Machine Ethics

Edited by Jeffrey White (Okinawa Institute Of Science And Technology, Universidade Nova de Lisboa)
About this topic
Summary In the early 2000s, James Moor set out four classes of ethical machine, advising that the near-term focus of machine ethics research should be on "explicit ethical agents", agents designed from an understanding of human theoretical ethics to operate according with these theoretical principles. Above this class, the ultimate aim of inquiry into machine ethics is understanding human morality and natural science well enough to engineer a fully autonomous, moral machine. This sub-category focuses on supporting this inquiry. Other work on other sorts of computer applications and their ethical impacts appear in different categories, including Ethics of Artificial Intelligence, Moral Status of Artificial Systems, and also Robot Ethics, Algorithmic Fairness, Computer Ethics, and others. Machine ethics is ethics, and it is also a study of machines. Machine ethicists wonder why people, human beings, other organisms, do what they do when they do it, and what makes these things the right things to do - they are ethicists. In addition, machine ethicists work out how to articulate such processes in an independent artificial system (rather than by parenting a biological child, or training a human minion, as traditional alternatives). So, machine ethics researchers engage directly with rapidly advancing work in cognitive science and psychology alongside that in robotics and AI, applied ethics such as medical ethics and philosophy of mind, computer modeling and data science, and so on. Drawing from so many disciplines with all of these advancing rapidly and with their own impacts, machine ethics is in the middle of a maelstrom of current research activity. Advances in materials science and physical chemistry leverage advances in cognitive science and neurology which feed advances in AI and robotics, including in regards to its interpretability for illustration. Putting this all together is the challenge for the machine ethics researcher. This sub-category is intended to support efforts to meet this challenge.  
Key works Allen et al 2005Wallach et al 2008Tonkens 2012Tonkens 2009Müller & Bostrom 2014White 2013White 2015
Introductions Anderson & Anderson 2007, Segun 2021, Powers 2011, Moor 2006
Related categories

459 found
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  1. Ética e Segurança da Inteligência Artificial: ferramentas práticas para se criar "bons" modelos.Nicholas Kluge Corrêa - manuscript
    A AI Robotics Ethics Society (AIRES) é uma organização sem fins lucrativos fundada em 2018 por Aaron Hui, com o objetivo de se promover a conscientização e a importância da implementação e regulamentação ética da AI. A AIRES é hoje uma organização com capítulos em universidade como UCLA (Los Angeles), USC (University of Southern California), Caltech (California Institute of Technology), Stanford University, Cornell University, Brown University e a Pontifícia Universidade Católica do Rio Grande do Sul (Brasil). AIRES na PUCRS é (...)
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  2. Can a robot lie?Markus Kneer - manuscript
    The potential capacity for robots to deceive has received considerable attention recently. Many papers focus on the technical possibility for a robot to engage in deception for beneficial purposes (e.g. in education or health). In this short experimental paper, I focus on a more paradigmatic case: Robot lying (lying being the textbook example of deception) for nonbeneficial purposes as judged from the human point of view. More precisely, I present an empirical experiment with 399 participants which explores the following three (...)
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  3. First human upload as AI Nanny.Alexey Turchin - manuscript
    Abstract: As there are no visible ways to create safe self-improving superintelligence, but it is looming, we probably need temporary ways to prevent its creation. The only way to prevent it, is to create special AI, which is able to control and monitor all places in the world. The idea has been suggested by Goertzel in form of AI Nanny, but his Nanny is still superintelligent and not easy to control, as was shown by Bensinger at al. We explore here (...)
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  4. Literature Review: What Artificial General Intelligence Safety Researchers Have Written About the Nature of Human Values.Alexey Turchin & David Denkenberger - manuscript
    Abstract: The field of artificial general intelligence (AGI) safety is quickly growing. However, the nature of human values, with which future AGI should be aligned, is underdefined. Different AGI safety researchers have suggested different theories about the nature of human values, but there are contradictions. This article presents an overview of what AGI safety researchers have written about the nature of human values, up to the beginning of 2019. 21 authors were overviewed, and some of them have several theories. A (...)
