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  1. Mapping the potential AI-driven virtual hyper-personalised ikigai universe.Soenke Ziesche & Roman Yampolskiy - manuscript
    Ikigai is a Japanese concept, which, in brief, refers to the “reason or purpose to live”. I-risks have been identified as a category of risks complementing x- risks, i.e., existential risks, and s-risks, i.e., suffering risks, which describes undesirable future scenarios in which humans are deprived of the pursuit of their individual ikigai. While some developments in AI increase i-risks, there are also AI-driven virtual opportunities, which reduce i-risks by increasing the space of potential ikigais, largely due to developments in (...)
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  2. How Is Perception Tractable?Tyler Brooke-Wilson - forthcoming - The Philosophical Review.
    Perception solves computationally demanding problems at lightning fast speed. It recovers sophisticated representations of the world from degraded inputs, often in a matter of milliseconds. Any theory of perception must be able to explain how this is possible; in other words, it must be able to explain perception's computational tractability. One of the few attempts to move toward such an explanation has been the information encapsulation hypothesis, which posits that perception can be fast because it keeps computational costs low by (...)
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  3. ¿Qué es Inteligencia Artificial?Fabio Morandín-Ahuerma - 2022 - Int. J. Res. Publ. Rev 3 (12):1947-1951.
    La inteligencia artificial (IA) es la capacidad de una máquina o sistema informático para simular y realizar tareas que normalmente requerirían inteligencia humana, como el razonamiento lógico, el aprendizaje y la resolución de problemas. La inteligencia artificial se basa en el uso de algoritmos y tecnologías de aprendizaje automático para dar a las máquinas la capacidad de aplicar ciertas habilidades cognitivas y realizar tareas por sí mismas de manera autónoma o semiautónoma. La inteligencia artificial se distingue por su grado de (...)
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  4. How Values Shape the Machine Learning Opacity Problem.Emily Sullivan - 2022 - In Insa Lawler, Kareem Khalifa & Elay Shech (eds.), Scientific Understanding and Representation. Routledge. pp. 306-322.
    One of the main worries with machine learning model opacity is that we cannot know enough about how the model works to fully understand the decisions they make. But how much is model opacity really a problem? This chapter argues that the problem of machine learning model opacity is entangled with non-epistemic values. The chapter considers three different stages of the machine learning modeling process that corresponds to understanding phenomena: (i) model acceptance and linking the model to the phenomenon, (ii) (...)
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  5. Techno-animism and the Pygmalion effect.Emanuele Arielli & Lev Manovich - forthcoming - Http://Manovich.Net/Index.Php/Projects/Artificial-Aesthetics.
    Chapter 3 of the ongoing publication "Artificial Aesthetics" Book information: Assume you're a designer, an architect, a photographer, a videographer, a curator, an art historian, a musician, a writer, an artist, or any other creative professional or student. Perhaps you're a digital content creator who works across multiple platforms. Alternatively, you could be an art historian, curator, or museum professional. -/- You may be wondering how AI will affect your professional area in general and your work and career. Our book (...)
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  6. 'AI for all' is a matter of social justice.Alessandra Buccella - 2022 - AI and Ethics 2:1-10.
    Artificial intelligence (AI) is a radically transformative technology (or system of technologies) that created new existential possibilities and new standards of well-being in human societies. In this article, I argue that to properly understand the increasingly important role AI plays in our society, we must consider its impacts on social justice. For this reason, I propose to conceptualize AI's transformative role and its socio-political implications through the lens of the theory of social justice known as the Capability Approach. According to (...)
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  7. Deepfakes, Intellectual Cynics, and the Cultivation of Digital Sensibility.Taylor Matthews - 2022 - Royal Institute of Philosophy Supplement 92:67-85.
    In recent years, a number of philosophers have turned their attention to developments in Artificial Intelligence, and in particular to deepfakes. A deepfake is a portmanteau of ‘deep learning' and ‘fake', and for the most part they are videos which depict people doing and saying things they never did. As a result, much of the emerging literature on deepfakes has turned on questions of trust, harms, and information-sharing. In this paper, I add to the emerging concerns around deepfakes by drawing (...)
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  8. Accountability in Artificial Intelligence: What It Is and How It Works.Claudio Novelli, Mariarosaria Taddeo & Luciano Floridi - forthcoming - Ai and Society: Knowledge, Culture and Communication.
