Philosophy of Artificial Intelligence

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  1. A Dilemma for Solomonoff Prediction.Sven Neth - forthcoming - Philosophy of Science.
    The framework of Solomonoff prediction assigns prior probability to hypotheses inversely proportional to their Kolmogorov complexity. There are two well-known problems. First, the Solomonoff prior is relative to a choice of Universal Turing machine. Second, the Solomonoff prior is not computable. However, there are responses to both problems. Different Solomonoff priors converge with more and more data. Further, there are computable approximations to the Solomonoff prior. I argue that there is a tension between these two responses. This is because computable (...)
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  2. Reclaiming Control: Extended Mindreading and the Tracking of Digital Footprints.Uwe Peters - 2022 - Social Epistemology 36 (3):267-282.
    It is well known that on the Internet, computer algorithms track our website browsing, clicks, and search history to infer our preferences, interests, and goals. The nature of this algorithmic tracking remains unclear, however. Does it involve what many cognitive scientists and philosophers call ‘mindreading’, i.e., an epistemic capacity to attribute mental states to people to predict, explain, or influence their actions? Here I argue that it does. This is because humans are in a particular way embedded in the process (...)
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  3. Development of Keyword Trend Prediction Models for Obesity Before and After the COVID-19 Pandemic Using RNN and LSTM: Analyzing the News Big Data of South Korea.Gayeong Eom & Haewon Byeon - 2022 - Frontiers in Public Health 10:894266.
    The Korea National Health and Nutrition Examination Survey (2020) reported that the prevalence of obesity (≥19 years old) was 31.4% in 2011, but it increased to 33.8% in 2019 and 38.3% in 2020, which confirmed that it increased rapidly after the outbreak of COVID-19. Obesity increases not only the risk of infection with COVID-19 but also severity and fatality rate after being infected with COVID-19 compared to people with normal weight or underweight. Therefore, identifying the difference in potential factors for (...)
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  4. Putnam’s Problem of the Robot and Extended Minds.Jacob Berk - 2022 - Stance 15:88-99.
    In this paper, I consider Hilary Putnam’s argument for the prima facie acceptance of robotic consciousness as deserving the status of mind. I argue that such an extension of consciousness renders the category fundamentally unintelligible, and we should instead understand robots as integral products of an extended human consciousness. To this end, I propose a test from conceptual object permanence, which can be applied not just to robots, but to the innumerable artifacts of consciousness that texture our existences.
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  5. Unownability of AI: Why Legal Ownership of Artificial Intelligence is Hard.Roman Yampolskiy - manuscript
    To hold developers responsible, it is important to establish the concept of AI ownership. In this paper we review different obstacles to ownership claims over advanced intelligent systems, including unexplainability, unpredictability, uncontrollability, self-modification, AI-rights, ease of theft when it comes to AI models and code obfuscation. We conclude that it is difficult if not impossible to establish ownership claims over AI models beyond a reasonable doubt.
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  6. The Use and Misuse of Counterfactuals in Ethical Machine Learning.Atoosa Kasirzadeh & Andrew Smart - 2021 - In ACM Conference on Fairness, Accountability, and Transparency (FAccT 21).
    The use of counterfactuals for considerations of algorithmic fairness and explainability is gaining prominence within the machine learning community and industry. This paper argues for more caution with the use of counterfactuals when the facts to be considered are social categories such as race or gender. We review a broad body of papers from philosophy and social sciences on social ontology and the semantics of counterfactuals, and we conclude that the counterfactual approach in machine learning fairness and social explainability can (...)
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  7. Certifiable AI.Jobst Landgrebe - 2022 - Applied Sciences 12 (3):1050.
    Implicit stochastic models, including both ‘deep neural networks’ (dNNs) and the more recent unsupervised foundational models, cannot be explained. That is, it cannot be determined how they work, because the interactions of the millions or billions of terms that are contained in their equations cannot be captured in the form of a causal model. Because users of stochastic AI systems would like to understand how they operate in order to be able to use them safely and reliably, there has emerged (...)
