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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. Good AI for the Present of Humanity Democratizing AI Governance.Nicholas Kluge Corrêa - manuscript
    What does Cyberpunk and AI Ethics have to do with each other? Cyberpunk is a sub-genre of science fiction that explores the post-human relationships between human experience and technology. One similarity between AI Ethics and Cyberpunk literature is that both seek a dialogue in which the reader may inquire about the future and the ethical and social problems that our technological advance may bring upon society. In recent years, an increasing number of ethical matters involving AI have been pointed and (...)
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  3. On Social Machines for Algorithmic Regulation.Nello Cristianini & Teresa Scantamburlo - manuscript
    Autonomous mechanisms have been proposed to regulate certain aspects of society and are already being used to regulate business organisations. We take seriously recent proposals for algorithmic regulation of society, and we identify the existing technologies that can be used to implement them, most of them originally introduced in business contexts. We build on the notion of 'social machine' and we connect it to various ongoing trends and ideas, including crowdsourced task-work, social compiler, mechanism design, reputation management systems, and social (...)
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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. Narrow AI Nanny: Reaching Strategic Advantage Via Narrow AI to Prevent Creation of the Dangerous Superintelligence.Alexey Turchin - manuscript
    Abstract: As there are no currently obvious ways to create safe self-improving superintelligence, but its emergence is looming, we probably need temporary ways to prevent its creation. The only way to prevent it is to create a special type of AI that is able to control and monitor the entire world. The idea has been suggested by Goertzel in the form of an AI Nanny, but his Nanny is still superintelligent, and is not easy to control. We explore here ways (...)
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  6. 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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  7. Levels of Self-Improvement in AI and Their Implications for AI Safety.Alexey Turchin - manuscript
    Abstract: This article presents a model of self-improving AI in which improvement could happen on several levels: hardware, learning, code and goals system, each of which has several sublevels. We demonstrate that despite diminishing returns at each level and some intrinsic difficulties of recursive self-improvement—like the intelligence-measuring problem, testing problem, parent-child problem and halting risks—even non-recursive self-improvement could produce a mild form of superintelligence by combining small optimizations on different levels and the power of learning. Based on this, we analyze (...)
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  8. 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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  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. 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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  11. Simulation Typology and Termination Risks.Alexey Turchin & Roman Yampolskiy - manuscript
    The goal of the article is to explore what is the most probable type of simulation in which humanity lives (if any) and how this affects simulation termination risks. We firstly explore the question of what kind of simulation in which humanity is most likely located based on pure theoretical reasoning. We suggest a new patch to the classical simulation argument, showing that we are likely simulated not by our own descendants, but by alien civilizations. Based on this, we provide (...)
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  12. Ethical Pitfalls for Natural Language Processing in Psychology.Mark Alfano, Emily Sullivan & Amir Ebrahimi Fard - forthcoming - In Morteza Dehghani & Ryan Boyd (eds.), The Atlas of Language Analysis in Psychology. Guilford Press.
    Knowledge is power. Knowledge about human psychology is increasingly being produced using natural language processing (NLP) and related techniques. The power that accompanies and harnesses this knowledge should be subject to ethical controls and oversight. In this chapter, we address the ethical pitfalls that are likely to be encountered in the context of such research. These pitfalls occur at various stages of the NLP pipeline, including data acquisition, enrichment, analysis, storage, and sharing. We also address secondary uses of the results (...)
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  13. 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.
  14. 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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  15. 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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  16. Inscrutable Processes: Algorithms, Agency, and Divisions of Deliberative Labour.Marinus Ferreira - forthcoming - Journal of Applied Philosophy.
    As the use of algorithmic decision‐making becomes more commonplace, so too does the worry that these algorithms are often inscrutable and our use of them is a threat to our agency. Since we do not understand why an inscrutable process recommends one option over another, we lose our ability to judge whether the guidance is appropriate and are vulnerable to being led astray. In response, I claim that a process being inscrutable does not automatically make its guidance inappropriate. This phenomenon (...)
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  17. Ethics of Artificial Intelligence in Brain and Mental Health.Marcello Ienca & Fabrice Jotterand (eds.) - forthcoming
  18. 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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  19. Who Should Bear the Risk When Self‐Driving Vehicles Crash?Antti Kauppinen - forthcoming - Journal of Applied Philosophy.
    The moral importance of liability to harm has so far been ignored in the lively debate about what self-driving vehicles should be programmed to do when an accident is inevitable. But liability matters a great deal to just distribution of risk of harm. While morality sometimes requires simply minimizing relevant harms, this is not so when one party is liable to harm in virtue of voluntarily engaging in activity that foreseeably creates a risky situation, while having reasonable alternatives. On plausible (...)