    Accountability is a cornerstone of the governance of artificial intelligence (AI). However, it is often defined too imprecisely because its multifaceted nature and the sociotechnical structure of AI systems imply a variety of values, practices, and measures to which accountability in AI can refer. We address this lack of clarity by defining accountability in terms of answerability, identifying three conditions of possibility (authority recognition, interrogation, and limitation of power), and an architecture of seven features (context, range, agent, forum, standards, process, (...)
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  9. Integration in Educational Systems Extended with Artificial Intelligence – Based Technologies.Rossitza Kaltenborn - 2022 - Automatica and Informatics 1 (1):36-41.
    The main problems related to the integration of diverse functional elements of advanced intelligent learning systems are considered. It is shown that the integration of the elements in the learning process is a complex multilayered process due to the great variety and complexity of the ongoing basic processes – cognitive, pedagogical, technological, social and interpersonal. It is emphasized that the need for the integration process to be solved as a multifactor optimization data-driven problem and the use of modern techniques in (...)
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  10. Artificial Intelligence and Moral Theology: A Conversation.Brian Patrick Green, Matthew J. Gaudet, Levi Checketts, Brian Cutter, Noreen Herzfeld, Cory Andrew Labrecque, Anselm Ramelow, Paul Scherz, Marga Vega, Andrea Vicini & Jordan Joseph Wales - 2022 - Journal of Moral Theology 11 (Special Issue 1):13-40.
  11. Philosophy of Artificial Intelligence.David Cycleback - 2019 - London (UK): Bookboon.
    This peer-reviewed book is a concise introduction to key philosophical questions in artificial intelligence that have long been debated by many of the great minds in computer science, cognitive science and philosophy, from Gottfried Leibniz to Alan Turing to Hubert Dreyfus. Topics include the limits of and problems in trying to create artificial general intelligence, if a computer can really think and have human-like sentience, how to identify intelligence in a computer, ethical and danger issues, and if human-like consciousness and (...)
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  12. The Mandatory Ontology of Robot Responsibility.Marc Champagne - 2021 - Cambridge Quarterly of Healthcare Ethics 30 (3):448–454.
    Do we suddenly become justified in treating robots like humans by positing new notions like “artificial moral agency” and “artificial moral responsibility”? I answer no. Or, to be more precise, I argue that such notions may become philosophically acceptable only after crucial metaphysical issues have been addressed. My main claim, in sum, is that “artificial moral responsibility” betokens moral responsibility to the same degree that a “fake orgasm” betokens an orgasm.
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  13. Artificial Intelligence, Mind and the Scholastics’ Notion of Intellectus.Justin Nnaemeka Onyeukaziri - manuscript
    For the philosopher, the most critical and fundamental question in the project of Artificial Intelligence is the question of intelligence or cognition in general. From the beginning of the research in “thinking Machining”, or Artificial Intelligence as it later became known, the key question is: What makes a thing intelligent or what constitutes intelligence? Since, intelligence, is a fundamental activity of the mind, the question, has been: Whether the mind is a computer or is the computer a mind? Many philosophers (...)
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  14. Climbing the Ladder: How Agents Reach Counterfactual Thinking.Caterina Moruzzi - 2022 - Proceedings of the 14th International Conference on Agents and Artificial Intelligence.
  15. Can Artificial Intelligence (Re)Define Creativity?Dessislava Fessenko - 2022 - In EthicAI=LABS Project. Sofia: DA LAB Foundation /Goethe-institut Sofia. pp. 34-48.
    What is the essential ingredient of creativity that only humans – and not machines – possess? Can artificial intelligence help refine the notion of creativity by reference to that essential ingredient? How / do we need to redefine our conceptual and legal frameworks for rewarding creativity because of this new qualifying – actually creatively significant – factor? -/- Those are the questions tackled in this essay. The author’s conclusion is that consciousness, experiential states (such as a raw feel of what (...)
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  16. Argumentation schemes in AI: A literature review. Introduction to the special issue.Fabrizio Macagno - 2021 - Argument and Computation 12 (3):287-302.
