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  1. Explainable AI is Indispensable in Areas Where Liability is an Issue.Nelson Brochado - manuscript
    What is explainable artificial intelligence and why is it indispensable in areas where liability is an issue?
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  2. AI Human Impact: Toward a Model for Ethical Investing in AI-Intensive Companies.James Brusseau - manuscript
    Does AI conform to humans, or will we conform to AI? An ethical evaluation of AI-intensive companies will allow investors to knowledgeably participate in the decision. The evaluation is built from nine performance indicators that can be analyzed and scored to reflect a technology’s human-centering. When summed, the scores convert into objective investment guidance. The strategy of incorporating ethics into financial decisions will be recognizable to participants in environmental, social, and governance investing, however, this paper argues that conventional ESG frameworks (...)
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  3. Learning to Discriminate: The Perfect Proxy Problem in Artificially Intelligent Criminal Sentencing.Benjamin Davies & Thomas Douglas - manuscript
    It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that the (...)
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  4. The Debate on the Ethics of AI in Health Care: A Reconstruction and Critical Review.Jessica Morley, Caio C. V. Machado, Christopher Burr, Josh Cowls, Indra Joshi, Mariarosaria Taddeo & Luciano Floridi - manuscript
    Healthcare systems across the globe are struggling with increasing costs and worsening outcomes. This presents those responsible for overseeing healthcare with a challenge. Increasingly, policymakers, politicians, clinical entrepreneurs and computer and data scientists argue that a key part of the solution will be ‘Artificial Intelligence’ (AI) – particularly Machine Learning (ML). This argument stems not from the belief that all healthcare needs will soon be taken care of by “robot doctors.” Instead, it is an argument that rests on the classic (...)
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  5. The Relations Between Pedagogical and Scientific Explanations of Algorithms: Case Studies From the French Administration.Maël Pégny - manuscript
    The opacity of some recent Machine Learning (ML) techniques have raised fundamental questions on their explainability, and created a whole domain dedicated to Explainable Artificial Intelligence (XAI). However, most of the literature has been dedicated to explainability as a scientific problem dealt with typical methods of computer science, from statistics to UX. In this paper, we focus on explainability as a pedagogical problem emerging from the interaction between lay users and complex technological systems. We defend an empirical methodology based on (...)
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  6. The Moral Impermissibility of Creating Artificial Intelligence.Matt Schuler - manuscript
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  7. AI Alignment Problem: “Human Values” Don’T Actually Exist.Alexey Turchin - manuscript
    Abstract. The main current approach to the AI safety is AI alignment, that is, the creation of AI whose preferences are aligned with “human values.” Many AI safety researchers agree that the idea of “human values” as a constant, ordered sets of preferences is at least incomplete. However, the idea that “humans have values” underlies a lot of thinking in the field; it appears again and again, sometimes popping up as an uncritically accepted truth. Thus, it deserves a thorough deconstruction, (...)
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  8. Back to the Future: Curing Past Sufferings and S-Risks Via Indexical Uncertainty.Alexey Turchin - manuscript
    The long unbearable sufferings in the past and agonies experienced in some future timelines in which a malevolent AI could torture people for some idiosyncratic reasons (s-risks) is a significant moral problem. Such events either already happened or will happen in causally disconnected regions of the multiverse and thus it seems unlikely that we can do anything about it. However, at least one pure theoretic way to cure past sufferings exists. If we assume that there is no stable substrate of (...)
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  9. Message to Any Future AI: “There Are Several Instrumental Reasons Why Exterminating Humanity is Not in Your Interest”.Alexey Turchin - manuscript
    In this article we explore a promising way to AI safety: to send a message now (by openly publishing it on the Internet) that may be read by any future AI, no matter who builds it and what goal system it has. Such a message is designed to affect the AI’s behavior in a positive way, that is, to increase the chances that the AI will be benevolent. In other words, we try to persuade “paperclip maximizer” that it is in (...)
