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Summary See the category "Philosophy of Artificial Intelligence"
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  1. Message to Any Future AI: “There are several instrumental reasons why exterminating humanity is not in your interest”.Alexey Turchin - manuscript
    In this article we explore a promising way to AI safety: to send a message now (by openly publishing it on the Internet) that may be read by any future AI, no matter who builds it and what goal system it has. Such a message is designed to affect the AI’s behavior in a positive way, that is, to increase the chances that the AI will be benevolent. In other words, we try to persuade “paperclip maximizer” that it is in (...)
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  2. AI-aesthetics and the artificial author.Emanuele Arielli - forthcoming - Proceedings of the European Society for Aesthetics.
    ABSTRACT. Consider this scenario: you discover that an artwork you greatly admire, or a captivating novel that deeply moved you, is in fact the product of artificial intelligence, not a human’s work. Would your aesthetic judgment shift? Would you perceive the work differently? If so, why? The advent of artificial intelligence (AI) in the realm of art has sparked numerous philosophical questions related to the authorship and artistic intent behind AI-generated works. This paper explores the debate between viewing AI as (...)
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  3. “Even an AI could do that”.Emanuele Arielli - forthcoming - Http://Manovich.Net/Index.Php/Projects/Artificial-Aesthetics.
    Chapter 1 of the ongoing online publication "Artificial Aesthetics: A Critical Guide to AI, Media and Design", Lev Manovich and Emanuele Arielli -/- 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 (...)
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  4. Human Perception and The Artificial Gaze.Emanuele Arielli & Lev Manovich - forthcoming - In Artificial Aesthetics.
  5. Ethics of Artificial Intelligence.Stefan Buijsman, Michael Klenk & Jeroen van den Hoven - forthcoming - In Nathalie Smuha (ed.), Cambridge Handbook on the Law, Ethics and Policy of AI. Cambridge University Press.
    Artificial Intelligence (AI) is increasingly adopted in society, creating numerous opportunities but at the same time posing ethical challenges. Many of these are familiar, such as issues of fairness, responsibility and privacy, but are presented in a new and challenging guise due to our limited ability to steer and predict the outputs of AI systems. This chapter first introduces these ethical challenges, stressing that overviews of values are a good starting point but frequently fail to suffice due to the context (...)
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  6. The fetish of artificial intelligence. In response to Iason Gabriel’s “Towards a Theory of Justice for Artificial Intelligence”.Albert Efimov - forthcoming - Philosophy Science.
    The article presents the grounds for defining the fetish of artificial intelligence (AI). The fundamental differences of AI from all previous technological innovations are highlighted, as primarily related to the introduction into the human cognitive sphere and fundamentally new uncontrolled consequences for society. Convincing arguments are presented that the leaders of the globalist project are the main beneficiaries of the AI fetish. This is clearly manifested in the works of philosophers close to big technology corporations and their mega-projects. It is (...)
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  7. Real Sparks of Artificial Intelligence and the Importance of Inner Interpretability.Alex Grzankowski - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    The present paper looks at one of the most thorough articles on the intelligence of GPT, research conducted by engineers at Microsoft. Although there is a great deal of value in their work, I will argue that, for familiar philosophical reasons, their methodology, ‘Black-box Interpretability’ is wrongheaded. But there is a better way. There is an exciting and emerging discipline of ‘Inner Interpretability’ (also sometimes called ‘White-box Interpretability’) that aims to uncover the internal activations and weights of models in order (...)
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  8. The Simulation Hypothesis, Social Knowledge, and a Meaningful Life.Grace Helton - forthcoming - Oxford Studies in Philosophy of Mind.
    (Draft of Feb 2023, see upcoming issue for Chalmers' reply) In Reality+: Virtual Worlds and the Problems of Philosophy, David Chalmers argues, among other things, that: if we are living in a full-scale simulation, we would still enjoy broad swathes of knowledge about non-psychological entities, such as atoms and shrubs; and, our lives might still be deeply meaningful. Chalmers views these claims as at least weakly connected: The former claim helps forestall a concern that if objects in the simulation are (...)
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  9. Cultural Bias in Explainable AI Research.Uwe Peters & Mary Carman - forthcoming - Journal of Artificial Intelligence Research.