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  5. Autonomous Reboot: the challenges of artificial moral agency and the ends of Machine Ethics.Jeffrey White - manuscript
    Ryan Tonkens (2009) has issued a seemingly impossible challenge, to articulate a comprehensive ethical framework within which artificial moral agents (AMAs) satisfy a Kantian inspired recipe - both "rational" and "free" - while also satisfying perceived prerogatives of Machine Ethics to create AMAs that are perfectly, not merely reliably, ethical. Challenges for machine ethicists have also been presented by Anthony Beavers and Wendell Wallach, who have pushed for the reinvention of traditional ethics in order to avoid "ethical nihilism" due to (...)
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  6. Artificial Intelligence Ethics and Safety: practical tools for creating "good" models.Nicholas Kluge Corrêa -
    The AI Robotics Ethics Society (AIRES) is a non-profit organization founded in 2018 by Aaron Hui to promote awareness and the importance of ethical implementation and regulation of AI. AIRES is now an organization with chapters at universities such as UCLA (Los Angeles), USC (University of Southern California), Caltech (California Institute of Technology), Stanford University, Cornell University, Brown University, and the Pontifical Catholic University of Rio Grande do Sul (Brazil). AIRES at PUCRS is the first international chapter of AIRES, and (...)
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  7. Two arguments against human-friendly AI.Ken Daley - forthcoming - AI and Ethics.
    The past few decades have seen a substantial increase in the focus on the myriad ethical implications of artificial intelligence. Included amongst the numerous issues is the existential risk that some believe could arise from the development of artificial general intelligence (AGI) which is an as-of-yet hypothetical form of AI that is able to perform all the same intellectual feats as humans. This has led to extensive research into how humans can avoid losing control of an AI that is at (...)
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  8. Making moral machines: why we need artificial moral agents.Paul Formosa & Malcolm Ryan - forthcoming - AI and Society.
    As robots and Artificial Intelligences become more enmeshed in rich social contexts, it seems inevitable that we will have to make them into moral machines equipped with moral skills. Apart from the technical difficulties of how we could achieve this goal, we can also ask the ethical question of whether we should seek to create such Artificial Moral Agents (AMAs). Recently, several papers have argued that we have strong reasons not to develop AMAs. In response, we develop a comprehensive analysis (...)
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  9. Make Them Rare or Make Them Care: Artificial Intelligence and Moral Cost-Sharing.Blake Hereth & Nicholas Evans - forthcoming - In Daniel Schoeni, Tobias Vestner & Kevin Govern (eds.), Ethical Dilemmas in the Global Defense Industry. Oxford University Press.
    The use of autonomous weaponry in warfare has increased substantially over the last twenty years and shows no sign of slowing. Our chapter raises a novel objection to the implementation of autonomous weapons, namely, that they eliminate moral cost-sharing. To grasp the basics of our argument, consider the case of uninhabited aerial vehicles that act autonomously (i.e., LAWS). Imagine that a LAWS terminates a military target and that five civilians die as a side effect of the LAWS bombing. Because LAWS (...)
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  10. Quantum of Wisdom.Brett Karlan & Colin Allen - forthcoming - In Greg Viggiano (ed.), Quantum Computing and AI: Social, Ethical, and Geo-Political Implications. Hoboken, NJ: Wiley-Blackwell. pp. 1-6.
    Practical quantum computing devices and their applications to AI in particular are presently mostly speculative. Nevertheless, questions about whether this future technology, if achieved, presents any special ethical issues are beginning to take shape. As with any novel technology, one can be reasonably confident that the challenges presented by "quantum AI" will be a mixture of something new and something old. Other commentators (Sevilla & Moreno 2019), have emphasized continuity, arguing that quantum computing does not substantially affect approaches to value (...)
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  11. Machine morality, moral progress, and the looming environmental disaster.Ben Kenward & Thomas Sinclair - forthcoming - Cognitive Computation and Systems.
