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  1. Saint Thomas d'Aquin contre les robots. Pistes pour une approche philosophique de l'Intelligence Artificielle.Matthieu Raffray - 2019 - Angelicum 4 (96):553-572.
    In light of the pervasive developments of new technologies, such as NBIC (Nanotechnology, biotechnology, information technology, and cognitive science), it is imperative to produce a coherent and deep reflexion on the human nature, on human intelligence and on the limit of both of them, in order to successfully respond to some technical argumentations that strive to depict humanity as a purely mechanical system. For this purpose, it is interesting to refer to the epistemology and metaphysics of Thomas Aquinas as a (...)
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  2. Playing the Blame Game with Robots.Markus Kneer & Michael T. Stuart - 2021 - In Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction (HRI’21 Companion). New York, NY, USA:
    Recent research shows – somewhat astonishingly – that people are willing to ascribe moral blame to AI-driven systems when they cause harm [1]–[4]. In this paper, we explore the moral- psychological underpinnings of these findings. Our hypothesis was that the reason why people ascribe moral blame to AI systems is that they consider them capable of entertaining inculpating mental states (what is called mens rea in the law). To explore this hypothesis, we created a scenario in which an AI system (...)
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  3. Privacy and Digital Ethics After the Pandemic.Carissa Véliz - 2021 - Nature Electronics 4:10-11.
    The increasingly prominent role of digital technologies during the coronavirus pandemic has been accompanied by concerning trends in privacy and digital ethics. But more robust protection of our rights in the digital realm is possible in the future. -/- After surveying some of the challenges we face, I argue for the importance of diplomacy. Democratic countries must try to come together and reach agreements on minimum standards and rules regarding cybersecurity, privacy and the governance of AI.
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  4. Consequences of Unexplainable Machine Learning for the Notions of a Trusted Doctor and Patient Autonomy.Michal Klincewicz & Lily Frank - 2020 - Proceedings of the 2nd EXplainable AI in Law Workshop (XAILA 2019) Co-Located with 32nd International Conference on Legal Knowledge and Information Systems (JURIX 2019).
    This paper provides an analysis of the way in which two foundational principles of medical ethics–the trusted doctor and patient autonomy–can be undermined by the use of machine learning (ML) algorithms and addresses its legal significance. This paper can be a guide to both health care providers and other stakeholders about how to anticipate and in some cases mitigate ethical conflicts caused by the use of ML in healthcare. It can also be read as a road map as to what (...)
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  5. AI Extenders and the Ethics of Mental Health.Karina Vold & Jose Hernandez-Orallo - forthcoming - In Marcello Ienca & Fabrice Jotterand (eds.), Ethics of Artificial Intelligence in Brain and Mental Health.
    The extended mind thesis maintains that the functional contributions of tools and artefacts can become so essential for our cognition that they can be constitutive parts of our minds. In other words, our tools can be on a par with our brains: our minds and cognitive processes can literally ‘extend’ into the tools. Several extended mind theorists have argued that this ‘extended’ view of the mind offers unique insights into how we understand, assess, and treat certain cognitive conditions. In this (...)
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  6. Deepfakes and the Epistemic Backstop.Regina Rini - 2020 - Philosophers' Imprint 20 (24):1-16.
    Deepfake technology uses machine learning to fabricate video and audio recordings that represent people doing and saying things they've never done. In coming years, malicious actors will likely use this technology in attempts to manipulate public discourse. This paper prepares for that danger by explicating the unappreciated way in which recordings have so far provided an epistemic backstop to our testimonial practices. Our reasonable trust in the testimony of others depends, to a surprising extent, on the regulative effects of the (...)
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  7. Computational Models (of Narrative) for Literary Studies.Antonio Lieto - 2015 - Semicerchio, Rivista di Poesia Comparata 2 (LIII):38-44.
    In the last decades a growing body of literature in Artificial Intelligence (AI) and Cognitive Science (CS) has approached the problem of narrative understanding by means of computational systems. Narrative, in fact, is an ubiquitous element in our everyday activity and the ability to generate and understand stories, and their structures, is a crucial cue of our intelligence. However, despite the fact that - from an historical standpoint - narrative (and narrative structures) have been an important topic of investigation in (...)
