Philosophy of Artificial Intelligence

Edited by Eric Dietrich (State University of New York at Binghamton)
Assistant editor: Michelle Thomas (University of Western Ontario)
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  1. Designing AI Nudging for Social Good: New Healthcare Skills for Digital Personal Assistants.Marianna Capasso & Steven Umbrello - manuscript
    Traditional medical practices and relationships are changing given the widespread adoption of AI-driven technologies across the various domains of health and healthcare. In many cases, these new technologies are not specific to the field of healthcare. Still, they are existent, ubiquitous, and commercially available systems upskilled to integrate these novel care practices. Given the widespread adoption, coupled with the dramatic changes in practices, new ethical and social issues emerge due to how these systems nudge users into making decisions and changing (...)
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  2. Famous Wet Raincoat: Review of Erik Larson The Myth of Artificial Intelligence[REVIEW]Christopher Mole - 2021 - TLS: The Times Literary Supplement 6169 (June 25th):25.
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  3. Citizenship as the Exception to the Rule: An Addendum.Tyler L. Jaynes - forthcoming - AI and Society:1-20.
    This addendum expands upon the arguments made in the author’s 2020 essay, “Legal Personhood for Artificial Intelligence: Citizenship as the Exception to the Rule”, in an effort to display the significance human augmentation technologies will have on (feasibly) inadvertently providing legal protections to artificial intelligence systems (AIS)—a topic only briefly addressed in that work. It will also further discuss the impacts popular media have on imprinting notions of computerised behaviour and its subsequent consequences on the attribution of legal protections to (...)
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  4. The Gap Between Intelligence and Mind.Bowen Xu, Xinyi Zhan & Quansheng Ren - manuscript
    The feeling (quale) brings the "Hard Problem" to philosophy of mind. Does the subjective feeling have a non-ignorable impact on Intelligence? If so, can the feeling be realized in Artificial Intelligence (AI)? To discuss the problems, we have to figure out what the feeling means, by giving a clear definition. In this paper, we primarily give some mainstream perspectives on the topic of the mind, especially the topic of the feeling (or qualia, subjective experience, etc.). Then, a definition of the (...)
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  5. Philosophy and Digitization: Dangers and Possibilities in the New Digital Worlds.Esther Oluffa Pedersen & Maria Brincker - 2021 - SATS 22 (1):1-9.
    Our world is under going an enormous digital transformation. Nearly no area of our social, informational, political, economic, cultural, and biological spheres are left unchanged. What can philosophy contribute as we try to under- stand and think through these changes? How does digitization challenge past ideas of who we are and where we are headed? Where does it leave our ethical aspirations and cherished ideals of democracy, equality, privacy, trust, freedom, and social embeddedness? Who gets to decide, control, and harness (...)
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  6. Science Fiction and Philosophy: From Time Travel to Superintelligence (Wiley-Blackwell, 2016). [REVIEW]Stefano Bigliardi - 2020 - Journal of Science Fiction and Philosophy 3.
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  7. Ethics as a service: a pragmatic operationalisation of AI ethics.Jessica Morley, Anat Elhalal, Francesca Garcia, Libby Kinsey, Jakob Mökander & Luciano Floridi - 2021 - Minds and Machines 31 (2):239–256.
    As the range of potential uses for Artificial Intelligence, in particular machine learning, has increased, so has awareness of the associated ethical issues. This increased awareness has led to the realisation that existing legislation and regulation provides insufficient protection to individuals, groups, society, and the environment from AI harms. In response to this realisation, there has been a proliferation of principle-based ethics codes, guidelines and frameworks. However, it has become increasingly clear that a significant gap exists between the theory of (...)
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  8. Ethics-based auditing to develop trustworthy AI.Jakob Mökander & Luciano Floridi - 2021 - Minds and Machines 31 (2):323–327.
    A series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions concerning ethics-based auditing, we offer three contributions. First, we argue that ethics-based auditing can improve the quality of decision making, increase user satisfaction, unlock growth potential, enable law-making, and relieve human suffering. Second, we highlight current best practices to support the design and implementation of ethics-based auditing: To be feasible and effective, ethics-based auditing (...)