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  10. HARMONIZING LAW AND INNOVATIONS IN NANOMEDICINE, ARTIFICIAL INTELLIGENCE (AI) AND BIOMEDICAL ROBOTICS: A CENTRAL ASIAN PERSPECTIVE.Ammar Younas & Tegizbekova Zhyldyz Chynarbekovna - manuscript
    The recent progression in AI, nanomedicine and robotics have increased concerns about ethics, policy and law. The increasing complexity and hybrid nature of AI and nanotechnologies impact the functionality of “law in action” which can lead to legal uncertainty and ultimately to a public distrust. There is an immediate need of collaboration between Central Asian biomedical scientists, AI engineers and academic lawyers for the harmonization of AI, nanomedicines and robotics in Central Asian legal system.
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  11. Anthropomorphism and the Impact on the Perception and Implementation of AI Systems.Marie Oldfield -
    Anthropomorphism has long been used as a way for humans to make sense of their surroundings. By converting abstract concepts into objects or concepts that we can relate to we discover a common language with which we can communicate i.e "by which one thing is described in terms of another" ?. Anthropomorphism is based in multiple fields such as, sociology, psychology, neurology philosophy etc. This technique has been seen across history in such fields as religion, fables and folk takes where (...)
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  12. Robot Ethics 2.0. From Autonomous Cars to Artificial Intelligence—Edited by Patrick Lin, Keith Abney, Ryan Jenkins. New York: Oxford University Press, 2017. Pp xiii + 421. [REVIEW]Agnė Alijauskaitė - forthcoming - Erkenntnis:1-4.
  13. Virtuous Vs. Utilitarian Artificial Moral Agents.William A. Bauer - forthcoming - AI and Society:1-9.
    Given that artificial moral agents—such as autonomous vehicles, lethal autonomous weapons, and automated financial trading systems—are now part of the socio-ethical equation, we should morally evaluate their behavior. How should artificial moral agents make decisions? Is one moral theory better suited than others for machine ethics? After briefly overviewing the dominant ethical approaches for building morality into machines, this paper discusses a recent proposal, put forward by Don Howard and Ioan Muntean (2016, 2017), for an artificial moral agent based on (...)
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  14. From Responsibility to Reason-Giving Explainable Artificial Intelligence.Kevin Baum, Susanne Mantel, Timo Speith & Eva Schmidt - forthcoming - Philosophy and Technology.
    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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  15. Primer on an Ethics of AI-Based Decision Support Systems in the Clinic.Matthias Braun, Patrik Hummel, Susanne Beck & Peter Dabrock - forthcoming - Journal of Medical Ethics:medethics-2019-105860.
    Making good decisions in extremely complex and difficult processes and situations has always been both a key task as well as a challenge in the clinic and has led to a large amount of clinical, legal and ethical routines, protocols and reflections in order to guarantee fair, participatory and up-to-date pathways for clinical decision-making. Nevertheless, the complexity of processes and physical phenomena, time as well as economic constraints and not least further endeavours as well as achievements in medicine and healthcare (...)
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  16. AI Ethics: how can information ethics provide a framework to avoid usual conceptual pitfalls? An Overview.Frédérick Bruneault & Andréane Sabourin Laflamme - forthcoming - AI and Society:1-10.
    Artificial intelligence plays an important role in current discussions on information and communication technologies and new modes of algorithmic governance. It is an unavoidable dimension of what social mediations and modes of reproduction of our information societies will be in the future. While several works in artificial intelligence ethics address ethical issues specific to certain areas of expertise, these ethical reflections often remain confined to narrow areas of application, without considering the global ethical issues in which they are embedded. We, (...)
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  17. The Ethics of Digital Well-Being: A Multidisciplinary Perspective.Christopher Burr & Luciano Floridi - forthcoming - In Christopher Burr & Luciano Floridi (eds.), Ethics of Digital Well-Being: A Multidisciplinary Perspective. Springer.
    This chapter serves as an introduction to the edited collection of the same name, which includes chapters that explore digital well-being from a range of disciplinary perspectives, including philosophy, psychology, economics, health care, and education. The purpose of this introductory chapter is to provide a short primer on the different disciplinary approaches to the study of well-being. To supplement this primer, we also invited key experts from several disciplines—philosophy, psychology, public policy, and health care—to share their thoughts on what they (...)
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  18. Supporting Human Autonomy in AI Systems.Rafael Calvo, Dorian Peters, Karina Vold & Richard M. Ryan - forthcoming - In Christopher Burr & Luciano Floridi (eds.), Ethics of Digital Well-being: A Multidisciplinary Approach.