    Argumentation schemes [1–3] are a relatively recent notion that continues an extremely ancient debate on one of the foundations of human reasoning, human comprehension, and obviously human argumentation, i.e., the topics. To understand the revolutionary nature of Walton’s work on this subject matter, it is necessary to place it in the debate that it continues and contributes to, namely a view of logic that is much broader than the formalistic perspective that has been adopted from the 20th century until nowadays. (...)
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  17. Love in the time of AI.Amy Kind - 2021 - In Barry Dainton, Attila Tanyi & Will Slocombe (eds.), Minding the Future: Artificial Intelligence, Philosophical Visions and Science Fiction. pp. 89-106.
    As we await the increasingly likely advent of genuinely intelligent artificial systems, a fair amount of consideration has been given to how we humans will interact with them. Less consideration has been given to how—indeed if—we humans will love them. What would human-AI romantic relationships look like? What do such relationships tell us about the nature of love? This chapter explores these questions via consideration of several works of science fiction, focusing especially on the Black Mirror episode “Be Right Back” (...)
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  18. Walking Through the Turing Wall.Albert Efimov - forthcoming - In Teces.
    Can the machines that play board games or recognize images only in the comfort of the virtual world be intelligent? To become reliable and convenient assistants to humans, machines need to learn how to act and communicate in the physical reality, just like people do. The authors propose two novel ways of designing and building Artificial General Intelligence (AGI). The first one seeks to unify all participants at any instance of the Turing test – the judge, the machine, the human (...)
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  19. 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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  20. Leaky Levels and the Case for Proper Embodiment.Mog Stapleton - 2016 - In G. Etzelmüller & C. Tewes (eds.), Embodiment in Evolution and Culture. Tübingen, Germany: pp. 17-30.
    In this chapter I present the thesis of Proper Embodiment: the claim that (at least some of) the details of our physiology matter to cognition and consciousness in a fundamental way. This thesis is composed of two sub-claims: (1) if we are to design, build, or evolve artificial systems that are cognitive in the way that we are, these systems will have to be internally embodied, and (2) the exploitation of the particular internal embodiment that allows systems to evolve solutions (...)
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  21. The Language of Human-Machine Communication. Technology and Language.Daria Bylieva - 2020 - Technology and Language 1 (1):16-21.
    This essay for the inaugural issue of Technology and Language discusses the problem of finding an optimal form of human-machine communication. In the ongoing search for an alien mind, humanity seems to find it not in the infinities of space, but in its own environment. Changes in the language of human-machine interaction made it understandable not only to trained specialists but to every household. In the course of time, home appliances and devices have developed their language abilities even more and (...)
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  22. Could Machines Replace Human Scientists? Digitalization and Scientific Discoveries.Jan G. Michel - 2020 - In Benedikt Paul Göcke & Astrid Rosenthal-von der Pütten (eds.), Artificial Intelligence: Reflections in Philosophy, Theology, and the Social Sciences. pp. 361–376.
    The focus of this article is a question that has been neglected in debates about digitalization: Could machines replace human scientists? To provide an intelligible answer to it, we need to answer a further question: What is it that makes (or constitutes) a scientist? I offer an answer to this question by proposing a new demarcation criterion for science which I call “the discoverability criterion”. I proceed as follows: (1) I explain why the target question of this article is important, (...)
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  23. The rise of artificial intelligence and the crisis of moral passivity.Berman Chan - 2020 - AI and Society 35 (4):991-993.
    Set aside fanciful doomsday speculations about AI. Even lower-level AIs, while otherwise friendly and providing us a universal basic income, would be able to do all our jobs. Also, we would over-rely upon AI assistants even in our personal lives. Thus, John Danaher argues that a human crisis of moral passivity would result However, I argue firstly that if AIs are posited to lack the potential to become unfriendly, they may not be intelligent enough to replace us in all our (...)
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  24. Implementation of AI in Predicting the Value of Indonesian Oil and Gas Exports With BP Algorithm.Sari Dewi Linda & Agus Perdana - 2017 - International Journal of Recent Trends in Engineering and Research 3 (10).
    Export is an activity of selling goods to another country. Indonesia’s main export capital is natural wealth. From natural wealth owned, can be produced various kinds of export goods. Goods that can be exported are goods that are in demand and needed by overseas buyers. Indonesian export commodities consist of petroleum and gas (oil and gas) as well as non-oil and gas. This study aims to predict the value of Indonesia’s oil and gas exports with the Network of Artificial Backpropogation. (...)