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  9. Techno-Telepathy & Silent Subvocal Speech-Recognition Robotics.Virgil W. Brower - 2021 - HORIZON. Studies in Phenomenology 10 (1):232-257.
    The primary focus of this project is the silent and subvocal speech-recognition interface unveiled in 2018 as an ambulatory device wearable on the neck that detects a myoelectrical signature by electrodes worn on the surface of the face, throat, and neck. These emerge from an alleged “intending to speak” by the wearer silently-saying-something-to-oneself. This inner voice is believed to occur while one reads in silence or mentally talks to oneself. The artifice does not require spoken sounds, opening the mouth, or (...)
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  10. Moral Difference Between Humans and Robots: Paternalism and Human-Relative Reason.Tsung-Hsing Ho - forthcoming - AI and Society:1-11.
    According to some philosophers, if moral agency is understood in behaviourist terms, robots could become moral agents that are as good as or even better than humans. Given the behaviourist conception, it is natural to think that there is no interesting moral difference between robots and humans in terms of moral agency. However, such moral differences exist: based on Strawson’s account of participant reactive attitude and Scanlon’s relational account of blame, I argue that a distinct kind of reason available to (...)
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  11. Varieties of Artifacts: Embodied, Perceptual, Cognitive, and Affective.Richard Heersmink - 2021 - Topics in Cognitive Science:1-24.
    The primary goal of this essay is to provide a comprehensive overview and analysis of the various relations between material artifacts and the embodied mind. A secondary goal of this essay is to identify some of the trends in the design and use of artifacts. First, based on their functional properties, I identify four categories of artifacts co-opted by the embodied mind, namely (1) embodied artifacts, (2) perceptual artifacts, (3) cognitive artifacts, and (4) affective artifacts. These categories can overlap and (...)
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  12. Word vector embeddings hold social ontological relations capable of reflecting meaningful fairness assessments.Ahmed Izzidien - 2021 - AI and Society (March 2021):1-20.
    Programming artificial intelligence to make fairness assessments of texts through top-down rules, bottom-up training, or hybrid approaches, has presented the challenge of defining cross-cultural fairness. In this paper a simple method is presented which uses vectors to discover if a verb is unfair or fair. It uses already existing relational social ontologies inherent in Word Embeddings and thus requires no training. The plausibility of the approach rests on two premises. That individuals consider fair acts those that they would be willing (...)
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  13. Algorithmic Fairness in Mortgage Lending: From Absolute Conditions to Relational Trade-Offs.Michelle Seng Ah Lee & Luciano Floridi - 2021 - Minds and Machines 31 (1):165-191.
    To address the rising concern that algorithmic decision-making may reinforce discriminatory biases, researchers have proposed many notions of fairness and corresponding mathematical formalizations. Each of these notions is often presented as a one-size-fits-all, absolute condition; however, in reality, the practical and ethical trade-offs are unavoidable and more complex. We introduce a new approach that considers fairness—not as a binary, absolute mathematical condition—but rather, as a relational notion in comparison to alternative decisionmaking processes. Using US mortgage lending as an example use (...)
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  14. Artifacts and Affordances: From Designed Properties to Possibilities for Action.Fabio Tollon - 2021 - AI and Society 2:1-10.
    In this paper I critically evaluate the value neutrality thesis regarding technology, and find it wanting. I then introduce the various ways in which artifacts can come to influence moral value, and our evaluation of moral situations and actions. Here, following van de Poel and Kroes, I introduce the idea of value sensitive design. Specifically, I show how by virtue of their designed properties, artifacts may come to embody values. Such accounts, however, have several shortcomings. In agreement with Michael Klenk, (...)
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  15. Quem ou o que pensa? Uma busca de aportes para questões filosóficas suscitadas pela revolução informática atual.Lamartine De Hollanda Cavalcanti Neto - 2020 - Dissertation, Universidade Federal de São Paulo
    Taking as an assumption the existence of an informatics revolution nowadays and that the examination of studies and debates related to it may allow the identification of questions of a philosophical nature, the present study aims to identify and formulate some of these questions, as well as to investigate whether the historical controversy about monopsychism, which occurred at the University of Paris in 1270, can be considered a theoretical framework capable of providing contributions to these philosophical questions. The answer to (...)