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  8. Legal Fictions and the Essence of Robots: Thoughts on Essentialism and Pragmatism in the Regulation of Robotics.Fabio Fossa - 2018 - In Mark Coeckelbergh, Janina Loh, Michael Funk, Joanna Seibt & Marco Nørskov (eds.), Envisioning Robots in Society – Power, Politics, and, Public Space. Amsterdam: pp. 103-111.
    The purpose of this paper is to offer some critical remarks on the so-called pragmatist approach to the regulation of robotics. To this end, the article mainly reviews the work of Jack Balkin and Joanna Bryson, who have taken up such ap- proach with interestingly similar outcomes. Moreover, special attention will be paid to the discussion concerning the legal fiction of ‘electronic personality’. This will help shed light on the opposition between essentialist and pragmatist methodologies. After a brief introduction (1.), (...)
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  9. Making Metaethics Work for AI: Realism and Anti-Realism.Michal Klincewicz & Lily E. Frank - 2018 - In Mark Coeckelbergh, M. Loh, J. Funk, M. Seibt & J. Nørskov (eds.), Envisioning Robots in Society – Power, Politics, and Public Space. Amsterdam, Netherlands: IOS Press. pp. 311-318.
    Engineering an artificial intelligence to play an advisory role in morally charged decision making will inevitably introduce meta-ethical positions into the design. Some of these positions, by informing the design and operation of the AI, will introduce risks. This paper offers an analysis of these potential risks along the realism/anti-realism dimension in metaethics and reveals that realism poses greater risks, but, on the other hand, anti-realism undermines the motivation for engineering a moral AI in the first place.
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  10. Philosophy and Theory of Artificial Intelligence 2017.Vincent C. Müller (ed.) - 2017 - Berlin: Springer.
    This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; (...)
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Artificial Intelligence Safety
  1. AI Risk Denialism.Roman V. Yampolskiy - manuscript
    In this work, we survey skepticism regarding AI risk and show parallels with other types of scientific skepticism. We start by classifying different types of AI Risk skepticism and analyze their root causes. We conclude by suggesting some intervention approaches, which may be successful in reducing AI risk skepticism, at least amongst artificial intelligence researchers.
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  2. 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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  3. Sztuczna Inteligencja Bezpieczeństwo I Zabezpieczenia.Roman Yampolskiy (ed.) - 2020 - Warszawa: Wydawnictwo Naukowe PWN.
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  4. Epistemological Solipsism as a Route to External World Skepticism.Grace Helton - manuscript
    (Draft of a work committed to Philosophical Perspectives.) I show that some of the most initially attractive routes of refuting epistemological solipsism face serious obstacles. I also argue that for creatures like ourselves, solipsism is a genuine form of external world skepticism. I suggest that together these claims suggest the following morals: No proposed solution to external world skepticism can succeed which does not also solve the problem of epistemological solipsism. And, more tentatively: In assessing proposed solutions to external world (...)
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  5. Autonomous Weapon Systems, Asymmetrical Warfare, and Myth.Michal Klincewicz - 2018 - Civitas. Studia Z Filozofii Polityki 23:179-195.
    Predictions about autonomous weapon systems are typically thought to channel fears that drove all the myths about intelligence embodied in matter. One of these is the idea that the technology can get out of control and ultimately lead to horrifi c consequences, as is the case in Mary Shelley’s classic Frankenstein. Given this, predictions about AWS are sometimes dismissed as science-fiction fear-mongering. This paper considers several analogies between AWS and other weapon systems and ultimately offers an argument that nuclear weapons (...)
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  6. 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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  7. The Promise and Perils of Medical AI.Robert Sparrow & Joshua James Hatherley - 2019 - International Journal of Chinese and Comparative Philosophy of Medicine 17 (2):79-109.