    The creation of artificial moral systems requires us to make difficult choices about which of varying human value sets should be instantiated. The industry-standard approach is to seek and encode moral consensus. Here we argue, based on evidence from empirical psychology, that encoding current moral consensus risks reinforcing current norms, and thus inhibiting moral progress. However, so do efforts to encode progressive norms. Machine ethics is thus caught between a rock and a hard place. The problem is particularly acute when (...)
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  12. Digital Well-Being and Manipulation Online.Michael Klenk - forthcoming - In Christopher Burr & Luciano Floridi (eds.), Ethics of Digital Well-being: A Multidisciplinary Approach. Springer.
    Social media use is soaring globally. Existing research of its ethical implications predominantly focuses on the relationships amongst human users online, and their effects. The nature of the software-to-human relationship and its impact on digital well-being, however, has not been sufficiently addressed yet. This paper aims to close the gap. I argue that some intelligent software agents, such as newsfeed curator algorithms in social media, manipulate human users because they do not intend their means of influence to reveal the user’s (...)
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  13. Accountability in Artificial Intelligence: What It Is and How It Works.Claudio Novelli, Mariarosaria Taddeo & Luciano Floridi - forthcoming - Ai and Society: Knowledge, Culture and Communication.
    Accountability is a cornerstone of the governance of artificial intelligence (AI). However, it is often defined too imprecisely because its multifaceted nature and the sociotechnical structure of AI systems imply a variety of values, practices, and measures to which accountability in AI can refer. We address this lack of clarity by defining accountability in terms of answerability, identifying three conditions of possibility (authority recognition, interrogation, and limitation of power), and an architecture of seven features (context, range, agent, forum, standards, process, (...)
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  14. Digital suffering: why it's a problem and how to prevent it.Bradford Saad & Adam Bradley - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    As ever more advanced digital systems are created, it becomes increasingly likely that some of these systems will be digital minds, i.e. digital subjects of experience. With digital minds comes the risk of digital suffering. The problem of digital suffering is that of mitigating this risk. We argue that the problem of digital suffering is a high stakes moral problem and that formidable epistemic obstacles stand in the way of solving it. We then propose a strategy for solving it: Access (...)
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  15. Handbook of Research on Machine Ethics and Morality.Steven John Thompson (ed.) - forthcoming - Hershey, PA: IGI-Global.
    This book is dedicated to expert research topics, and analyses of ethics-related inquiry, at the machine ethics and morality level: key players, benefits, problems, policies, and strategies. Gathering some of the leading voices that recognize and understand the complexities and intricacies of human-machine ethics provides a resourceful compendium to be accessed by decision-makers and theorists concerned with identification and adoption of human-machine ethics initiatives, leading to needed policy adoption and reform for human-machine entities, their technologies, and their societal and legal (...)
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  16. Varieties of Artificial Moral Agency and the New Control Problem.Marcus Arvan - 2022 - Humana.Mente - Journal of Philosophical Studies 15 (42):225-256.
    This paper presents a new trilemma with respect to resolving the control and alignment problems in machine ethics. Section 1 outlines three possible types of artificial moral agents (AMAs): (1) 'Inhuman AMAs' programmed to learn or execute moral rules or principles without understanding them in anything like the way that we do; (2) 'Better-Human AMAs' programmed to learn, execute, and understand moral rules or principles somewhat like we do, but correcting for various sources of human moral error; and (3) 'Human-Like (...)
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  17. From Responsibility to Reason-Giving Explainable Artificial Intelligence.Kevin Baum, Susanne Mantel, Timo Speith & Eva Schmidt - 2022 - Philosophy and Technology 35 (1):1-30.
    We argue that explainable artificial intelligence (XAI), specifically reason-giving XAI, often constitutes the most suitable way of ensuring that someone can properly be held responsible for decisions that are based on the outputs of artificial intelligent (AI) systems. We first show that, to close moral responsibility gaps (Matthias 2004), often a human in the loop is needed who is directly responsible for particular AI-supported decisions. Second, we appeal to the epistemic condition on moral responsibility to argue that, in order to (...)