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  16. Ethics-Based Auditing to Develop Trustworthy AI.Jakob Mökander & Luciano Floridi - 2021 - Minds and Machines.
    A series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions concerning ethics-based auditing, we offer three contributions. First, we argue that ethics-based auditing can improve the quality of decision making, increase user satisfaction, unlock growth potential, enable law-making, and relieve human suffering. Second, we highlight current best practices to support the design and implementation of ethics-based auditing: To be feasible and effective, ethics-based auditing (...)
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  17. An Empathy Imitation Game: Empathy Turing Test for Care- and Chat-Bots.Jeremy Howick, Jessica Morley & Luciano Floridi - forthcoming - Minds and Machines:1–⁠5.
    AI, in the form of artificial carers, provides a possible solution to the problem of a growing elderly population Yet, concerns remain that artificial carers ( such as care-or chat-bots) could not emphathize with patients to the extent that humans can. Utilising the concept of empathy perception,we propose a Turing-type test that could check whether artificial carers could do many of the menial tasks human carers currently undertake, and in the process, free up more time for doctors to offer empathy. (...)
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  18. Debate: What is Personhood in the Age of AI?David J. Gunkel & Jordan Joseph Wales - forthcoming - AI and Society.
    In a friendly interdisciplinary debate, we interrogate from several vantage points the question of “personhood” in light of contemporary and near-future forms of social AI. David J. Gunkel approaches the matter from a philosophical and legal standpoint, while Jordan Wales offers reflections theological and psychological. Attending to metaphysical, moral, social, and legal understandings of personhood, we ask about the position of apparently personal artificial intelligences in our society and individual lives. Re-examining the “person” and questioning prominent construals of that category, (...)
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  19. Morphing Intelligence: From IQ Measurement to Artificial Brains. [REVIEW]Ekin Erkan - 2020 - Chiasma 6 (1):248-260.
    In her seminal text, What Should We Do With Our Brain? (2008), Catherine Malabou gestured towards neuroplasticity to upend Bergson's famous parallel of the brain as a "central telephonic exchange," whereby the function of the brain is simply that of a node where perceptions get in touch with motor mechanisms, the brain as an instrument limited to the transmission and divisions of movements. Drawing from the history of cybernetics one can trace how Bergson's 'telephonic exchange' prefigures the neural 'cybernetic metaphor.' (...)
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  20. The Cognitive Sciences: A Comment on 6 Reviews of The MIT Encyclopedia of the Cognitive Sciences.Robert A. Wilson - 2001 - Artificial Intelligence 130 (2):223-229.
    As the pluralization in the title of MITECS suggests, and as many reviewers have noted, the stance that we adopted as general editors for this project was ecumenical. We were particularly concerned to generate a volume whose range of topics and perspectives indicated that “cognitive science” was different things to different groups of researchers, and that many even fundamental questions remain open after at least four decades of various interdisciplinary ventures. Implicit in this view is a wariness of any putative (...)
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  21. Creativity.Peter Langland-Hassan - 2020 - In Explaining Imagination. Oxford: pp. 262-296.
    Comparatively easy questions we might ask about creativity are distinguished from the hard question of explaining transformative creativity. Many have focused on the easy questions, offering no reason to think that the imagining relied upon in creative cognition cannot be reduced to more basic folk psychological states. The relevance of associative thought processes to songwriting is then explored as a means for understanding the nature of transformative creativity. Productive artificial neural networks—known as generative antagonistic networks (GANs)—are a recent example of (...)
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  22. GPT-3: Its Nature, Scope, Limits, and Consequences.Luciano Floridi & Massimo Chiriatti - 2020 - Minds and Machines 30 (4):681–⁠694.
    In this commentary, we discuss the nature of reversible and irreversible questions, that is, questions that may enable one to identify the nature of the source of their answers. We then introduce GPT-3, a third-generation, autoregressive language model that uses deep learning to produce human-like texts, and use the previous distinction to analyse it. We expand the analysis to present three tests based on mathematical, semantic, and ethical questions and show that GPT-3 is not designed to pass any of them. (...)
