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  1. 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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  2. 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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  3. 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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  4. The Moral Impermissibility of Creating Artificial Intelligence.Matt Schuler - manuscript
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  5. 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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  6. 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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  7. 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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  8. 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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  9. Conscience: The Mechanism of Morality.Jeffrey White - manuscript
    Conscience is oft-referred to yet not understood. This text develops a theory of cognition around a model of conscience, the ACTWith model. It represents a synthesis of results from contemporary neuroscience with traditional philosophy, building from Jamesian insights into the emergence of the self to narrative identity, all the while motivated by a single mechanism as represented in the ACTWith model. Emphasis is placed on clarifying historical expressions and demonstrations of conscience - Socrates, Heidegger, Kant, M.L. King - in light (...)
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  10. ОТВЕТСТВЕННЫЙ ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ: ВВЕДЕНИЕ «КОЧЕВЫЕ ПРИНЦИПЫ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА» ДЛЯ ЦЕНТРАЛЬНОЙ АЗИИ.Ammar Younas - manuscript
    Мы предлагаем, чтобы Центральная Азия разработала свои собственные принципы этики ИИ, которые мы предлагаем назвать “кочевыми принципами ИИ”.
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  11. 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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  12. Varieties of Transparency: Exploring Agency Within AI Systems.Gloria Andrada, Robert William Clowes & Paul Smart - forthcoming - AI and Society:1-11.
    AI systems play an increasingly important role in shaping and regulating the lives of millions of human beings across the world. Calls for greater transparency from such systems have been widespread. However, there is considerable ambiguity concerning what “transparency” actually means, and therefore, what greater transparency might entail. While, according to some debates, transparency requires seeing through the artefact or device, widespread calls for transparency imply seeing into different aspects of AI systems. These two notions are in apparent tension with (...)
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  13. Online Extremism, AI, and (Human) Content Moderation.Michael Randall Barnes - forthcoming - Feminist Philosophy Quarterly.
    This paper has 3 main goals: (1) to clarify the role of Artificial Intelligence (AI)—along with algorithms more broadly—in online radicalization that results in ‘real world violence’; (2) to argue that technological solutions (like better AI) are inadequate proposals for this problem given both technical and social reasons; and (3) to demonstrate that platform companies’ (e.g., Meta, Google) statements of preference for technological solutions functions as a type of propaganda that serves to erase the work of the thousands of human (...)
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  14. 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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  15. 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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  16. Ethical Assurance: A Practical Approach to the Responsible Design, Development, and Deployment of Data-Driven Technologies.Christopher Burr & David Leslie - forthcoming - AI and Ethics.
    This article offers several contributions to the interdisciplinary project of responsible research and innovation in data science and AI. First, it provides a critical analysis of current efforts to establish practical mechanisms for algorithmic auditing and assessment to identify limitations and gaps with these approaches. Second, it provides a brief introduction to the methodology of argument-based assurance and explores how it is currently being applied in the development of safety cases for autonomous and intelligent systems. Third, it generalises this method (...)
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  17. 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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  18. Just Machines.Clinton Castro - forthcoming - Public Affairs Quarterly.
    A number of findings in the field of machine learning have given rise to questions about what it means for automated scoring- or decisionmaking systems to be fair. One center of gravity in this discussion is whether such systems ought to satisfy classification parity (which requires parity in accuracy across groups, defined by protected attributes) or calibration (which requires similar predictions to have similar meanings across groups, defined by protected attributes). Central to this discussion are impossibility results, owed to Kleinberg (...)
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  19. Sims and Vulnerability: On the Ethics of Creating Emulated Minds.Bartek Chomanski - forthcoming - Science and Engineering Ethics.
    It might become possible to build artificial minds with the capacity for experience. This raises a plethora of ethical issues, explored, among others, in the context of whole brain emulations (WBE). In this paper, I will take up the problem of vulnerability – given, for various reasons, less attention in the literature – that the conscious emulations will likely exhibit. Specifically, I will examine the role that vulnerability plays in generating ethical issues that may arise when dealing with WBEs. I (...)
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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. 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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  26. 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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  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. Learning to Discriminate: The Perfect Proxy Problem in Artificially Intelligent Criminal Sentencing.Benjamin Davies & Thomas Douglas - forthcoming - In Jesper Ryberg & Julian V. Roberts (eds.), Sentencing and Artificial Intelligence. Oxford: Oxford University Press.
    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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  31. 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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  32. Understanding, Idealization, and Explainable AI.Will Fleisher - forthcoming - Episteme:1-27.
    Many AI systems that make important decisions are black boxes: how they function is opaque even to their developers. This is due to their high complexity and to the fact that they are trained rather than programmed. Efforts to alleviate the opacity of black box systems are typically discussed in terms of transparency, interpretability, and explainability. However, there is little agreement about what these key concepts mean, which makes it difficult to adjudicate the success or promise of opacity alleviation methods. (...)
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  33. Understanding Sophia? On human interaction with artificial agents.Thomas Fuchs - forthcoming - Phenomenology and the Cognitive Sciences:1-22.
    Advances in artificial intelligence create an increasing similarity between the performance of AI systems or AI-based robots and human communication. They raise the questions: whether it is possible to communicate with, understand, and even empathically perceive artificial agents; whether we should ascribe actual subjectivity and thus quasi-personal status to them beyond a certain level of simulation; what will be the impact of an increasing dissolution of the distinction between simulated and real encounters. To answer these questions, the paper argues that (...)