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  18. Autonomous Vehicles, Business Ethics, and Risk Distribution in Hybrid Traffic.Brian Berkey - 2022 - In Ryan Jenkins, David Cerny & Tomas Hribek (eds.), Autonomous Vehicle Ethics: The Trolley Problem and Beyond. New York, NY, USA: pp. 210-228.
    In this chapter, I argue that in addition to the generally accepted aim of reducing traffic-related injuries and deaths as much as possible, a principle of fairness in the distribution of risk should inform our thinking about how firms that produce autonomous vehicles ought to program them to respond in conflict situations involving human-driven vehicles. This principle, I claim, rules out programming autonomous vehicles to systematically prioritize the interests of their occupants over those of the occupants of other vehicles, including (...)
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  19. Extending the Is-ought Problem to Top-down Artificial Moral Agents.Robert James M. Boyles - 2022 - Symposion: Theoretical and Applied Inquiries in Philosophy and Social Sciences 9 (2):171–189.
    This paper further cashes out the notion that particular types of intelligent systems are susceptible to the is-ought problem, which espouses the thesis that no evaluative conclusions may be inferred from factual premises alone. Specifically, it focuses on top-down artificial moral agents, providing ancillary support to the view that these kinds of artifacts are not capable of producing genuine moral judgements. Such is the case given that machines built via the classical programming approach are always composed of two parts, namely: (...)
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  20. Legitimacy and automated decisions: the moral limits of algocracy.Bartek Chomanski - 2022 - Ethics and Information Technology 24 (3):1-9.
    With the advent of automated decision-making, governments have increasingly begun to rely on artificially intelligent algorithms to inform policy decisions across a range of domains of government interest and influence. The practice has not gone unnoticed among philosophers, worried about “algocracy”, and its ethical and political impacts. One of the chief issues of ethical and political significance raised by algocratic governance, so the argument goes, is the lack of transparency of algorithms. One of the best-known examples of philosophical analyses of (...)
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  21. Blame It on the AI? On the Moral Responsibility of Artificial Moral Advisors.Mihaela Constantinescu, Constantin Vică, Radu Uszkai & Cristina Voinea - 2022 - Philosophy and Technology 35 (2):1-26.
    Deep learning AI systems have proven a wide capacity to take over human-related activities such as car driving, medical diagnosing, or elderly care, often displaying behaviour with unpredictable consequences, including negative ones. This has raised the question whether highly autonomous AI may qualify as morally responsible agents. In this article, we develop a set of four conditions that an entity needs to meet in order to be ascribed moral responsibility, by drawing on Aristotelian ethics and contemporary philosophical research. We encode (...)
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  22. Apprehending AI moral purpose in practical wisdom.Mark Graves - 2022 - AI and Society:1-14.
    Practical wisdom enables moral decision-making and action by aligning one’s apprehension of proximate goods with a distal, socially embedded interpretation of a more ultimate Good. A focus on purpose within the overall process mutually informs human moral psychology and moral AI development in their examinations of practical wisdom. AI practical wisdom could ground an AI system’s apprehension of reality in a sociotechnical moral process committed to orienting AI development and action in light of a pluralistic, diverse interpretation of that Good. (...)
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  23. Theological Foundations for Moral Artificial Intelligence.Mark Graves - 2022 - Journal of Moral Theology 11 (Special Issue 1):182-211.
    The expanding social role and continued development of artificial intelligence (AI) needs theological investigation of its anthropological and moral potential. A pragmatic theological anthropology adapted for AI can characterize moral AI as experiencing its natural, social, and moral world through interpretations of its external reality as well as its self-reckoning. Systems theory can further structure insights into an AI social self that conceptualizes itself within Ignacio Ellacuria’s historical reality and its moral norms through Thomistic ideogenesis. This enables a conceptualization process (...)
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  24. A Fuzzy-Cognitive-Maps Approach to Decision-Making in Medical Ethics.Alice Hein, Lukas J. Meier, Alena Buyx & Klaus Diepold - 2022 - 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).