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  23. What Do Technology and Artificial Intelligence Mean Today?Scott H. Hawley & Elias Kruger - forthcoming - In Hector Fernandez (ed.), Sociedad Tecnológica y Futuro Humano, vol. 1: Desafíos conceptuales. Santiago, Chile: pp. 17.
    Technology and Artificial Intelligence, both today and in the near future, are dominated by automated algorithms that combine optimization with models based on the human brain to learn, predict, and even influence the large-scale behavior of human users. Such applications can be understood to be outgrowths of historical trends in industry and academia, yet have far-reaching and even unintended consequences for social and political life around the world. Countries in different parts of the world take different regulatory views for the (...)
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  24. Every Step You Take, We’Ll Be Watching You: Nudging and the Ramifications of GPS Technology.William Hebblewhite & Alexander James Gillett - 2020 - AI and Society.
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  25. What is Interpretability?Adrian Erasmus, Tyler D. P. Brunet & Eyal Fisher - 2020 - Philosophy and Technology.
    We argue that artificial networks are explainable and offer a novel theory of interpretability. Two sets of conceptual questions are prominent in theoretical engagements with artificial neural networks, especially in the context of medical artificial intelligence: Are networks explainable, and if so, what does it mean to explain the output of a network? And what does it mean for a network to be interpretable? We argue that accounts of “explanation” tailored specifically to neural networks have ineffectively reinvented the wheel. In (...)
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  26. Self-Building Technologies.François Kammerer - 2020 - AI and Society 35 (4):901-915.
    On the basis of two thought experiments, I argue that self-building technologies are possible given our current level of technological progress. We could already use technology to make us instantiate selfhood in a more perfect, complete manner. I then examine possible extensions of this thesis, regarding more radical self-building technologies which might become available in a distant future. I also discuss objections and reservations one might have about this view.
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  27. Aiming AI at a Moving Target: Health.Mihai Nadin - 2020 - AI and Society 35 (4):841-849.
    Justified by spectacular achievements facilitated through applied deep learning methodology, the “Everything is possible” view dominates this new hour in the “boom and bust” curve of AI performance. The optimistic view collides head on with the “It is not possible”—ascertainments often originating in a skewed understanding of both AI and medicine. The meaning of the conflicting views can be assessed only by addressing the nature of medicine. Specifically: Which part of medicine, if any, can and should be entrusted to AI—now (...)
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  28. Vagueness and Roughness.Bonikowski Zbigniew & Wybranie-Skardowska Urszula - 2008 - In Transactions on Rough Sets IX. Lectures Notes and Computer Science 5290. Berlin-Heidelberg: pp. 1-13.
    The paper proposes a new formal approach to vagueness and vague sets taking inspirations from Pawlak’s rough set theory. Following a brief introduction to the problem of vagueness, an approach to conceptualization and representation of vague knowledge is presented from a number of different perspectives: those of logic, set theory, algebra, and computer science. The central notion of the vague set, in relation to the rough set, is defined as a family of sets approximated by the so called lower and (...)
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  29. Transparency in Complex Computational Systems.Kathleen A. Creel - 2020 - Philosophy of Science 87 (4):568-589.
    Scientists depend on complex computational systems that are often ineliminably opaque, to the detriment of our ability to give scientific explanations and detect artifacts. Some philosophers have s...
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  30. In Defence of the Hivemind Society.John Danaher & Steve Petersen - forthcoming - Neuroethics:1-15.
    The idea that humans should abandon their individuality and use technology to bind themselves together into hivemind societies seems both farfetched and frightening – something that is redolent of the worst dystopias from science fiction. In this article, we argue that these common reactions to the ideal of a hivemind society are mistaken. The idea that humans could form hiveminds is sufficiently plausible for its axiological consequences to be taken seriously. Furthermore, far from being a dystopian nightmare, the hivemind society (...)
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  31. Deleuze’s Postscript on the Societies of Control Updated for Big Data and Predictive Analytics.James Brusseau - 2020 - Theoria 67 (164):1-25.