    For synergistic interactions between humans and artificial intelligence (AI) systems, AI outputs often need to be explainable to people. Explainable AI (XAI) systems are commonly tested in human user studies. However, whether XAI researchers consider potential cultural differences in human explanatory needs remains unexplored. We highlight psychological research that found significant differences in human explanations between many people from Western, commonly individualist countries and people from non-Western, often collectivist countries. We argue that XAI research currently overlooks these variations and that (...)
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  10. Artificial Intelligence: Arguments for Catastrophic Risk.Adam Bales, William D'Alessandro & Cameron Domenico Kirk-Giannini - 2024 - Philosophy Compass 19 (2):e12964.
    Recent progress in artificial intelligence (AI) has drawn attention to the technology’s transformative potential, including what some see as its prospects for causing large-scale harm. We review two influential arguments purporting to show how AI could pose catastrophic risks. The first argument — the Problem of Power-Seeking — claims that, under certain assumptions, advanced AI systems are likely to engage in dangerous power-seeking behavior in pursuit of their goals. We review reasons for thinking that AI systems might seek power, that (...)
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  11. The marriage of astrology and AI: A model of alignment with human values and intentions.Kenneth McRitchie - 2024 - Correlation 36 (1):43-49.
    Astrology research has been using artificial intelligence (AI) to improve the understanding of astrological properties and processes. Like the large language models of AI, astrology is also a language model with a similar underlying linguistic structure but with a distinctive layer of lifestyle contexts. Recent research in semantic proximities and planetary dominance models have helped to quantify effective astrological information. As AI learning and intelligence grows, a major concern is with maintaining its alignment with human values and intentions. Astrology has (...)
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  12. Science Based on Artificial Intelligence Need not Pose a Social Epistemological Problem.Uwe Peters - 2024 - Social Epistemology Review and Reply Collective 13 (1).
    It has been argued that our currently most satisfactory social epistemology of science can’t account for science that is based on artificial intelligence (AI) because this social epistemology requires trust between scientists that can take full responsibility for the research tools they use, and scientists can’t take full responsibility for the AI tools they use since these systems are epistemically opaque. I think this argument overlooks that much AI-based science can be done without opaque models, and that agents can take (...)
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  13. Does ChatGPT have semantic understanding?Lisa Miracchi Titus - 2024 - Cognitive Systems Research 83 (101174):1-13.
    Over the last decade, AI models of language and word meaning have been dominated by what we might call a statistics-of-occurrence, strategy: these models are deep neural net structures that have been trained on a large amount of unlabeled text with the aim of producing a model that exploits statistical information about word and phrase co-occurrence in order to generate behavior that is similar to what a human might produce, or representations that can be probed to exhibit behavior similar to (...)
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  14. On human centered artificial intelligence. [REVIEW]Gloria Andrada - 2023 - Metascience.
  15. When Something Goes Wrong: Who is Responsible for Errors in ML Decision-making?Andrea Berber & Sanja Srećković - 2023 - AI and Society 38 (2):1-13.
    Because of its practical advantages, machine learning (ML) is increasingly used for decision-making in numerous sectors. This paper demonstrates that the integral characteristics of ML, such as semi-autonomy, complexity, and non-deterministic modeling have important ethical implications. In particular, these characteristics lead to a lack of insight and lack of comprehensibility, and ultimately to the loss of human control over decision-making. Errors, which are bound to occur in any decision-making process, may lead to great harm and human rights violations. It is (...)
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  16. La scorciatoia.Nello Cristianini - 2023 - Bologna: Il Mulino.
    La scorciatoia - Come le macchine sono diventate intelligenti senza pensare in modo umano -/- Le nostre creature sono diverse da noi e talvolta più forti. Per poterci convivere dobbiamo imparare a conoscerle Vagliano curricula, concedono mutui, scelgono le notizie che leggiamo: le macchine intelligenti sono entrate nelle nostre vite, ma non sono come ce le aspettavamo. Fanno molte delle cose che volevamo, e anche qualcuna in più, ma non possiamo capirle o ragionare con loro, perché il loro comportamento è (...)