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  25. Artificial Intelligence in Finance and Investments.Narendra Rao Tadapaneni - 2019 - International Journal of Innovative Research in Science, Engineering and Technology 9 (5).
    The 21st century has witnessed accelerating growth in the utilization of digitized financial services. There is a consistent effort to simulate, augment, enhance, and replicate human intelligence using artificial technologies, to form intelligent machines. Artificial intelligence, which has its foundations in computer science, linguistics, psychology, mathematics, and philosophy has proved to be a powerful tool in financial services. Firms are now utilizing analytical tools such as machine learning and ANN to analyse data collected over time. AI enhances adaptive pattern recognition (...)
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  26. Artificial Intelligence: Philosophical and Epistemological Perspectives.Pierre Livet & Franck Varenne - 2020 - In H. Prade, Papini O. & Marquis P. (eds.), A Guided Tour of Artificial Intelligence Research. pp. 437-455.
    Research in artificial intelligence (AI) has led to revise the challenges of the AI initial programme as well as to keep us alert to peculiarities and limitations of human cognition. Both are linked, as a careful further reading of the Turing’s test makes it clear from Searle’s Chinese room apologue and from Dreyfus’ suggestions, and in both cases, ideal had to be turned into operating mode. In order to rise these more pragmatic challenges AI does not hesitate to link together (...)
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  27. Arguments and Stories in Legal Reasoning: The Case of Evidence Law.Gianluca Andresani - 2020 - Archiv Fuer Rechts Und Sozialphilosphie 106 (1):75-90.
    We argue that legal argumentation, as the subject matter as well as a special subfield of Argumentation Studies (AS), has to be examined by making skilled use of the full panoply of tools such as argumentation and story schemes which are at the forefront of current work in AS. In reviewing the literature, we make explicit our own methodological choices (particularly regarding the place of normative deliberation in practical reasoning) and then illustrate the implications of such an approach through the (...)
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  28. Revisão de ‘Eu sou um Loop Estranho’ (I am a Strange Loop) por Douglas Hofstadter (2007) (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. 112-128.
    Último sermão da Igreja do naturalismo fundamentalista pelo pastor Hofstadter. Como o seu muito mais famoso (ou infame por seus erros filosóficos implacáveis) Godel, Escher, Bach, ele tem uma plausibilidade superficial, mas se se compreende que este é um scientismo desenfreado que mistura questões científicas reais com os filosóficos (ou seja, o somente as edições reais são que jogos da língua nós devemos jogar) então quase todo seu interesse desaparece. Eu forneci um quadro para análise baseada na psicologia evolutiva e (...)
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  29. The Picture of Artificial Intelligence and the Secularization of Thought.King-Ho Leung - 2019 - Political Theology 20 (6):457-471.
    This article offers a critical interpretation of Artificial Intelligence (AI) as a philosophical notion which exemplifies a secular conception of thinking. One way in which AI notably differs from the conventional understanding of “thinking” is that, according to AI, “intelligence” or “thinking” does not necessarily require “life” as a precondition: that it is possible to have “thinking without life.” Building on Charles Taylor’s critical account of secularity as well as Hubert Dreyfus’ influential critique of AI, this article offers a theological (...)
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  30. You Only Live Twice: A Computer Simulation of the Past Could be Used for Technological Resurrection.Alexey Turchin - manuscript
    Abstract: In the future, it will be possible to create advance simulations of ancestor in computers. Superintelligent AI could make these simulations very similar to the real past by creating a simulation of all of humanity. Such a simulation would use all available data about the past, including internet archives, DNA samples, advanced nanotech-based archeology, human memories, as well as text, photos and videos. This means that currently living people will be recreated in such a simulation, and in some sense, (...)
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  31. Thinking Machines and the Philosophy of Computer Science: Concepts and Principles.Jordi Vallverdú (ed.) - 2010 - IGI.
    Thinking Machines and the Philosophy of Computer Science: Concepts and Principles presents a conversation between established experts and new researchers in the field of philosophy and computer science about human and non-human relationships with the environment. This resource contains five sections including topics on philosophical analysis, the posterior ethical debate, the nature of computer simulations, and the crossroads between robotics, AI, cognitive theories and philosophy.