    In 1990, Gilles Deleuze published Postscript on the Societies of Control, an introduction to the potentially suffocating reality of the nascent control society. This thirty-year update details how Deleuze’s conception has developed from a broad speculative vision into specific economic mechanisms clustering around personal information, big data, predictive analytics, and marketing. The central claim is that today’s advancing control society coerces without prohibitions, and through incentives that are not grim but enjoyable, even euphoric because they compel individuals to obey their (...)
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  32. Carving a Life From Legacy: Frankfurt’s Account of Free Will and Manipulation in Greg Egan’s “Reasons to Be Cheerful”.Taylor W. Cyr - 2018 - Journal of Science Fiction and Philosophy 1:1-15.
    Many find it intuitive that having been manipulated undermines a person's free will. Some have objected to accounts of free will like Harry Frankfurt's (according to which free will depends only on an agent's psychological structure at the time of action) by arguing that it is possible for manipulated agents, who are intuitively unfree, to satisfy Frankfurt's allegedly sufficient conditions for freedom. Drawing resources from Greg Egan's "Reasons to Be Cheerful" as well as from stories of psychologically sophisticated artificial intelligence (...)
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  33. Artificial Intelligence as Art – What the Philosophy of Art Can Offer the Understanding of AI and Consciousness.Hutan Ashrafian - manuscript
    Defining Artificial Intelligence and Artificial General Intelligence remain controversial and disputed. They stem from a longer-standing controversy of what is the definition of consciousness, which if solved could possibly offer a solution to defining AI and AGI. Central to these problems is the paradox that appraising AI and Consciousness requires epistemological objectivity of domains that are ontologically subjective. I propose that applying the philosophy of art, which also aims to define art through a lens of epistemological objectivity where the domains (...)
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  34. Towards the Ethical Publication of Country of Origin Information (COI) in the Asylum Process.Nikita Aggarwal & Luciano Floridi - 2020 - Minds and Machines 30 (2):247-257.
    This article addresses the question of how ‘Country of Origin Information’ reports—that is, research developed and used to support decision-making in the asylum process—can be published in an ethical manner. The article focuses on the risk that published COI reports could be misused and thereby harm the subjects of the reports and/or those involved in their development. It supports a situational approach to assessing data ethics when publishing COI reports, whereby COI service providers must weigh up the benefits and harms (...)
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  35. Can the G Factor Play a Role in Artificial General Intelligence Research?Davide Serpico & Marcello Frixione - 2018 - In Proceedings of the Society for the Study of Artificial Intelligence and Simulation of Behaviour 2018. pp. 301-305.
    In recent years, a trend in AI research has started to pursue human-level, general artificial intelli-gence (AGI). Although the AGI framework is characterised by different viewpoints on what intelligence is and how to implement it in artificial systems, it conceptualises intelligence as flexible, general-purposed, and capable of self-adapting to different contexts and tasks. Two important ques-tions remain open: a) should AGI projects simu-late the biological, neural, and cognitive mecha-nisms realising the human intelligent behaviour? and b) what is the relationship, if (...)
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  36. Ethical Foresight Analysis: What It is and Why It is Needed?Luciano Floridi & Andrew Strait - 2020 - Minds and Machines 30 (1):77-97.
    An increasing number of technology firms are implementing processes to identify and evaluate the ethical risks of their systems and products. A key part of these review processes is to foresee potential impacts of these technologies on different groups of users. In this article, we use the expression Ethical Foresight Analysis to refer to a variety of analytical strategies for anticipating or predicting the ethical issues that new technological artefacts, services, and applications may raise. This article examines several existing EFA (...)
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  37. The AI Human Condition is a Dilemma Between Authenticity and Freedom.James Brusseau - manuscript
    Big data and predictive analytics applied to economic life is forcing individuals to choose between authenticity and freedom. The fact of the choice cuts philosophy away from the traditional understanding of the two values as entwined. This essay describes why the split is happening, how new conceptions of authenticity and freedom are rising, and the human experience of the dilemma between them. Also, this essay participates in recent philosophical intersections with Shoshana Zuboff’s work on surveillance capitalism, but the investigation connects (...)