    Although machine intelligence is increasingly employed in healthcare, the realm of decision-making in medical ethics remains largely unexplored from a technical perspective. We propose an approach based on fuzzy cognitive maps (FCMs), which builds on Beauchamp and Childress’ prima-facie principles. The FCM’s weights are optimized using a genetic algorithm to provide recommendations regarding the initiation, continuation, or withdrawal of medical treatment. The resulting model approximates the answers provided by our team of medical ethicists fairly well and offers a high degree (...)
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  25. AI, alignment, and the categorical imperative.Fritz McDonald - 2022 - AI and Ethics.
    Tae Wan Kim, John Hooker, and Thomas Donaldson make an attempt, in recent articles, to solve the alignment problem. As they define the alignment problem, it is the issue of how to give AI systems moral intelligence. They contend that one might program machines with a version of Kantian ethics cast in deontic modal logic. On their view, machines can be aligned with human values if such machines obey principles of universalization and autonomy, as well as a deontic utilitarian principle. (...)
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  26. Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept.Lukas J. Meier, Alice Hein, Klaus Diepold & Alena Buyx - 2022 - American Journal of Bioethics 22 (7):4-20.
    Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on the (...)
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  27. Clinical Ethics – To Compute, or Not to Compute?Lukas J. Meier, Alice Hein, Klaus Diepold & Alena Buyx - 2022 - American Journal of Bioethics 22 (12):W1-W4.
    Can machine intelligence do clinical ethics? And if so, would applying it to actual medical cases be desirable? In a recent target article (Meier et al. 2022), we described the piloting of our advisory algorithm METHAD. Here, we reply to commentaries published in response to our project. The commentaries fall into two broad categories: concrete criticism that concerns the development of METHAD; and the more general question as to whether one should employ decision-support systems of this kind—the debate we set (...)
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  28. Ethical Issues with Artificial Ethics Assistants.Elizabeth O'Neill, Michal Klincewicz & Michiel Kemmer - 2022 - In Oxford Handbook of Digital Ethics. Oxford: Oxford University Press.
    This chapter examines the possibility of using AI technologies to improve human moral reasoning and decision-making, especially in the context of purchasing and consumer decisions. We characterize such AI technologies as artificial ethics assistants (AEAs). We focus on just one part of the AI-aided moral improvement question: the case of the individual who wants to improve their morality, where what constitutes an improvement is evaluated by the individual’s own values. We distinguish three broad areas in which an individual might think (...)
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  29. Responsibility gaps and the reactive attitudes.Fabio Tollon - 2022 - AI and Ethics 1 (1).
    Artificial Intelligence (AI) systems are ubiquitous. From social media timelines, video recommendations on YouTube, and the kinds of adverts we see online, AI, in a very real sense, filters the world we see. More than that, AI is being embedded in agent-like systems, which might prompt certain reactions from users. Specifically, we might find ourselves feeling frustrated if these systems do not meet our expectations. In normal situations, this might be fine, but with the ever increasing sophistication of AI-systems, this (...)
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  30. Designing AI for Explainability and Verifiability: A Value Sensitive Design Approach to Avoid Artificial Stupidity in Autonomous Vehicles.Steven Umbrello & Roman Yampolskiy - 2022 - International Journal of Social Robotics 14 (2):313-322.
    One of the primary, if not most critical, difficulties in the design and implementation of autonomous systems is the black-boxed nature of the decision-making structures and logical pathways. How human values are embodied and actualised in situ may ultimately prove to be harmful if not outright recalcitrant. For this reason, the values of stakeholders become of particular significance given the risks posed by opaque structures of intelligent agents (IAs). This paper explores how decision matrix algorithms, via the belief-desire-intention model for (...)
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  31. Autonomous reboot: Aristotle, autonomy and the ends of machine ethics.Jeffrey White - 2022 - AI and Society 37 (2):647-659.
