learning machines, based on neural networks, genetic algorithms and agent architectures, create a new situation, where the manufacturer/operator of the machine is in principle not capable of predicting the future machine behaviour any more, and thus cannot be held morally responsible or liable for it. The society must decide between not using this kind of machine any more (which is not a (...)
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  • Standards of practice in empirical bioethics research: towards a consensus.Jonathan Ives, Michael Dunn, Bert Molewijk, Jan Schildmann, Kristine Bærøe, Lucy Frith, Richard Huxtable, Elleke Landeweer, Marcel Mertz, Veerle Provoost, Annette Rid, Sabine Salloch, Mark Sheehan, Daniel Strech, Martine de Vries & Guy Widdershoven - 2018 - BMC Medical Ethics 19 (1):68.
    This paper responds to the commentaries from Stacy Carter and Alan Cribb. We pick up on two main themes in our response. First, we reflect on how the process of setting standards for empirical bioethics research entails drawing boundaries around what research counts as empirical bioethics research, and we discuss whether the standards agreed in the consensus process draw these boundaries correctly. Second, we expand on the discussion in the original paper of the role and significance of the concept of (...)
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  • Ethical Design of Intelligent Assistive Technologies for Dementia: A Descriptive Review.Marcello Ienca, Tenzin Wangmo, Fabrice Jotterand, Reto W. Kressig & Bernice Elger - 2018 - Science and Engineering Ethics 24 (4):1035-1055.
    The use of Intelligent Assistive Technology in dementia care opens the prospects of reducing the global burden of dementia and enabling novel opportunities to improve the lives of dementia patients. However, with current adoption rates being reportedly low, the potential of IATs might remain under-expressed as long as the reasons for suboptimal adoption remain unaddressed. Among these, ethical and social considerations are critical. This article reviews the spectrum of IATs for dementia and investigates the prevalence of ethical considerations in the (...)
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  • Translating principles into practices of digital ethics: five risks of being unethical.Luciano Floridi - 2019 - Philosophy and Technology 32 (2):185-193.
    Modern digital technologies—from web-based services to Artificial Intelligence (AI) solutions—increasingly affect the daily lives of billions of people. Such innovation brings huge opportunities, but also concerns about design, development, and deployment of digital technologies. This article identifies and discusses five clusters of risk in the international debate about digital ethics: ethics shopping; ethics bluewashing; ethics lobbying; ethics dumping; and ethics shirking.
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  • Ethical foresight analysis: what it is and why it is needed?Luciano Floridi & Andrew Strait - 2020 - Minds and Machines 30 (1):77-97.
    An increasing number of technology firms are implementing processes to identify and evaluate the ethical risks of their systems and products. A key part of these review processes is to foresee potential impacts of these technologies on different groups of users. In this article, we use the expression Ethical Foresight Analysis to refer to a variety of analytical strategies for anticipating or predicting the ethical issues that new technological artefacts, services, and applications may raise. This article examines several existing EFA (...)
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  • Ethical Foresight Analysis: What It Is and Why It Is Needed?Luciano Floridi & Andrew Strait - 2021 - In Josh Cowls & Jessica Morley (eds.), The 2020 Yearbook of the Digital Ethics Lab. Springer Verlag. pp. 173-194.
    An increasing number of technology firms are implementing processes to identify and evaluate the ethical risks of their systems and products. A key part of these review processes is to foresee potential impacts of these technologies on different groups of users. In this chapter, we use the expression Ethical Foresight Analysis to refer to a variety of analytical strategies for anticipating or predicting the ethical issues that new technological artefacts, services, and applications may raise. This chapter examines several existing EFA (...)
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  • Principles of Biomedical Ethics.Ezekiel J. Emanuel, Tom L. Beauchamp & James F. Childress - 1995 - Hastings Center Report 25 (4):37.
    Book reviewed in this article: Principles of Biomedical Ethics. By Tom L. Beauchamp and James F. Childress.
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