    What does Artificial Intelligence (AI) have to contribute to health care? And what should we be looking out for if we are worried about its risks? In this paper we offer a survey, and initial evaluation, of hopes and fears about the applications of artificial intelligence in medicine. AI clearly has enormous potential as a research tool, in genomics and public health especially, as well as a diagnostic aid. It’s also highly likely to impact on the organisational and business practices (...)
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  8. On the Logical Impossibility of Solving the Control Problem.Caleb Rudnick - manuscript
    In the philosophy of artificial intelligence (AI) we are often warned of machines built with the best possible intentions, killing everyone on the planet and in some cases, everything in our light cone. At the same time, however, we are also told of the utopian worlds that could be created with just a single superintelligent mind. If we’re ever to live in that utopia (or just avoid dystopia) it’s necessary we solve the control problem. The control problem asks how humans (...)
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  9. 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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  10. 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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  11. On Controllability of Artificial Intelligence.Roman Yampolskiy - manuscript
    Invention of artificial general intelligence is predicted to cause a shift in the trajectory of human civilization. In order to reap the benefits and avoid pitfalls of such powerful technology it is important to be able to control it. However, possibility of controlling artificial general intelligence and its more advanced version, superintelligence, has not been formally established. In this paper, we present arguments as well as supporting evidence from multiple domains indicating that advanced AI can’t be fully controlled. Consequences of (...)
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  12. Human ≠ AGI.Roman Yampolskiy - manuscript
    Terms Artificial General Intelligence (AGI) and Human-Level Artificial Intelligence (HLAI) have been used interchangeably to refer to the Holy Grail of Artificial Intelligence (AI) research, creation of a machine capable of achieving goals in a wide range of environments. However, widespread implicit assumption of equivalence between capabilities of AGI and HLAI appears to be unjustified, as humans are not general intelligences. In this paper, we will prove this distinction.
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  13. 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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  14. 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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  15. 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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  16. 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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  17. 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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  18. 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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  19. 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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  20. 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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  21. Será que Hominoids ou Androids Destroem a Terra? — uma revisão de Como Criar Uma Mente (How to Create a Mind) por Ray Kurzweil (2012) (revisão revisada 2019).Michael Richard Starks - 2019 - In Delírios Utópicos Suicidas no Século XXI Filosofia, Natureza Humana e o Colapso da Civilization- Artigos e Comentários 2006-2019 5ª edição. Las Vegas, NV USA: Reality Press. pp. 155-167.
    Alguns anos atrás, cheguei ao ponto onde eu normalmente pode dizer a partir do título de um livro, ou pelo menos a partir dos títulos do capítulo, que tipos de erros filosóficos serão feitas e com que freqüência. No caso de obras nominalmente científicas, estas podem ser largamente restritas a certos capítulos que enceram filosóficos ou tentam tirar conclusões gerais sobre o significado ou significado a longo prazo do trabalho. Normalmente entretanto as matérias científicas do fato são misturado generosa com (...)
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  22. 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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  23. Responses to Catastrophic AGI Risk: A Survey.Kaj Sotala & Roman V. Yampolskiy - 2015 - Physica Scripta 90.
    Many researchers have argued that humanity will create artificial general intelligence (AGI) within the next twenty to one hundred years. It has been suggested that AGI may inflict serious damage to human well-being on a global scale ('catastrophic risk'). After summarizing the arguments for why AGI may pose such a risk, we review the fieldʼs proposed responses to AGI risk. We consider societal proposals, proposals for external constraints on AGI behaviors and proposals for creating AGIs that are safe due to (...)
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  24. 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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  25. چگونه هفت Sociopaths که حکومت چین در حال برنده شدن در جنگ جهانی سه و سه راه برای جلوگیری از آنها.Michael Richard Starks - 2019 - In خودکشی توسط دموکراسی یک موانع برای آمریکا و جهان. Las Vegas, NV USA: Reality Press. pp. 41-45.