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  20. 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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  21. 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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  22. Machines Learning Values.Steve Petersen - forthcoming - In S. Matthew Liao (ed.), Ethics of Artificial Intelligence. New York, USA: Oxford University Press.
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  23. 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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  24. 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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  25. 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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  26. Designing AI for Explainability and Verifiability: A Value Sensitive Design Approach to Avoid Artificial Stupidity in Autonomous Vehicles.Steven Umbrello & Roman Yampolskiy - forthcoming - International Journal of Social Robotics:1-15.
    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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  27. Mapping Value Sensitive Design Onto AI for Social Good Principles.Steven Umbrello & Ibo van de Poel - 2021 - AI and Ethics 1:1-14.
    Value Sensitive Design (VSD) is an established method for integrating values into technical design. It has been applied to different technologies and, more recently, to artificial intelligence (AI). We argue that AI poses a number of challenges specific to VSD that require a somewhat modified VSD approach. Machine learning (ML), in particular, poses two challenges. First, humans may not understand how an AI system learns certain things. This requires paying attention to values such as transparency, explicability, and accountability. Second, ML (...)
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  28. Technologically scaffolded atypical cognition: The case of YouTube’s recommender system.Mark Alfano, Amir Ebrahimi Fard, J. Adam Carter, Peter Clutton & Colin Klein - 2020 - Synthese:1-24.
    YouTube has been implicated in the transformation of users into extremists and conspiracy theorists. The alleged mechanism for this radicalizing process is YouTube’s recommender system, which is optimized to amplify and promote clips that users are likely to watch through to the end. YouTube optimizes for watch-through for economic reasons: people who watch a video through to the end are likely to then watch the next recommended video as well, which means that more advertisements can be served to them. This (...)
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  29. Social choice ethics in artificial intelligence.Seth D. Baum - 2020 - AI and Society 35 (1):165-176.
    A major approach to the ethics of artificial intelligence is to use social choice, in which the AI is designed to act according to the aggregate views of society. This is found in the AI ethics of “coherent extrapolated volition” and “bottom–up ethics”. This paper shows that the normative basis of AI social choice ethics is weak due to the fact that there is no one single aggregate ethical view of society. Instead, the design of social choice AI faces three (...)
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  30. Digital Psychiatry: Ethical Risks and Opportunities for Public Health and Well-Being.Christopher Burr, Jessica Morley, Mariarosaria Taddeo & Luciano Floridi - 2020 - IEEE Transactions on Technology and Society 1 (1):21-33.
    Common mental health disorders are rising globally, creating a strain on public healthcare systems. This has led to a renewed interest in the role that digital technologies may have for improving mental health outcomes. One result of this interest is the development and use of artificial intelligence for assessing, diagnosing, and treating mental health issues, which we refer to as ‘digital psychiatry’. This article focuses on the increasing use of digital psychiatry outside of clinical settings, in the following sectors: education, (...)
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  31. Modelos Dinâmicos Aplicados à Aprendizagem de Valores em Inteligência Artificial.Nicholas Kluge Corrêa & Nythamar De Oliveira - 2020 - Veritas – Revista de Filosofia da Pucrs 2 (65):1-15.
    Experts in Artificial Intelligence (AI) development predict that advances in the development of intelligent systems and agents will reshape vital areas in our society. Nevertheless, if such an advance is not made prudently and critically-reflexively, it can result in negative outcomes for humanity. For this reason, several researchers in the area have developed a robust, beneficial, and safe concept of AI for the preservation of humanity and the environment. Currently, several of the open problems in the field of AI research (...)
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  32. Consequentialism & Machine Ethics: Towards a Foundational Machine Ethic to Ensure the Right Action of Artificial Moral Agents.Josiah Della Foresta - 2020 - Montreal AI Ethics Institute.
    In this paper, I argue that Consequentialism represents a kind of ethical theory that is the most plausible to serve as a basis for a machine ethic. First, I outline the concept of an artificial moral agent and the essential properties of Consequentialism. Then, I present a scenario involving autonomous vehicles to illustrate how the features of Consequentialism inform agent action. Thirdly, an alternative Deontological approach will be evaluated and the problem of moral conflict discussed. Finally, two bottom-up approaches to (...)
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  33. Kevin Macnish: The Ethics of Surveillance: An Introduction: Routledge, London and New York, 2018, ISBN 978-1138643796, $45.95.Tony Doyle - 2020 - Ethics and Information Technology 22 (1):39-42.
  34. Toward Implementing the ADC Model of Moral Judgment in Autonomous Vehicles.Veljko Dubljević - 2020 - Science and Engineering Ethics 26 (5):2461-2472.