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  8. Examining the Intelligence in Artificial Intelligence.David Cycleback - 2020 - Center for Artifact Studies.
    The following looks at several problems and questions concerning our understanding of the word ‘intelligence’ and the phrase ‘artificial intelligence’ (AI), including: how to define these terms; whether intelligence can exist in AI; if artificial intelligence in AI is identifiable; and what (if any) kind of intelligence is important to AI.
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  9. Are Propositional Attitudes Mental States?Umut Baysan - forthcoming - Minds and Machines:1-16.
    I present an argument that propositional attitudes are not mental states. In a nutshell, the argument is that if propositional attitudes are mental states, then only minded beings could have them; but there are reasons to think that some non-minded beings could bear propositional attitudes. To illustrate this, I appeal to cases of genuine group intentionality. I argue that these are cases in which some group entities bear propositional attitudes, but they are not subjects of mental states. Although propositional attitudes (...)
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  10. Exploring RoBERTa's Theory of Mind Through Textual Entailment.Michael Cohen - manuscript
    Within psychology, philosophy, and cognitive science, theory of mind refers to the cognitive ability to reason about the mental states of other people, thus recognizing them as having beliefs, knowledge, intentions and emotions of their own. In this project, we construct a natural language inference (NLD) dataset that tests the ability of a state of the art language model, RoBERTa-large finetuned on the MNLI dataset, to make theory of mind inferences related to knowledge and belief. Experimental results suggest that the (...)
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  11. Artificial Intelligence and Analytic Pragmatism / Umjetna inteligencija i analitički pragmatizam (Bosnian translation by Nijaz Ibrulj).Nijaz Ibrulj & Robert B. Brandom - 2022 - Sophos 1 (15):211-232.
    The text "Artificial Intelligence and Analytic Pragmatism" was translated from the book by Robert B. Brand: Between Saying and Doing: Towards an Analytical Pragmatism. Chapter 3. Oxford University Press. pp. 69 - 92.
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  12. Whispers and Shouts. The Measurement of the Human Act.Fernando Flores Morador & Luis de Marcos Ortega (eds.) - 2021 - Alcalá de Henares, Madrid: Departement of Computational Sciences. University of Alcalá; Madrid.
    The 20th Century is the starting point for the most ambitious attempts to extrapolate human life into artificial systems. Norbert Wiener’s Cybernetics, Claude Shannon’s Information Theory, John von Neumann’s Cellular Automata, Universal Constructor to the Turing Test, Artificial Intelligence to Maturana and Varela’s Autopoietic Organization, all shared the goal of understanding in what sense humans resemble a machine. This scientific and technological movement has embraced all disciplines without exceptions, not only mathematics and physics but also biology, sociology, psychology, economics etc. (...)
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  13. Combining Fast and Slow Thinking for Human-Like and Efficient Navigation in Constrained Environments.Marianna Bergamaschi Ganapini, Murray Campbell, Francesco Fabiano, Lior Horesh, Jon Lenchner, Andrea Loreggia, Nicholas Mattei, Taher Rahgooy, Francesca Rossi, Biplav Srivastava & Brent Venable - manuscript
    [Multiple authors] In this paper, we propose a general architecture that is based on fast/slow solvers and a metacognitive component. We then present experimental results on the behavior of an instance of this architecture, for AI systems that make decisions about navigating in a constrained environment. We show how combining the fast and slow decision modalities allows the system to evolve over time and gradually pass from slow to fast thinking with enough experience, and that this greatly helps in decision (...)
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  14. The Problem of Artificial Qualia.Wael Basille - 2021 - Dissertation, Sorbonne Université
    Is it possible to build a conscious machine, an artifact that has qualitative experiences such as feeling pain, seeing the redness of a flower or enjoying the taste of coffee ? What makes such experiences conscious is their phenomenal character: it is like something to have such experiences. In contemporary philosophy of mind, the question of the qualitative aspect of conscious experiences is often addressed in terms of qualia. In a pre-theoretical and intuitive sense, qualia refer to the phenomenal character (...)