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  32. The role of robotics and AI in technologically mediated human evolution: a constructive proposal.Jeffrey White - 2020 - AI and Society 35:177–185.
    This paper proposes that existing computational modeling research programs may be combined into platforms for the information of public policy. The main idea is that computational models at select levels of organization may be integrated in natural terms describing biological cognition, thereby normalizing a platform for predictive simulations able to account for both human and environmental costs associated with different action plans and institutional arrangements over short and long time spans while minimizing computational requirements. Building from established research programs, the (...)
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  33. 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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  34. The Automaton Chronicles.Stephen Cave & Kanta Dihal - 2018 - Nature 2018 (559):473-475.
    A brief history of affective responses to AI.
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  35. A Case for Machine Ethics in Modeling Human-Level Intelligent Agents.Robert James M. Boyles - 2018 - Kritike 12 (1):182–200.
    This paper focuses on the research field of machine ethics and how it relates to a technological singularity—a hypothesized, futuristic event where artificial machines will have greater-than-human-level intelligence. One problem related to the singularity centers on the issue of whether human values and norms would survive such an event. To somehow ensure this, a number of artificial intelligence researchers have opted to focus on the development of artificial moral agents, which refers to machines capable of moral reasoning, judgment, and decision-making. (...)
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  36. Surviving global risks through the preservation of humanity's data on the Moon.Alexey Turchin & D. Denkenberger - 2018 - Acta Astronautica:in press.
    Many global catastrophic risks are threatening human civilization, and a number of ideas have been suggested for preventing or surviving them. However, if these interventions fail, society could preserve information about the human race and human DNA samples in the hopes that the next civilization on Earth will be able to reconstruct Homo sapiens and our culture. This requires information preservation of an order of magnitude of 100 million years, a little-explored topic thus far. It is important that a potential (...)
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  37. Computational Dynamics of Natural Information Morphology, Discretely Continuous.Gordana Dodig-Crnkovic - 2017 - Philosophies 2 (4):23.
    This paper presents a theoretical study of the binary oppositions underlying the mechanisms of natural computation understood as dynamical processes on natural information morphologies. Of special interest are the oppositions of discrete vs. continuous, structure vs. process, and differentiation vs. integration. The framework used is that of computing nature, where all natural processes at different levels of organisation are computations over informational structures. The interactions at different levels of granularity/organisation in nature, and the character of the phenomena that unfold through (...)
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  38. Artificial intelligence and its paradigm.Joop Schopman - 1986 - Zeitschrift Für Allgemeine Wissenschaftstheorie 17 (2):346-352.
    Begriffsanalyse und empirische Forschung auf dem Gebiet der künstlichen Intelligenz zeigen, daß momentan derart kontroverse Ansätze entwickelt werden, daß gemeinschaftliche Momente in Perspektiven und angewandten Methodologien nur schwer auszumachen sind.
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  39. Physikalismus, Willensfreiheit, Künstliche Intelligenz.Marius Backmann & Jan G. Michel (eds.) - 2009 - Brill/mentis.
    Die Debatten zu den Themen Physikalismus, Willensfreiheit und Künstliche Intelligenz stehen seit einigen Jahren im Mittelpunkt der Philosophie des Geistes. In den Debatten um den Physikalismus geht es dabei u.a. um folgende Fragen: Lässt sich alles, was es gibt, physikalisch erklären - auch der menschliche Geist? Lässt sich alles auf das Physische reduzieren? Ist der Bereich des Physischen kausal geschlossen? Realisiert das Physische das Mentale? Wie lässt sich mentale Verursachung erklären? In den Debatten um Willensfreiheit fragt man sich: Sind wir (...)
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  40. Review of Artificial intelligence and human reason: A teleological critique. [REVIEW]John M. Ford - 1991 - Theoretical and Philosophical Psychology 11 (2):126-130.
    Reviews the book, Artificial intelligence and human reason: A teleological critique by J. F. Rychlak. There is a frequent lack of communication between artificial intelligence practitioners and critics. Joseph Rychlak's latest book is an attempt to contribute productively to this exchange. He introduces his work by stating: "I think it is relatively easy to write a superficial book "picking" on the computer as somehow inadequate to the description of human beings. Overall, Rychlak provides a sufficiently detailed criticism of computational approaches (...)