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  38. Calibrating Generative Models: The Probabilistic Chomsky-Schützenberger Hierarchy.Thomas Icard - 2020 - Journal of Mathematical Psychology 95.
    A probabilistic Chomsky–Schützenberger hierarchy of grammars is introduced and studied, with the aim of understanding the expressive power of generative models. We offer characterizations of the distributions definable at each level of the hierarchy, including probabilistic regular, context-free, (linear) indexed, context-sensitive, and unrestricted grammars, each corresponding to familiar probabilistic machine classes. Special attention is given to distributions on (unary notations for) positive integers. Unlike in the classical case where the "semi-linear" languages all collapse into the regular languages, using analytic tools (...)
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  39. Why Technoscience Cannot Reproduce Human Desire According to Lacanian Thomism.Christopher Wojtulewicz & Graham J. McAleer - 2019 - Forum Philosophicum: International Journal for Philosophy 2 (24):279-300.
    Being born into a family structure—being born of a mother—is key to being human. It is, for Jacques Lacan, essential to the formation of human desire. It is also part of the structure of analogy in the Thomistic thought of Erich Przywara. AI may well increase exponentially in sophistication, and even achieve human-like qualities; but it will only ever form an imaginary mirroring of genuine human persons—an imitation that is in fact morbid and dehumanising. Taking Lacan and Przywara at a (...)
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  40. Rituals and Algorithms: Genealogy of Reflective Faith and Postmetaphysical Thinking.Martin Beck Matuštík - 2019 - European Journal for Philosophy of Religion 11 (4):163-184.
    What happens when mindless symbols of algorithmic AI encounter mindful performative rituals? I return to my criticisms of Habermas’ secularising reading of Kierkegaard’s ethics. Next, I lay out Habermas’ claim that the sacred complex of ritual and myth contains the ur-origins of postmetaphysical thinking and reflective faith. If reflective faith shares with ritual same origins as does communicative interaction, how do we access these archaic ritual sources of human solidarity in the age of AI?
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  41. Key ethical challenges in the European Medical Information Framework.Luciano Floridi, Christoph Luetge, Ugo Pagallo, Burkhard Schafer, Peggy Valcke, Effy Vayena, Janet Addison, Nigel Hughes, Nathan Lea, Caroline Sage, Bart Vannieuwenhuyse & Dipak Kalra - 2019 - Minds and Machines 29 (3):355-371.
    The European Medical Information Framework project, funded through the IMI programme, has designed and implemented a federated platform to connect health data from a variety of sources across Europe, to facilitate large scale clinical and life sciences research. It enables approved users to analyse securely multiple, diverse, data via a single portal, thereby mediating research opportunities across a large quantity of research data. EMIF developed a code of practice to ensure the privacy protection of data subjects, protect the interests of (...)
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  42. La Modellizzazione Computazionale Della Competenza Inferen-Ziale E Della Competenza Referenziale.Fabrizio Calzavarini & Antonio Lieto - forthcoming - Sistemi Intelligenti.
    In philosophy of language, a distinction has been proposed by Diego Marconi between two aspects of lexical competence, i.e. referential and inferential competence. The former accounts for the relation-ship of words to the world, the latter for the relationship of words among themselves. The aim of the pa-per is to offer a critical discussion of the kind of formalisms and computational techniques that can be used in Artificial Intelligence to model the two aspects of lexical competence, and of the main (...)
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  43. From Biological to Synthetic Neurorobotics Approaches to Understanding the Structure Essential to Consciousness (Part 2).Jun Tani & Jeff White - 2016 - APA Newsletter on Philosophy and Computers 2 (16):29-41.
    We have been left with a big challenge, to articulate consciousness and also to prove it in an artificial agent against a biological standard. After introducing Boltuc’s h-consciousness in the last paper, we briefly reviewed some salient neurology in order to sketch less of a standard than a series of targets for artificial consciousness, “most-consciousness” and “myth-consciousness.” With these targets on the horizon, we began reviewing the research program pursued by Jun Tani and colleagues in the isolation of the formal (...)
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  44. From Biological to Synthetic Neurorobotics Approaches to Understanding the Structure Essential to Consciousness, Part 1.Jeffrey White - 2016 - APA Newsletter on Philosophy and Computers 1 (16):13-23.