    Autonomous vehicles —and accidents they are involved in—attest to the urgent need to consider the ethics of artificial intelligence. The question dominating the discussion so far has been whether we want AVs to behave in a ‘selfish’ or utilitarian manner. Rather than considering modeling self-driving cars on a single moral system like utilitarianism, one possible way to approach programming for AI would be to reflect recent work in neuroethics. The agent–deed–consequence model :3–20, 2014a, Behav Brain Sci 37:487–488, 2014b) provides a (...)
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  35. Towards Transparency by Design for Artificial Intelligence.Heike Felzmann, Eduard Fosch-Villaronga, Christoph Lutz & Aurelia Tamò-Larrieux - 2020 - Science and Engineering Ethics 26 (6):3333-3361.
    In this article, we develop the concept of Transparency by Design that serves as practical guidance in helping promote the beneficial functions of transparency while mitigating its challenges in automated-decision making environments. With the rise of artificial intelligence and the ability of AI systems to make automated and self-learned decisions, a call for transparency of how such systems reach decisions has echoed within academic and policy circles. The term transparency, however, relates to multiple concepts, fulfills many functions, and holds different (...)
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  36. The Immoral Machine.John Harris - 2020 - Cambridge Quarterly of Healthcare Ethics 29 (1):71-79.
    :In a recent paper in Nature1 entitled The Moral Machine Experiment, Edmond Awad, et al. make a number of breathtakingly reckless assumptions, both about the decisionmaking capacities of current so-called “autonomous vehicles” and about the nature of morality and the law. Accepting their bizarre premise that the holy grail is to find out how to obtain cognizance of public morality and then program driverless vehicles accordingly, the following are the four steps to the Moral Machinists argument:1)Find out what “public morality” (...)
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  37. Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions.Thomas C. King, Nikita Aggarwal, Mariarosaria Taddeo & Luciano Floridi - 2020 - Science and Engineering Ethics 26 (1):89-120.
    Artificial intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently (...)
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  38. Introduction to the Special Issue on the Ethics of State Mass Surveillance.Peter Königs - 2020 - Moral Philosophy and Politics 7 (1):1-8.
    Recent decades have seen an unprecedented proliferation of surveillance programs by government agencies. This development has been driven both by technological progress, which has made large scale surveillance operations relatively cheap and easy, and by the threat of terrorism, organized crime and pandemics, which supplies a ready justification for surveillance. For a long time, mass surveillance programs have been associated with autocratic regimes, most notoriously with the German Democratic Republic and the Stasi, its secret police. A more recent case in (...)
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  39. Meaningful Human Control as Reason-Responsiveness: The Case of Dual-Mode Vehicles.Giulio Mecacci & Filippo Santoni de Sio - 2020 - Ethics and Information Technology 22 (2):103-115.
    In this paper, in line with the general framework of value-sensitive design, we aim to operationalize the general concept of “Meaningful Human Control” in order to pave the way for its translation into more specific design requirements. In particular, we focus on the operationalization of the first of the two conditions investigated: the so-called ‘tracking’ condition. Our investigation is led in relation to one specific subcase of automated system: dual-mode driving systems. First, we connect and compare meaningful human control with (...)
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  40. Ethics of Artificial Intelligence and Robotics.Vincent C. Müller - 2020 - In Edward Zalta (ed.), Stanford Encyclopedia of Philosophy. Palo Alto, Cal.: CSLI, Stanford University. pp. 1-70.
    Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used (...)
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  41. Improve Alignment of Research Policy and Societal Values.Peter Novitzky, Michael J. Bernstein, Vincent Blok, Robert Braun, Tung Tung Chan, Wout Lamers, Anne Loeber, Ingeborg Meijer, Ralf Lindner & Erich Griessler - 2020 - Science 369 (6499):39-41.
    Historically, scientific and engineering expertise has been key in shaping research and innovation policies, with benefits presumed to accrue to society more broadly over time. But there is persistent and growing concern about whether and how ethical and societal values are integrated into R&I policies and governance, as we confront public disbelief in science and political suspicion toward evidence-based policy-making. Erosion of such a social contract with science limits the ability of democratic societies to deal with challenges presented by new, (...)
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  42. AI and the Path to Envelopment: Knowledge as a First Step Towards the Responsible Regulation and Use of AI-Powered Machines.Scott Robbins - 2020 - AI and Society 35 (2):391-400.
    With Artificial Intelligence entering our lives in novel ways—both known and unknown to us—there is both the enhancement of existing ethical issues associated with AI as well as the rise of new ethical issues. There is much focus on opening up the ‘black box’ of modern machine-learning algorithms to understand the reasoning behind their decisions—especially morally salient decisions. However, some applications of AI which are no doubt beneficial to society rely upon these black boxes. Rather than requiring algorithms to be (...)