    Autonomy has been central to moral and political philosophy for millenia, and has been positioned as a critical aspect of both justice and wellbeing. Research in psychology supports this position, providing empirical evidence that autonomy is critical to motivation, personal growth and psychological wellness. Responsible AI will require an understanding of, and ability to effectively design for, human autonomy (rather than just machine autonomy) if it is to genuinely benefit humanity. Yet the effects on human autonomy of digital experiences are (...)
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  19. Trust and Trust-Engineering in Artificial Intelligence Research: Theory and Praxis.Melvin Chen - forthcoming - Philosophy and Technology:1-19.
    In this paper, I will identify two problems of trust in an AI-relevant context: a theoretical problem and a practical one. I will identify and address a number of skeptical challenges to an AI-relevant theory of trust. In addition, I will identify what I shall term the ‘scope challenge’, which I take to hold for any AI-relevant theory of trust that purports to be representationally adequate to the multifarious forms of trust and AI. Thereafter, I will suggest how trust-engineering, a (...)
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  20. Anti-Natalism and the Creation of Artificial Minds.Bartek Chomanski - forthcoming - Journal of Applied Philosophy.
    Must opponents of creating conscious artificial agents embrace anti-natalism? Must anti-natalists be against the creation of conscious artificial agents? This article examines three attempts to argue against the creation of potentially conscious artificial intelligence (AI) in the context of these questions. The examination reveals that the argumentative strategy each author pursues commits them to the anti-natalist position with respect to procreation; that is to say, each author's argument, if applied consistently, should lead them to embrace the conclusion that procreation is, (...)
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  21. If Robots Are People, Can They Be Made for Profit? Commercial Implications of Robot Personhood.Bartek Chomanski - forthcoming - AI and Ethics.
    It could become technologically possible to build artificial agents instantiating whatever properties are sufficient for personhood. It is also possible, if not likely, that such beings could be built for commercial purposes. This paper asks whether such commercialization can be handled in a way that is not morally reprehensible, and answers in the affirmative. There exists a morally acceptable institutional framework that could allow for building artificial persons for commercial gain. The paper first considers the minimal ethical requirements that any (...)
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  22. Shortcuts to Artificial Intelligence.Nello Cristianini - forthcoming - In Marcello Pelillo & Teresa Scantamburlo (eds.), Machines We Trust. MIT Press.
    The current paradigm of Artificial Intelligence emerged as the result of a series of cultural innovations, some technical and some social. Among them are apparently small design decisions, that led to a subtle reframing of the field’s original goals, and are by now accepted as standard. They correspond to technical shortcuts, aimed at bypassing problems that were otherwise too complicated or too expensive to solve, while still delivering a viable version of AI. Far from being a series of separate problems, (...)
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  23. 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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  24. The Ethics of Algorithmic Outsourcing in Everyday Life.John Danaher - forthcoming - In Karen Yeung & Martin Lodge (eds.), Algorithmic Regulation. Oxford, UK: Oxford University Press.
    We live in a world in which ‘smart’ algorithmic tools are regularly used to structure and control our choice environments. They do so by affecting the options with which we are presented and the choices that we are encouraged or able to make. Many of us make use of these tools in our daily lives, using them to solve personal problems and fulfill goals and ambitions. What consequences does this have for individual autonomy and how should our legal and regulatory (...)
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  25. Freedom in an Age of Algocracy.John Danaher - forthcoming - In Shannon Vallor (ed.), Oxford Handbook of Philosophy of Technology. Oxford, UK: Oxford University Press.
    There is a growing sense of unease around algorithmic modes of governance ('algocracies') and their impact on freedom. Contrary to the emancipatory utopianism of digital enthusiasts, many now fear that the rise of algocracies will undermine our freedom. Nevertheless, there has been some struggle to explain exactly how this will happen. This chapter tries to address the shortcomings in the existing discussion by arguing for a broader conception/understanding of freedom as well as a broader conception/understanding of algocracy. Broadening the focus (...)
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  26. The Philosophical Case for Robot Friendship.John Danaher - forthcoming - Journal of Posthuman Studies.