    Direct neurological and especially imaging-driven investigations into the structures essential to naturally occurring cognitive systems in their development and operation have motivated broadening interest in the potential for artificial consciousness modeled on these systems. This first paper in a series of three begins with a brief review of Boltuc’s (2009) “brain-based” thesis on the prospect of artificial consciousness, focusing on his formulation of h-consciousness. We then explore some of the implications of brain research on the structure of consciousness, finding limitations (...)
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  45. Menschengestützte Künstliche Intelligenz: Über die soziotechnischen Voraussetzungen von "deep learning".Rainer Mühlhoff - 2019 - Zeitschrift Für Medienwissenschaft (ZfM) 21 (2):56–64.
    Die aktuellen Erfolge von Künstlicher Intelligenz beruhen nicht nur auf technologischen Fortschritten, sondern auch auf einem grundlegenden soziotechnischen Strukturwandel. Denn maschinelle Lernverfahren wie Deep Learning benötigen eine große Menge Trainingsdaten, die nur über menschliche Mitarbeit gewonnen werden können. In einer Konvergenz von Methoden der Human-Computer-Interaction und der KI ist in den letzten zehn Jahren eine Fülle von Mensch-Maschine-Interfaces und medialen Infrastrukturen entstanden, durch die menschliche kognitive Ressourcen in hybride Mensch-Maschine-Apparate eingespannt werden. Diese Apparate vollbringen im Ganzen jene Leistung, die als (...)
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  46. Why Be Random?Thomas Icard - 2021 - Mind 130 (517):fzz065.
    When does it make sense to act randomly? A persuasive argument from Bayesian decision theory legitimizes randomization essentially only in tie-breaking situations. Rational behaviour in humans, non-human animals, and artificial agents, however, often seems indeterminate, even random. Moreover, rationales for randomized acts have been offered in a number of disciplines, including game theory, experimental design, and machine learning. A common way of accommodating some of these observations is by appeal to a decision-maker’s bounded computational resources. Making this suggestion both precise (...)
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  47. Privacy, Autonomy, and Personalised Targeting: Rethinking How Personal Data is Used.Karina Vold & Jessica Whittlestone - 2019 - In Carissa Véliz (ed.), Report on Data, Privacy, and the Individual in the Digital Age.
    Technological advances are bringing new light to privacy issues and changing the reasons for why privacy is important. These advances have changed not only the kind of personal data that is available to be collected, but also how that personal data can be used by those who have access to it. We are particularly concerned with how information about personal attributes inferred from collected data (such as online behaviour), can be used to tailor messages and services to specific individuals or (...)
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  48. What Does It Mean to Understand? Neural Networks Case.Albert Ierusalem & Aleksandr Senin - manuscript
    We can say that we understand neural networks then and only then if you will come to me and say that the best model ever for some task has a 100 layers, and I will answer "No! 101 layers model is the best!".
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  49. Social intelligence: How to integrate research? A mechanistic perspective.Marcin Miłkowski - 2019 - AI and Society 34 (4):735-744.
    Is there a field of social intelligence? Many various disciplines approach the subject and it may only seem natural to suppose that different fields of study aim at explaining different phenomena; in other words, there is no special field of study of social intelligence. In this paper, I argue for an opposite claim. Namely, there is a way to integrate research on social intelligence, as long as one accepts the mechanistic account to explanation. Mechanistic integration of different explanations, however, comes (...)
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  50. The Bit (and Three Other Abstractions) Define the Borderline Between Hardware and Software.Russ Abbott - 2019 - Minds and Machines 29 (2):239-285.
    Modern computing is generally taken to consist primarily of symbol manipulation. But symbols are abstract, and computers are physical. How can a physical device manipulate abstract symbols? Neither Church nor Turing considered this question. My answer is that the bit, as a hardware-implemented abstract data type, serves as a bridge between materiality and abstraction. Computing also relies on three other primitive—but more straightforward—abstractions: Sequentiality, State, and Transition. These physically-implemented abstractions define the borderline between hardware and software and between physicality and (...)
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