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  43. In AI We Trust: Ethics, Artificial Intelligence, and Reliability.Mark Ryan - 2020 - Science and Engineering Ethics 26 (5):2749-2767.
    One of the main difficulties in assessing artificial intelligence is the tendency for people to anthropomorphise it. This becomes particularly problematic when we attach human moral activities to AI. For example, the European Commission’s High-level Expert Group on AI have adopted the position that we should establish a relationship of trust with AI and should cultivate trustworthy AI. Trust is one of the most important and defining activities in human relationships, so proposing that AI should be trusted, is a very (...)
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  44. AI Methods in Bioethics.Joshua August Skorburg, Walter Sinnott-Armstrong & Vincent Conitzer - 2020 - American Journal of Bioethics: Empirical Bioethics 1 (11):37-39.
    Commentary about the role of AI in bioethics for the 10th anniversary issue of AJOB: Empirical Bioethics.
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  45. Transhumanism as a New Social Movement.Fabio Tollon - 2020 - Metapsychology Online Reviews.
    In his engaging book, James MacFarlane details the emergence of Technological Human Enhancement Advocacy (THEA) and provides a detailed ethnographic account of this phenomenon. Specifically, he aims to outline how transhumanism, as a specific offshoot of THEA, has “come to represent an enduring set of techno-optimistic ideas surrounding the future of humanity, with its advocates seeking to transcend limits of the body and mind according to an unwavering Enlightenment-derived faith in science, reason and individual freedom” (pg. 3).
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  46. Classification of Global Catastrophic Risks Connected with Artificial Intelligence.Alexey Turchin & David Denkenberger - 2020 - AI and Society 35 (1):147-163.
    A classification of the global catastrophic risks of AI is presented, along with a comprehensive list of previously identified risks. This classification allows the identification of several new risks. We show that at each level of AI’s intelligence power, separate types of possible catastrophes dominate. Our classification demonstrates that the field of AI risks is diverse, and includes many scenarios beyond the commonly discussed cases of a paperclip maximizer or robot-caused unemployment. Global catastrophic failure could happen at various levels of (...)
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  47. Meaningful Human Control Over Smart Home Systems: A Value Sensitive Design Approach.Steven Umbrello - 2020 - Humana.Mente Journal of Philosophical Studies 13 (37):40-65.
    The last decade has witnessed the mass distribution and adoption of smart home systems and devices powered by artificial intelligence systems ranging from household appliances like fridges and toasters to more background systems such as air and water quality controllers. The pervasiveness of these sociotechnical systems makes analyzing their ethical implications necessary during the design phases of these devices to ensure not only sociotechnical resilience, but to design them for human values in mind and thus preserve meaningful human control over (...)
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  48. The Future of War: The Ethical Potential of Leaving War to Lethal Autonomous Weapons.Steven Umbrello, Phil Torres & Angelo F. De Bellis - 2020 - AI and Society 35 (1):273-282.
    Lethal Autonomous Weapons (LAWs) are robotic weapons systems, primarily of value to the military, that could engage in offensive or defensive actions without human intervention. This paper assesses and engages the current arguments for and against the use of LAWs through the lens of achieving more ethical warfare. Specific interest is given particularly to ethical LAWs, which are artificially intelligent weapons systems that make decisions within the bounds of their ethics-based code. To ensure that a wide, but not exhaustive, survey (...)
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  49. Robustness to Fundamental Uncertainty in AGI Alignment.G. G. Worley Iii - 2020 - Journal of Consciousness Studies 27 (1-2):225-241.
    The AGI alignment problem has a bimodal distribution of outcomes with most outcomes clustering around the poles of total success and existential, catastrophic failure. Consequently, attempts to solve AGI alignment should, all else equal, prefer false negatives (ignoring research programs that would have been successful) to false positives (pursuing research programs that will unexpectedly fail). Thus, we propose adopting a policy of responding to points of philosophical and practical uncertainty associated with the alignment problem by limiting and choosing necessary assumptions (...)
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  50. Autonomous Vehicles, Trolley Problems, and the Law.Stephen S. Wu - 2020 - Ethics and Information Technology 22 (1):1-13.
    Autonomous vehicles have the potential to save tens of thousands of lives, but legal and social barriers may delay or even deter manufacturers from offering fully automated vehicles and thereby cost lives that otherwise could be saved. Moral philosophers use “thought experiments” to teach us about what ethics might say about the ethical behavior of AVs. If a manufacturer designing an AV decided to make what it believes is an ethical choice to save a large group of lives by steering (...)
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