    اولین چیزی که ما باید در ذهن داشته باشیم این است که زمانی که گفت که چین می گوید که این یا چین این کار را انجام می دهد ، ما از مردم چین صحبت نمی کنیم ، اما از Sociopaths که کنترل حزب کمونیست چین-چینی ، یعنی هفت قاتلان جامعه سالخورده (SSSSK) از th e کمیته ایستاده از حزب کمونیست چین و یا 25 نفر از اعضای پلی تکنیک و غیره. -/- برنامه های حزب کمونیست برای WW3 و سلطه (...)
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  26. Distributive Justice as an Ethical Principle for Autonomous Vehicle Behavior Beyond Hazard Scenarios.Manuel Dietrich & Thomas H. Weisswange - 2019 - Ethics and Information Technology 21 (3):227-239.
    Through modern driver assistant systems, algorithmic decisions already have a significant impact on the behavior of vehicles in everyday traffic. This will become even more prominent in the near future considering the development of autonomous driving functionality. The need to consider ethical principles in the design of such systems is generally acknowledged. However, scope, principles and strategies for their implementations are not yet clear. Most of the current discussions concentrate on situations of unavoidable crashes in which the life of human (...)
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  27. 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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  28. Unexplainability and Incomprehensibility of Artificial Intelligence.Roman Yampolskiy - manuscript
    Explainability and comprehensibility of AI are important requirements for intelligent systems deployed in real-world domains. Users want and frequently need to understand how decisions impacting them are made. Similarly it is important to understand how an intelligent system functions for safety and security reasons. In this paper, we describe two complementary impossibility results (Unexplainability and Incomprehensibility), essentially showing that advanced AIs would not be able to accurately explain some of their decisions and for the decisions they could explain people would (...)
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  29. 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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  30. Unpredictability of AI.Roman Yampolskiy - manuscript
    The young field of AI Safety is still in the process of identifying its challenges and limitations. In this paper, we formally describe one such impossibility result, namely Unpredictability of AI. We prove that it is impossible to precisely and consistently predict what specific actions a smarter-than-human intelligent system will take to achieve its objectives, even if we know terminal goals of the system. In conclusion, impact of Unpredictability on AI Safety is discussed.
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  31. 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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  32. 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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  33. Designing AI for Social Good: Seven Essential Factors.Josh Cowls, Thomas C. King, Mariarosaria Taddeo & Luciano Floridi - manuscript
    The idea of Artificial Intelligence for Social Good (henceforth AI4SG) is gaining traction within information societies in general and the AI community in particular. It has the potential to address social problems effectively through the development of AI-based solutions. Yet, to date, there is only limited understanding of what makes AI socially good in theory, what counts as AI4SG in practice, and how to reproduce its initial successes in terms of policies (Cath et al. 2018). This article addresses this gap (...)
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  34. 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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  35. 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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  36. 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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  37. Lethal Autonomous Weapons: Designing War Machines with Values.Steven Umbrello - 2019 - Delphi: Interdisciplinary Review of Emerging Technologies 1 (2):30-34.
    Lethal Autonomous Weapons (LAWs) have becomes the subject of continuous debate both at national and international levels. Arguments have been proposed both for the development and use of LAWs as well as their prohibition from combat landscapes. Regardless, the development of LAWs continues in numerous nation-states. This paper builds upon previous philosophical arguments for the development and use of LAWs and proposes a design framework that can be used to ethically direct their development. The conclusion is that the philosophical arguments (...)
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  38. 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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  39. 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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  40. Privacy, Transparency, and Accountability in the NSA’s Bulk Metadata Program.Alan Rubel - 2015 - In Adam D. Moore (ed.), Privacy, Security, and Accountability: Ethics, Law, and Policy. London, UK: pp. 183-202.
    Disputes at the intersection of national security, surveillance, civil liberties, and transparency are nothing new, but they have become a particularly prominent part of public discourse in the years since the attacks on the World Trade Center in September 2001. This is in part due to the dramatic nature of those attacks, in part based on significant legal developments after the attacks (classifying persons as “enemy combatants” outside the scope of traditional Geneva protections, legal memos by White House counsel providing (...)
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