    Tonkens has issued a seemingly impossible challenge, to articulate a comprehensive ethical framework within which artificial moral agents satisfy a Kantian inspired recipe—"rational" and "free"—while also satisfying perceived prerogatives of machine ethicists to facilitate the creation of AMAs that are perfectly and not merely reliably ethical. Challenges for machine ethicists have also been presented by Anthony Beavers and Wendell Wallach. Beavers pushes for the reinvention of traditional ethics to avoid "ethical nihilism" due to the reduction of morality to mechanical causation. (...)
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  32. Autonomous Reboot: Kant, the categorical imperative, and contemporary challenges for machine ethicists.Jeffrey White - 2022 - AI and Society 37 (2):661-673.
    Ryan Tonkens has issued a seemingly impossible challenge, to articulate a comprehensive ethical framework within which artificial moral agents satisfy a Kantian inspired recipe—"rational" and "free"—while also satisfying perceived prerogatives of machine ethicists to facilitate the creation of AMAs that are perfectly and not merely reliably ethical. This series of papers meets this challenge by landscaping traditional moral theory in resolution of a comprehensive account of moral agency. The first paper established the challenge and set out autonomy in Aristotelian terms. (...)
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  33. Towards Moral Machines: A Discussion with Michael Anderson and Susan Leigh Anderson.Michael Anderson, Susan Leigh Anderson, Alkis Gounaris & George Kosteletos - 2021 - Conatus 6 (1).
    At the turn of the 21st century, Susan Leigh Anderson and Michael Anderson conceived and introduced the Machine Ethics research program, that aimed to highlight the requirements under which autonomous artificial intelligence systems could demonstrate ethical behavior guided by moral values, and at the same time to show that these values, as well as ethics in general, can be representable and computable. Today, the interaction between humans and AI entities is already part of our everyday lives; in the near future (...)
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  34. Prolegómenos a una ética para la robótica social.Júlia Pareto Boada - 2021 - Dilemata 34:71-87.
    Social robotics has a high disruptive potential, for it expands the field of application of intelligent technology to practical contexts of a relational nature. Due to their capacity to “intersubjectively” interact with people, social robots can take over new roles in our daily activities, multiplying the ethical implications of intelligent robotics. In this paper, we offer some preliminary considerations for the ethical reflection on social robotics, so that to clarify how to correctly orient the critical-normative thinking in this arduous task. (...)
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  35. The Mandatory Ontology of Robot Responsibility.Marc Champagne - 2021 - Cambridge Quarterly of Healthcare Ethics 30 (3):448–454.
    Do we suddenly become justified in treating robots like humans by positing new notions like “artificial moral agency” and “artificial moral responsibility”? I answer no. Or, to be more precise, I argue that such notions may become philosophically acceptable only after crucial metaphysical issues have been addressed. My main claim, in sum, is that “artificial moral responsibility” betokens moral responsibility to the same degree that a “fake orgasm” betokens an orgasm.
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  36. Understanding responsibility in Responsible AI. Dianoetic virtues and the hard problem of context.Mihaela Constantinescu, Cristina Voinea, Radu Uszkai & Constantin Vică - 2021 - Ethics and Information Technology 23 (4):803-814.
    During the last decade there has been burgeoning research concerning the ways in which we should think of and apply the concept of responsibility for Artificial Intelligence. Despite this conceptual richness, there is still a lack of consensus regarding what Responsible AI entails on both conceptual and practical levels. The aim of this paper is to connect the ethical dimension of responsibility in Responsible AI with Aristotelian virtue ethics, where notions of context and dianoetic virtues play a grounding role for (...)
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  37. Dynamic Cognition Applied to Value Learning in Artificial Intelligence.Nythamar De Oliveira & Nicholas Corrêa - 2021 - Aoristo - International Journal of Phenomenology, Hermeneutics and Metaphysics 4 (2):185-199.
    Experts in Artificial Intelligence (AI) development predict that advances in the dvelopment of intelligent systems and agents will reshape vital areas in our society. Nevertheless, if such an advance isn't done with prudence, it can result in negative outcomes for humanity. For this reason, several researchers in the area are trying to develop a robust, beneficial, and safe concept of artificial intelligence. Currently, several of the open problems in the field of AI research arise from the difficulty of avoiding unwanted (...)