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  15. AI with Alien Content and Alien Metasemantics.Herman Cappelen & Joshua Dever - forthcoming - In Ernest Lepore (ed.), Oxford Handbook of Applied Philosophy of Language. OUP.
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  16. There Is No Agency Without Attention.Paul Bello & Will Bridewell - 2017 - AI Magazine 38 (4):27-33.
    For decades AI researchers have built agents that are capable of carrying out tasks that require human-level or human-like intelligence. During this time, questions of how these programs compared in kind to humans have surfaced and led to beneficial interdisciplinary discussions, but conceptual progress has been slower than technological progress. Within the past decade, the term agency has taken on new import as intelligent agents have become a noticeable part of our everyday lives. Research on autonomous vehicles and personal assistants (...)
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  17. How Robots’ Unintentional Metacommunication Affects Human–Robot Interactions. A Systemic Approach.Piercosma Bisconti - 2021 - Minds and Machines 31 (4):487-504.
    In this paper, we theoretically address the relevance of unintentional and inconsistent interactional elements in human–robot interactions. We argue that elements failing, or poorly succeeding, to reproduce a humanlike interaction create significant consequences in human–robot relational patterns and may affect human–human relations. When considering social interactions as systems, the absence of a precise interactional element produces a general reshaping of the interactional pattern, eventually generating new types of interactional settings. As an instance of this dynamic, we study the absence of (...)
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  18. Thinking Fast and Slow in AI: The Role of Metacognition.Marianna Bergamaschi Ganapini - manuscript
    Multiple Authors - please see paper attached. -/- AI systems have seen dramatic advancement in recent years, bringing many applications that pervade our everyday life. However, we are still mostly seeing instances of narrow AI: many of these recent developments are typically focused on a very limited set of competencies and goals, e.g., image interpretation, natural language processing, classification, prediction, and many others. We argue that a better study of the mechanisms that allow humans to have these capabilities can help (...)
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  19. An Argument for the Impossibility of Machine Intelligence (Preprint).Jobst Landgrebe & Barry Smith - 2021 - Arxiv.
    Since the noun phrase `artificial intelligence' (AI) was coined, it has been debated whether humans are able to create intelligence using technology. We shed new light on this question from the point of view of themodynamics and mathematics. First, we define what it is to be an agent (device) that could be the bearer of AI. Then we show that the mainstream definitions of `intelligence' proposed by Hutter and others and still accepted by the AI community are too weak even (...)
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  20. Big Tech Corporations and AI: A Social License to Operate and Multi-Stakeholder Partnerships in the Digital Age.Marianna Capasso & Steven Umbrello - manuscript
    The pervasiveness of AI-empowered technologies across multiple sectors has led to drastic changes concerning traditional social practices and how we relate to one another. Moreover, market-driven Big Tech corporations are now entering public domains, and concerns have been raised that they may even influence public agenda and research. Therefore, this chapter focuses on assessing and evaluating what kind of business model is desirable to incentivise the AI for Social Good (AI4SG) factors. In particular, the chapter explores the implications of this (...)
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  21. Electronic Persons?Louis Caruana - 2020 - Gregorianum 101 (3):593-614.
    To describe computers and sophisticated robots, many people today have no problem using personal attributes. Alan Turing published his famous intelligence test in 1950. From that time onwards, computers have gained increasingly higher status in this regard. Computers and robots nowadays are not only intelligent. They perceive, they remember, they understand, they decide, they play and so on. Recently, another such step has occurred but, this time, many researchers are seriously concerned. In February 2017, the European Parliament passed a Resolution (...)
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  22. What Is Intelligence in the Context of AGI?Dan J. Bruiger - manuscript
    Lack of coherence in concepts of intelligence has implications for artificial intelligence. ‘Intelligence’ is an abstraction grounded in human experience while supposedly freed from the embodiment that is the basis of that experience. In addition to physical instantiation, embodiment is a condition of dependency, of an autopoietic system upon an environment, which thus matters to the system itself. The autonomy and general capability sought in artificial general intelligence implies artificially re-creating the organism’s natural condition of embodiment. That may not be (...)