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  34. Trustworthy Medical AI Systems Need to Know When They Don’T Know.Thomas Grote - forthcoming - Journal of Medical Ethics.
    There is much to learn from Durán and Jongsma’s paper.1 One particularly important insight concerns the relationship between epistemology and ethics in medical artificial intelligence. In clinical environments, the task of AI systems is to provide risk estimates or diagnostic decisions, which then need to be weighed by physicians. Hence, while the implementation of AI systems might give rise to ethical issues—for example, overtreatment, defensive medicine or paternalism2—the issue that lies at the heart is an epistemic problem: how can physicians (...)
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  35. Diachronic and Synchronic Variation in the Performance of Adaptive Machine Learning Systems: The Ethical Challenges.Joshua Hatherley & Robert Sparrow - forthcoming - Journal of the American Medical Informatics Association.
    Objectives: Machine learning (ML) has the potential to facilitate “continual learning” in medicine, in which an ML system continues to evolve in response to exposure to new data over time, even after being deployed in a clinical setting. In this article, we provide a tutorial on the range of ethical issues raised by the use of such “adaptive” ML systems in medicine that have, thus far, been neglected in the literature. -/- Target audience: The target audiences for this tutorial are (...)
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  36. The Virtues of Interpretable Medical Artificial Intelligence.Joshua Hatherley, Robert Sparrow & Mark Howard - forthcoming - Cambridge Quarterly of Healthcare Ethics.
    Artificial intelligence (AI) systems have demonstrated impressive performance across a variety of clinical tasks. However, notoriously, sometimes these systems are 'black boxes'. The initial response in the literature was a demand for 'explainable AI'. However, recently, several authors have suggested that making AI more explainable or 'interpretable' is likely to be at the cost of the accuracy of these systems and that prioritising interpretability in medical AI may constitute a 'lethal prejudice'. In this paper, we defend the value of interpretability (...)
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  37. 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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  38. Against “Democratizing AI”.Johannes Himmelreich - forthcoming - AI and Society:1-14.
    This paper argues against the call to democratize artificial intelligence. Several authors demand to reap purported benefits that rest in direct and broad participation: In the governance of AI, more people should be more involved in more decisions about AI—from development and design to deployment. This paper opposes this call. The paper presents five objections against broadening and deepening public participation in the governance of AI. The paper begins by reviewing the literature and carving out a set of claims that (...)
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  39. Ethics of Artificial Intelligence in Brain and Mental Health.Marcello Ienca & Fabrice Jotterand (eds.) - forthcoming
  40. 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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  41. (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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  42. 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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  43. The Concept of Accountability in AI Ethics and Governance.Theodore M. Lechterman - forthcoming - In Justin Bullock, Y. C. Chen, Johannes Himmelreich, V. Hudson, M. Korinek, M. Young & B. Zhang (eds.), The Oxford Handbook of AI Governance. Oxford: Oxford University Press.
    Calls to hold artificial intelligence to account are intensifying. Activists and researchers alike warn of an “accountability gap” or even a “crisis of accountability” in AI. Meanwhile, several prominent scholars maintain that accountability holds the key to governing AI. But usage of the term varies widely in discussions of AI ethics and governance. This chapter begins by disambiguating some different senses and dimensions of accountability, distinguishing it from neighboring concepts, and identifying sources of confusion. It proceeds to explore the idea (...)
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  44. 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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  45. The Patient Preference Predictor and the Objection From Higher-Order Preferences.Jakob Thrane Mainz - forthcoming - Journal of Medical Ethics.
    Recently, Jardas et al have convincingly defended the patient preference predictor (PPP) against a range of autonomy-based objections. In this response, I propose a new autonomy-based objection to the PPP that is not explicitly discussed by Jardas et al. I call it the ’objection from higher-order preferences’. Even if this objection is not sufficient reason to reject the PPP, the objection constitutes a pro tanto reason that is at least as powerful as the ones discussed by Jardas et al.
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  46. Why Algorithmic Speed Can Be More Important Than Algorithmic Accuracy.Jakob Mainz, Lauritz Munch, Jens Christian Bjerring & Godtfredsen Sissel - forthcoming - Clinical Ethics.
    Artificial Intelligence (AI) often outperforms human doctors in terms of decisional speed. For some diseases, the expected benefit of a fast but less accurate decision exceeds the benefit of a slow but more accurate one. In such cases, we argue, it is often justified to rely on a medical AI to maximize decision speed – even if the AI is less accurate than human doctors.
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  47. African Reasons Why AI Should Not Maximize Utility (Repr.).Thaddeus Metz - forthcoming - In Aribiah Attoe, Samuel Segun, Victor Nweke & John-Bosco Umezurike (eds.), Conversations on African Philosophy of Mind, Consciousness and AI. Springer.
    Reprint of a chapter first appearing in African Values, Ethics, and Technology: Questions, Issues, and Approaches (2021).
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  48. Explainable AI Lacks Regulative Reasons: Why AI and Human Decision‑Making Are Not Equally Opaque.Uwe Peters - forthcoming - AI and Ethics.
    Many artificial intelligence (AI) systems currently used for decision-making are opaque, i.e., the internal factors that determine their decisions are not fully known to people due to the systems’ computational complexity. In response to this problem, several researchers have argued that human decision-making is equally opaque and since simplifying, reason-giving explanations (rather than exhaustive causal accounts) of a decision are typically viewed as sufficient in the human case, the same should hold for algorithmic decision-making. Here, I contend that this argument (...)
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  49. 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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  50. 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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