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  38. The Unfounded Bias Against Autonomous Weapons Systems.Áron Dombrovszki - 2021 - Információs Társadalom 21 (2):13–28.
    Autonomous Weapons Systems (AWS) have not gained a good reputation in the past. This attitude is odd if we look at the discussion of other-usually highly anticipated-AI-technologies, like autonomous vehicles (AVs); whereby even though these machines evoke very similar ethical issues, philosophers' attitudes towards them are constructive. In this article, I try to prove that there is an unjust bias against AWS because almost every argument against them is effective against AVs too. I start with the definition of "AWS." Then, (...)
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  39. Robot Autonomy vs. Human Autonomy: Social Robots, Artificial Intelligence (AI), and the Nature of Autonomy.Paul Formosa - 2021 - Minds and Machines 31 (4):595-616.
    Social robots are robots that can interact socially with humans. As social robots and the artificial intelligence that powers them becomes more advanced, they will likely take on more social and work roles. This has many important ethical implications. In this paper, we focus on one of the most central of these, the impacts that social robots can have on human autonomy. We argue that, due to their physical presence and social capacities, there is a strong potential for social robots (...)
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  40. Lethal Autonomous Weapons: Re-Examining the Law and Ethics of Robotic Warfare.Jai Galliott, Duncan MacIntosh & Jens David Ohlin (eds.) - 2021 - New York: Oxford University Press.
    The question of whether new rules or regulations are required to govern, restrict, or even prohibit the use of autonomous weapon systems has been the subject of debate for the better part of a decade. Despite the claims of advocacy groups, the way ahead remains unclear since the international community has yet to agree on a specific definition of Lethal Autonomous Weapon Systems and the great powers have largely refused to support an effective ban. In this vacuum, the public has (...)
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  41. Correctness and Completeness of Programming Instructions for Traffic Circulation.Daniela Glavaničová & Matteo Pascucci - 2021 - Science and Engineering Ethics 27 (6):1-16.
    In the present article we exploit the logical notions of correctness and completeness to provide an analysis of some fundamental problems that can be encountered by a software developer when transforming norms for traffic circulation into programming instructions. Relying on this analysis, we then introduce a question and answer procedure that can be helpful, in case of an accident, to clarify which components of an existing framework should be revised and to what extent software developers can be held responsible.
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  42. Raising Ethical Machines: Bottom-Up Methods to Implementing Machine Ethics.Marten H. L. Kaas - 2021 - In Steven John Thompson (ed.), Machine Law, Ethics, and Morality in the Age of Artificial Intelligence. IGI Global. pp. 47-68.
    The ethical decision-making and behaviour of artificially intelligent systems is increasingly important given the prevalence of these systems and the impact they can have on human well-being. Many current approaches to implementing machine ethics utilize top-down approaches, that is, ensuring the ethical decision-making and behaviour of an agent via its adherence to explicitly defined ethical rules or principles. Despite the attractiveness of this approach, this chapter explores how all top-down approaches to implementing machine ethics are fundamentally limited and how bottom-up (...)
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  43. The Use and Misuse of Counterfactuals in Ethical Machine Learning.Atoosa Kasirzadeh & Andrew Smart - 2021 - In ACM Conference on Fairness, Accountability, and Transparency (FAccT 21).
    The use of counterfactuals for considerations of algorithmic fairness and explainability is gaining prominence within the machine learning community and industry. This paper argues for more caution with the use of counterfactuals when the facts to be considered are social categories such as race or gender. We review a broad body of papers from philosophy and social sciences on social ontology and the semantics of counterfactuals, and we conclude that the counterfactual approach in machine learning fairness and social explainability can (...)
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  44. Osaammeko rakentaa moraalisia toimijoita?Antti Kauppinen - 2021 - In Panu Raatikainen (ed.), Tekoäly, ihminen ja yhteiskunta.