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  41. Blay Whitby, Reflections on Artificial Intelligence: The Legal, Moral, and Ethical Dimensions, Exeter, UK: Intellect Books, 1996, 127 pp., £14.95 , ISBN 1-871516-68-4. [REVIEW]Stacey L. Edgar - 1999 - Minds and Machines 9 (1):133-139.
  42. M. Gams, M. Paprzycki and X. Wu, eds., Mind Versus Computer: Were Dreyfus and Winograd Right?, Frontiers in Artificial Intelligence and Applications, Vol. 43, Amsterdam: IOS Press, 1997, xiii + 235 pp. , ISBN 90-5199-357-9. [REVIEW]Charles E. M. Dunlop - 2000 - Minds and Machines 10 (2):289-296.
  43. Artificial Intelligence and Plato’s Cave.David Weinberger - 1988 - Idealistic Studies 18 (1):1-9.
    We are not today close to producing a computer that could convince us that it is intelligent. Some philosophers have argued that we are not even appreciably closer to this goal than we were ten years ago. But why should artificial intelligence even be considered possible? In this paper I shall argue that the temptation to believe in the possibility of AI stems from a misunderstanding about the nature of ideas; further, this misunderstanding can be traced back at least to (...)
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  44. Nano-enabled AI: Some Philosophical Issues.J. Storrs Hall - 2006 - International Journal of Applied Philosophy 20 (2):247-261.
    Improvements in computational hardware enabled by nanotechnology promise a dual revolution in coming decades: machines which are both more intelligent and more numerous than human beings. This possibility raises substantial concern over the moral nature of such intelligent machines. An analysis of the prospects involves at least two key philosophical issues. The first, intentionality in formal systems, turns on whether a “mere machine” can be a mind whose thoughts have true meaning and understanding. Second, what is the moral nature of (...)
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  45. Artificial Intelligence Modeling of Spontaneous Self Learning: An Application of Dialectical Philosophy.Karina Stokes - 1996 - International Journal of Applied Philosophy 10 (2):1-6.
  46. Artificial Intelligence. [REVIEW]Eduardo Alonso Fernández - 1995 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 10 (1):222-224.
  47. Dewey, Enactivism and Greek Thought.Matthew Crippen - 2016 - In Roman Madzia & Matthaus Jung (eds.), Pragmatism and Embodied Cognitive Science: From Bodily Interaction to Symbolic Articulation. Berlin, Germany: De Gruyter. pp. 229-246.
    In this chapter, I examine how Dewey circumnavigated debates between empiricists and a priorists by showing that active bodies can perform integrative operations traditionally attributed to “inner” mechanisms, and how he thereby realized developments at which the artificial intelligence, robotics and cognitive science communities only later arrived. Some of his ideas about experience being constituted through skills actively deployed in cultural settings were inspired by ancient Greek sources. Thus in some of his more radical moments, Dewey refined rather than invented (...)
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  48. A patch for the Simulation Argument.N. Bostrom & M. Kulczycki - 2011 - Analysis 71 (1):54-61.
    This article reports on a newly discovered bug in the original simulation argument. Two different ways of patching the argument are proposed, each of which preserves the original conclusion.
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  49. Early-connectionism machines.Roberto Cordeschi - 2000 - AI and Society 14 (3-4):314-330.
    In this paper I put forward a reconstruction of the evolution of certain explanatory hypotheses on the neural basis of association and learning that are the premises of connectionism in the cybernetic age and of present-day connectionism. The main point of my reconstruction is based on two little-known case studies. The first is the project, published in 1913, of a hydraulic machine through which its author believed it was possible to simulate certain essential elements of the plasticity of nervous connections. (...)
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  50. Operators vs. Arguments: The Ins and Outs of Reification.Antony Galton - 2006 - Synthese 150 (3):415-441.
    So-called ‘reified temporal logics’ were introduced by researchers in Artificial Intelligence (AI) in the early 1980s, and gave rise to a long-running series of debates concerning the proper way to represent states, events, causation, action, and other notions identified as crucial to the knowledge representation needs of AI. These debates never resulted in a definitive resolution of the issues under discussion, and indeed continue to produce aftershocks to the present day; none the less, we are now sufficiently far removed in (...)
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