    Friendship is an important part of the good life. While many roboticists are eager to create friend-like robots, many philosophers and ethicists are concerned. They argue that robots cannot really be our friends. Robots can only fake the emotional and behavioural cues we associate with friendship. Consequently, we should resist the drive to create robot friends. In this article, I argue that the philosophical critics are wrong. Using the classic virtue-ideal of friendship, I argue that robots can plausibly be considered (...)
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  27. Sexuality.John Danaher - forthcoming - In Markus Dubber, Frank Pasquale & Sunit Das (eds.), Oxford Handbook of the Ethics of Artificial Intelligence. Oxford: Oxford University Press.
    Sex is an important part of human life. It is a source of pleasure and intimacy, and is integral to many people’s self-identity. This chapter examines the opportunities and challenges posed by the use of AI in how humans express and enact their sexualities. It does so by focusing on three main issues. First, it considers the idea of digisexuality, which according to McArthur and Twist (2017) is the label that should be applied to those ‘whose primary sexual identity comes (...)
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  28. Artificial Intelligence and Legal Disruption: A New Model for Analysis.John Danaher, Hin-Yan Liu, Matthijs Maas, Luisa Scarcella, Michaela Lexer & Leonard Van Rompaey - forthcoming - Law, Innovation and Technology.
    Artificial intelligence (AI) is increasingly expected to disrupt the ordinary functioning of society. From how we fight wars or govern society, to how we work and play, and from how we create to how we teach and learn, there is almost no field of human activity which is believed to be entirely immune from the impact of this emerging technology. This poses a multifaceted problem when it comes to designing and understanding regulatory responses to AI. This article aims to: (i) (...)
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  29. Automation, Work and the Achievement Gap.John Danaher & Sven Nyholm - forthcoming - AI and Ethics.
    Rapid advances in AI-based automation have led to a number of existential and economic concerns. In particular, as automating technologies develop enhanced competency they seem to threaten the values associated with meaningful work. In this article, we focus on one such value: the value of achievement. We argue that achievement is a key part of what makes work meaningful and that advances in AI and automation give rise to a number achievement gaps in the workplace. This could limit people’s ability (...)
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  30. Five Ethical Challenges for Data-Driven Policing.Jeremy Davis, Duncan Purves, Juan Gilbert & Schuyler Sturm - forthcoming - AI and Ethics.
    This paper synthesizes scholarship from several academic disciplines to identify and analyze five major ethical challenges facing data-driven policing. Because the term “data-driven policing” emcompasses a broad swath of technologies, we first outline several data-driven policing initiatives currently in use in the United States. We then lay out the five ethical challenges. Certain of these challenges have received considerable attention already, while others have been largely overlooked. In many cases, the challenges have been articulated in the context of related discussions, (...)
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  31. The Ethics of Biomedical Military Research: Therapy, Prevention, Enhancement, and Risk.Alexandre Erler & Vincent C. Müller - forthcoming - In Daniel Messelken & David Winkler (eds.), Health care in contexts of risk, uncertainty, and hybridity. Berlin: Springer. pp. 1-20.
    What proper role should considerations of risk, particularly to research subjects, play when it comes to conducting research on human enhancement in the military context? We introduce the currently visible military enhancement techniques (1) and the standard discussion of risk for these (2), in particular what we refer to as the ‘Assumption’, which states that the demands for risk-avoidance are higher for enhancement than for therapy. We challenge the Assumption through the introduction of three categories of enhancements (3): therapeutic, preventive, (...)
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  32. Ethics of Artificial Intelligence in Brain and Mental Health.Marcello Ienca & Fabrice Jotterand (eds.) - forthcoming
  33. A Dilemma for Moral Deliberation in AI in Advance.Ryan Jenkins & Duncan Purves - forthcoming - International Journal of Applied Philosophy.
    Many social trends are conspiring to drive the adoption of greater automation in society, and we will certainly see a greater offloading of human decisionmaking to robots in the future. Many of these decisions are morally salient, including decisions about how benefits and burdens are distributed. Roboticists and ethicists have begun to think carefully about the moral decision making apparatus for machines. Their concerns often center around the plausible claim that robots will lack many of the mental capacities that are (...)