    Jotta olisimme moraalisesti vastuussa teoistamme, meidän on kyettävä muodostamaan käsityksiä oikeasta ja väärästä ja toimimaan ainakin jossain määrin niiden mukaisesti. Jos olemme täysivaltaisia moraalitoimijoita, myös ymmärrämme miksi jotkin teot ovat väärin, ja kykenemme siten joustavasti mukauttamaan toimintaamme eri tilanteisiin. Esitän, ettei näköpiirissä ole tekoälyjärjestelmiä, jotka kykenisivät aidosti välittämään oikein tekemisestä tai ymmärtämään moraalin vaatimuksia, koska nämä kyvyt vaativat kokemustietoisuutta ja kokonaisvaltaista arvostelukykyä. Emme siten voi sysätä koneille vastuuta teoistaan. Meidän on sen sijaan pyrittävä rakentamaan keinotekoisia oikeintekijöitä - järjestelmiä, jotka eivät (...)
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  45. Combating Disinformation with AI: Epistemic and Ethical Challenges.Benjamin Lange & Ted Lechterman - 2021 - IEEE International Symposium on Ethics in Engineering, Science and Technology (ETHICS) 1:1-5.
    AI-supported methods for identifying and combating disinformation are progressing in their development and application. However, these methods face a litany of epistemic and ethical challenges. These include (1) robustly defining disinformation, (2) reliably classifying data according to this definition, and (3) navigating ethical risks in the deployment of countermeasures, which involve a mixture of harms and benefits. This paper seeks to expose and offer preliminary analysis of these challenges.
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  46. Artificial Moral Agents Within an Ethos of AI4SG.Bongani Andy Mabaso - 2021 - Philosophy and Technology 34 (1):7-21.
    As artificial intelligence (AI) continues to proliferate into every area of modern life, there is no doubt that society has to think deeply about the potential impact, whether negative or positive, that it will have. Whilst scholars recognise that AI can usher in a new era of personal, social and economic prosperity, they also warn of the potential for it to be misused towards the detriment of society. Deliberate strategies are therefore required to ensure that AI can be safely integrated (...)
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  47. Kantian Moral Agency and the Ethics of Artificial Intelligence.Riya Manna & Rajakishore Nath - 2021 - Problemos 100:139-151.
    This paper discusses the philosophical issues pertaining to Kantian moral agency and artificial intelligence. Here, our objective is to offer a comprehensive analysis of Kantian ethics to elucidate the non-feasibility of Kantian machines. Meanwhile, the possibility of Kantian machines seems to contend with the genuine human Kantian agency. We argue that in machine morality, ‘duty’ should be performed with ‘freedom of will’ and ‘happiness’ because Kant narrated the human tendency of evaluating our ‘natural necessity’ through ‘happiness’ as the end. Lastly, (...)
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  48. The Problem Of Moral Agency In Artificial Intelligence.Riya Manna & Rajakishore Nath - 2021 - 2021 IEEE Conference on Norbert Wiener in the 21st Century (21CW).
    Humans have invented intelligent machinery to enhance their rational decision-making procedure, which is why it has been named ‘augmented intelligence’. The usage of artificial intelligence (AI) technology is increasing enormously with every passing year, and it is becoming a part of our daily life. We are using this technology not only as a tool to enhance our rationality but also heightening them as the autonomous ethical agent for our future society. Norbert Wiener envisaged ‘Cybernetics’ with a view of a brain-machine (...)
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  49. Emergent Models for Moral AI Spirituality.Graves Mark - 2021 - International Journal of Interactive Multimedia and Artificial Intelligence 7 (1):7-15.
    Examining AI spirituality can illuminate problematic assumptions about human spirituality and AI cognition, suggest possible directions for AI development, reduce uncertainty about future AI, and yield a methodological lens sufficient to investigate human-AI sociotechnical interaction and morality. Incompatible philosophical assumptions about human spirituality and AI limit investigations of both and suggest a vast gulf between them. An emergentist approach can replace dualist assumptions about human spirituality and identify emergent behavior in AI computation to overcome overly reductionist assumptions about computation. Using (...)
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  50. Faire la morale aux robots.Gibert Martin - 2021 - Paris: Flammarion.
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