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  1. Ecocentrism and Biosphere Life Extension.Karim Jebari & Anders Sandberg - 2022 - Science and Engineering Ethics 28 (6):1-19.
    The biosphere represents the global sum of all ecosystems. According to a prominent view in environmental ethics, ecocentrism, these ecosystems matter for their own sake, and not only because they contribute to human ends. As such, some ecocentrists are critical of the modern industrial civilization, and a few even argue that an irreversible collapse of the modern industrial civilization would be a good thing. However, taking a longer view and considering the eventual destruction of the biosphere by astronomical processes, we (...)
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  • Ethical Perceptions of AI in Hiring and Organizational Trust: The Role of Performance Expectancy and Social Influence.Maria Figueroa-Armijos, Brent B. Clark & Serge P. da Motta Veiga - 2023 - Journal of Business Ethics 186 (1):179-197.
    The use of artificial intelligence (AI) in hiring entails vast ethical challenges. As such, using an ethical lens to study this phenomenon is to better understand whether and how AI matters in hiring. In this paper, we examine whether ethical perceptions of using AI in the hiring process influence individuals’ trust in the organizations that use it. Building on the organizational trust model and the unified theory of acceptance and use of technology, we explore whether ethical perceptions are shaped by (...)
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  • The Moral Consideration of Artificial Entities: A Literature Review.Jamie Harris & Jacy Reese Anthis - 2021 - Science and Engineering Ethics 27 (4):1-95.
    Ethicists, policy-makers, and the general public have questioned whether artificial entities such as robots warrant rights or other forms of moral consideration. There is little synthesis of the research on this topic so far. We identify 294 relevant research or discussion items in our literature review of this topic. There is widespread agreement among scholars that some artificial entities could warrant moral consideration in the future, if not also the present. The reasoning varies, such as concern for the effects on (...)
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  • Axiological Futurism: The Systematic Study of the Future of Values.John Danaher - forthcoming - Futures.
    Human values seem to vary across time and space. What implications does this have for the future of human value? Will our human and (perhaps) post-human offspring have very different values from our own? Can we study the future of human values in an insightful and systematic way? This article makes three contributions to the debate about the future of human values. First, it argues that the systematic study of future values is both necessary in and of itself and an (...)
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  • Robot Betrayal: a guide to the ethics of robotic deception.John Danaher - 2020 - Ethics and Information Technology 22 (2):117-128.
    If a robot sends a deceptive signal to a human user, is this always and everywhere an unethical act, or might it sometimes be ethically desirable? Building upon previous work in robot ethics, this article tries to clarify and refine our understanding of the ethics of robotic deception. It does so by making three arguments. First, it argues that we need to distinguish between three main forms of robotic deception (external state deception; superficial state deception; and hidden state deception) in (...)
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  • Ethics of Artificial Intelligence and Robotics.Vincent C. Müller - 2020 - In Edward N. Zalta (ed.), Stanford Encylopedia of Philosophy. 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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  • Language Agents and Malevolent Design.Inchul Yum - 2024 - Philosophy and Technology 37 (104):1-19.
    Language agents are AI systems capable of understanding and responding to natural language, potentially facilitating the process of encoding human goals into AI systems. However, this paper argues that if language agents can achieve easy alignment, they also increase the risk of malevolent agents building harmful AI systems aligned with destructive intentions. The paper contends that if training AI becomes sufficiently easy or is perceived as such, it enables malicious actors, including rogue states, terrorists, and criminal organizations, to create powerful (...)
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  • Saved by the Dark Forest: How a Multitude of Extraterrestrial Civilizations Can Prevent a Hobbesian Trap.Karim Jebari & Andrea S. Asker - 2024 - The Monist 107 (2):176-189.
    The possibility of extraterrestrial intelligence (ETI) exists despite no observed evidence, and the risks and benefits of actively searching for ETI (Active SETI) have been debated. Active SETI has been criticized for potentially exposing humanity to existential risk, and a recent game-theoretical model highlights the Hobbesian trap that could occur following contact if mutual distrust leads to mutual destruction. We argue that observing a nearby ETI would suggest the existence of many unobserved ETI. This would expand the game and implies (...)
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  • Concepts of Existential Catastrophe.Hilary Greaves - 2024 - The Monist 107 (2):109-129.
    The notion of existential catastrophe is increasingly appealed to in discussion of risk management around emerging technologies, but it is not completely clear what this notion amounts to. Here, I provide an opinionated survey of the space of plausibly useful definitions of existential catastrophe. Inter alia, I discuss: whether to define existential catastrophe in ex post or ex ante terms, whether an ex ante definition should be in terms of loss of expected value or loss of potential, and what kind (...)
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  • Omission and commission errors underlying AI failures.Sasanka Sekhar Chanda & Debarag Narayan Banerjee - forthcoming - AI and Society:1-24.
    In this article we investigate origins of several cases of failure of Artificial Intelligence (AI) systems employing machine learning and deep learning. We focus on omission and commission errors in (a) the inputs to the AI system, (b) the processing logic, and (c) the outputs from the AI system. Our framework yields a set of 28 factors that can be used for reconstructing the path of AI failures and for determining corrective action. Our research helps identify emerging themes of inquiry (...)
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