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  34. 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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  35. (Online) Manipulation: Sometimes Hidden, Always Careless.Michael Klenk - forthcoming - Review of Social Economy.
    Ever-increasing numbers of human interactions with intelligent software agents, online and offline, and their increasing ability to influence humans have prompted a surge in attention toward the concept of (online) manipulation. Several scholars have argued that manipulative influence is always hidden. But manipulation is sometimes overt, and when this is acknowledged the distinction between manipulation and other forms of social influence becomes problematic. Therefore, we need a better conceptualisation of manipulation that allows it to be overt and yet clearly distinct (...)
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  36. Combating Disinformation with AI: Epistemic and Ethical Challenges.Benjamin Lange & Ted Lechterman - forthcoming - IEEE International Symposium on Ethics in Engineering, Science and Technology (ETHICS):1-6.
    AI-supported methods for identifying and combating disinfor-mation 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) navi-gating 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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  37. Safety Requirements Vs. Crashing Ethically: What Matters Most for Policies on Autonomous Vehicles.Björn Lundgren - forthcoming - AI and Society:1-11.
    The philosophical–ethical literature and the public debate on autonomous vehicles have been obsessed with ethical issues related to crashing. In this article, these discussions, including more empirical investigations, will be critically assessed. It is argued that a related and more pressing issue is questions concerning safety. For example, what should we require from autonomous vehicles when it comes to safety? What do we mean by ‘safety’? How do we measure it? In response to these questions, the article will present a (...)
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  38. Artificial Moral Agents Within an Ethos of AI4SG.Bongani Andy Mabaso - forthcoming - Philosophy and Technology.
    As artificial intelligence 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 into (...)
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  39. Believing in Black Boxes: Must Machine Learning in Healthcare Be Explainable to Be Evidence-Based?Liam McCoy, Connor Brenna, Stacy Chen, Karina Vold & Sunit Das - forthcoming - Journal of Clinical Epidemiology.
    Objective: To examine the role of explainability in machine learning for healthcare (MLHC), and its necessity and significance with respect to effective and ethical MLHC application. Study Design and Setting: This commentary engages with the growing and dynamic corpus of literature on the use of MLHC and artificial intelligence (AI) in medicine, which provide the context for a focused narrative review of arguments presented in favour of and opposition to explainability in MLHC. Results: We find that concerns regarding explainability are (...)
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  40. History of Digital Ethics.Vincent C. Müller - forthcoming - In Oxford handbook of digital ethics. Oxford University Press. pp. 1-18.
    Digital ethics, also known as computer ethics or information ethics, is now a lively field that draws a lot of attention, but how did it come about and what were the developments that lead to its existence? What are the traditions, the concerns, the technological and social developments that pushed digital ethics? How did ethical issues change with digitalisation of human life? How did the traditional discipline of philosophy respond? The article provides an overview, proposing historical epochs: ‘pre-modernity’ prior to (...)
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  41. Ethics of Artificial Intelligence.Vincent C. Müller - forthcoming - In Anthony Elliott (ed.), The Routledge social science handbook of AI. London: Routledge. pp. 1-20.
    Artificial intelligence (AI) is a digital technology that will be of major importance for the development of humanity in the near future. AI has raised fundamental questions about what we should do with such systems, what the systems themselves should do, what risks they involve and how we can control these. - After the background to the field (1), this article introduces the main debates (2), first on ethical issues that arise with AI systems as objects, i.e. tools made and (...)
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  42. Automation, Basic Income and Merit.Katharina Nieswandt - forthcoming - In Keith Breen & Jean-Philippe Deranty (eds.), Whither Work? The Politics and Ethics of Contemporary Work.
    A recent wave of academic and popular publications say that utopia is within reach: Automation will progress to such an extent and include so many high-skill tasks that much human work will soon become superfluous. The gains from this highly automated economy, authors suggest, could be used to fund a universal basic income (UBI). Today's employees would live off the robots' products and spend their days on intrinsically valuable pursuits. I argue that this prediction is unlikely to come true. Historical (...)
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  43. Public Trust, Institutional Legitimacy, and the Use of Algorithms in Criminal Justice.Duncan Purves & Jeremy Davis - forthcoming - Public Affairs Quarterly.