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  23. Machine-Believers Learning Faiths & Knowledges: The New Gospel of Artificial Intelligence.Virgil W. Brower - 2021 - Internationales Jahrbuch Für Medienphilosophie 7 (1):97-121.
    One is occasionally reminded of Foucault's proclamation in a 1970 interview that "perhaps, one day this century will be known as Deleuzian." Less often is one compelled to update and restart with a supplementary counter-proclamation of the mathematician, David Lindley: "the twenty-first century would be a Bayesian era..." The verb tenses of both are conspicuous. // To critically attend to what is today often feared and demonized, but also revered, deployed, and commonly referred to as algorithm(s), one cannot avoid the (...)
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  24. The Social Turn of Artificial Intelligence.Nello Cristianini, Teresa Scantamburlo & James Ladyman - 2021 - AI and Society (online).
    Social machines are systems formed by material and human elements interacting in a structured way. The use of digital platforms as mediators allows large numbers of humans to participate in such machines, which have interconnected AI and human components operating as a single system capable of highly sophisticated behavior. Under certain conditions, such systems can be understood as autonomous goal-driven agents. Many popular online platforms can be regarded as instances of this class of agent. We argue that autonomous social machines (...)
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  25. Can a Robot Lie? Exploring the Folk Concept of Lying as Applied to Artificial Agents.Markus Kneer - 2021 - Cognitive Science 45 (10):e13032.
    The potential capacity for robots to deceive has received considerable attention recently. Many papers explore the technical possibility for a robot to engage in deception for beneficial purposes (e.g., in education or health). In this short experimental paper, I focus on a more paradigmatic case: robot lying (lying being the textbook example of deception) for nonbeneficial purposes as judged from the human point of view. More precisely, I present an empirical experiment that investigates the following three questions: (a) Are ordinary (...)
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  26. Cyber Security and Dehumanisation.Marie Oldfield - 2021 - 5th Digital Geographies Research Group Annual Symposium.
    Artificial Intelligence is becoming widespread and as we continue ask ‘can we implement this’ we neglect to ask ‘should we implement this’. There are various frameworks and conceptual journeys one should take to ensure a robust AI product; context is one of the vital parts of this. AI is now expected to make decisions, from deciding who gets a credit card to cancer diagnosis. These decisions affect most, if not all, of society. As developers if we do not understand or (...)
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  27. Responsible Nudging for Social Good: New Healthcare Skills for AI-Driven Digital Personal Assistants.Marianna Capasso & Steven Umbrello - 2022 - Medicine, Health Care and Philosophy 25 (1):11-22.
    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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  28. 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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  29. Citizenship as the Exception to the Rule: An Addendum.Tyler L. Jaynes - 2021 - AI and Society 36 (3):911-930.
    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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  30. 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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  31. 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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  32. Science Fiction and Philosophy: From Time Travel to Superintelligence (Wiley-Blackwell, 2016). [REVIEW]Stefano Bigliardi - 2020 - Journal of Science Fiction and Philosophy 3:1-19.
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  33. 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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  34. 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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  35. Varieties of Artifacts: Embodied, Perceptual, Cognitive, and Affective.Richard Heersmink - 2021 - Topics in Cognitive Science (4):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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  36. 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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  37. 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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  38. 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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  39. An Empathy Imitation Game: Empathy Turing Test for Care- and Chat-Bots.Jeremy Howick, Jessica Morley & Luciano Floridi - 2021 - Minds and Machines 31 (3):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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  40. 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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  41. 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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  42. 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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  43. 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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  44. 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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  45. 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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  46. 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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  47. 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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  48. 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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  49. In Defence of the Hivemind Society.John Danaher & Steve Petersen - 2020 - Neuroethics 14 (2):253-267.
    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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  50. 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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