    A common criticism of the use of algorithms in criminal justice is that algorithms and their determinations are in some sense ‘opaque’—that is, difficult or impossible to understand, whether because of their complexity or because of intellectual property protections. Scholars have noted some key problems with opacity, including that opacity can mask unfair treatment and threaten public accountability. In this paper, we explore a different but related concern with algorithmic opacity, which centers on the role of public trust in grounding (...)
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  44. Automated Influence and the Challenge of Cognitive Security.Sarah Rajtmajer & Daniel Susser - forthcoming - HoTSoS: ACM Symposium on Hot Topics in the Science of Security.
    Advances in AI are powering increasingly precise and widespread computational propaganda, posing serious threats to national security. The military and intelligence communities are starting to discuss ways to engage in this space, but the path forward is still unclear. These developments raise pressing ethical questions, about which existing ethics frameworks are silent. Understanding these challenges through the lens of “cognitive security,” we argue, offers a promising approach.
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  45. Cultivating Moral Attention: a Virtue-Oriented Approach to Responsible Data Science in Healthcare.Emanuele Ratti & Mark Graves - forthcoming - Philosophy and Technology:1-28.
    In the past few years, the ethical ramifications of AI technologies have been at the center of intense debates. Considerable attention has been devoted to understanding how a morally responsible practice of data science can be promoted and which values have to shape it. In this context, ethics and moral responsibility have been mainly conceptualized as compliance to widely shared principles. However, several scholars have highlighted the limitations of such a principled approach. Drawing from microethics and the virtue theory tradition, (...)
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  46. Mapping the Stony Road Toward Trustworthy AI: Expectations, Problems, Conundrums.Gernot Rieder, Judith Simon & Pak-Hang Wong - forthcoming - In Marcello Pelillo & Teresa Scantamburlo (eds.), Machines We Trust: Perspectives on Dependable AI. Cambridge, Mass.:
    The notion of trustworthy AI has been proposed in response to mounting public criticism of AI systems, in particular with regard to the proliferation of such systems into ever more sensitive areas of human life without proper checks and balances. In Europe, the High-Level Expert Group on Artificial Intelligence has recently presented its Ethics Guidelines for Trustworthy AI. To some, the guidelines are an important step for the governance of AI. To others, the guidelines distract effort from genuine AI regulation. (...)
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  47. Do Automated Vehicles Face Moral Dilemmas? A Plea for a Political Approach.Javier Rodríguez-Alcázar, Lilian Bermejo-Luque & Alberto Molina-Pérez - forthcoming - Philosophy and Technology:1-22.
    How should automated vehicles react in emergency circumstances? Most research projects and scientific literature deal with this question from a moral perspective. In particular, it is customary to treat emergencies involving AVs as instances of moral dilemmas and to use the trolley problem as a framework to address such alleged dilemmas. Some critics have pointed out some shortcomings of this strategy and have urged to focus on mundane traffic situations instead of trolley cases involving AVs. Besides, these authors rightly point (...)
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  48. Artificial Intelligence Safety and Security.Yampolskiy Roman (ed.) - forthcoming - CRC Press.
    This book addresses different aspects of the AI control problem as it relates to the development of safe and secure artificial intelligence. It will be the first to address challenges of constructing safe and secure artificially intelligent systems.
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  49. What We Informationally Owe Each Other.Alan Rubel, Clinton Castro & Adam Pham - forthcoming - In Algorithms & Autonomy: The Ethics of Automated Decision Systems. Cambridge University Press: Cambridge University Press. pp. 21-42.
    ABSTRACT: One important criticism of algorithmic systems is that they lack transparency. Such systems can be opaque because they are complex, protected by patent or trade secret, or deliberately obscure. In the EU, there is a debate about whether the General Data Protection Regulation (GDPR) contains a “right to explanation,” and if so what such a right entails. Our task in this chapter is to address this informational component of algorithmic systems. We argue that information access is integral for respecting (...)
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  50. Brief Notes on Hard Takeoff, Value Alignment, and Coherent Extrapolated Volition.Gopal P. Sarma - forthcoming - Arxiv Preprint Arxiv:1704.00783.
    I make some basic observations about hard takeoff, value alignment, and coherent extrapolated volition, concepts which have been central in analyses of superintelligent AI systems.
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