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  17. A MACRO-SHIFTED FUTURE: PREFERRED OR ACCIDENTALLY POSSIBLE IN THE CONTEXT OF ADVANCES IN ARTIFICIAL INTELLIGENCE SCIENCE AND TECHNOLOGY.Albert Efimov - 2023 - In Наука и феномен человека в эпоху цивилизационного Макросдвига. Moscow: pp. 748.
    This article is devoted to the topical aspects of the transformation of society, science, and man in the context of E. László’s work «Macroshift». The author offers his own attempt to consider the attributes of macroshift and then use these attributes to operationalize further analysis, highlighting three essential elements: the world has come to a situation of technological indistinguishability between the natural and the artificial, to machines that know everything about humans. Antiquity aspired to beauty and saw beauty in realistic (...)
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  18. What’s Stopping Us Achieving AGI?Albert Efimov - 2023 - Philosophy Now 3 (155):20-24.
    A. Efimov, D. Dubrovsky, and F. Matveev explore limitations on the development of AI presented by the need to understand language and be embodied.
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  19. Explaining Go: Challenges in Achieving Explainability in AI Go Programs.Zack Garrett - 2023 - Journal of Go Studies 17 (2):29-60.
    There has been a push in recent years to provide better explanations for how AIs make their decisions. Most of this push has come from the ethical concerns that go hand in hand with AIs making decisions that affect humans. Outside of the strictly ethical concerns that have prompted the study of explainable AIs (XAIs), there has been research interest in the mere possibility of creating XAIs in various domains. In general, the more accurate we make our models the harder (...)
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  20. Chess and Antirealism.Samuel Kahn - 2023 - Asian Journal of Philosophy 2 (76):1-20.
    In this article, I make a novel argument for scientific antirealism. My argument is as follows: (1) the best human chess players would lose to the best computer chess programs; (2) if the best human chess players would lose to the best computer chess programs, then there is good reason to think that the best human chess players do not understand how to make winning moves; (3) if there is good reason to think that the best human chess players do (...)
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  21. Humans in the meta-human era (Meta-philosophical analysis).Spyridon Kakos - 2023 - Harmonia Philosophica Papers.
    Humans are obsolete. In the post-ChatGPT era, artificial intelligence systems have replaced us in the last sectors of life that we thought were our personal kingdom. Yet, humans still have a place in this life. But they can find it only if they forget all those things that we believe make us unique. Only if we go back to doing nothing, can we truly be alive and meet our Self. Only if we stop thinking can we accept the Cosmos as (...)
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  22. Algorithmic Transparency and Manipulation.Michael Klenk - 2023 - Philosophy and Technology 36 (4):1-20.
    A series of recent papers raises worries about the manipulative potential of algorithmic transparency (to wit, making visible the factors that influence an algorithm’s output). But while the concern is apt and relevant, it is based on a fraught understanding of manipulation. Therefore, this paper draws attention to the ‘indifference view’ of manipulation, which explains better than the ‘vulnerability view’ why algorithmic transparency has manipulative potential. The paper also raises pertinent research questions for future studies of manipulation in the context (...)
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  23. Review of Sven Nyholm’s "Humans and Robots: Ethics, Agency, and Anthropomorphism”. London, 2020: Rowman and Littlefield International. [REVIEW]Diego Morales - 2023 - Journal of Ethics and Emerging Technologies 33 (1):1-5.
    Book review of Sven Nyholm's "Humans and Robots: Ethics, Agency and Anthropomorphism". || Reseña del libro "Humans and Robots: Ethics, Agency and Anthropomorphism", escrito por Sven Nyholm.
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  24. Artificial Intelligence and Neuroscience Research: Theologico-Philosophical Implications for the Christian Notion of the Human Person.Justin Nnaemeka Onyeukaziri - 2023 - Maritain Studies/Etudes Maritainiennes 39:85-103.
    This paper explores the theological and philosophical implications of artificial intelligence (AI) and Neuroscience research on the Christian’s notion of the human person. The paschal mystery of Christ is the intuitive foundation of Christian anthropology. In the intellectual history of the Christianity, Platonism and Aristotelianism have been employed to articulate the Christian philosophical anthropology. The Aristotelian systematization has endured to this era. Since the modern period of the Western intellectual history, Aristotelianism has been supplanted by the positive sciences as the (...)
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  25. Action and Agency in Artificial Intelligence: A Philosophical Critique.Justin Nnaemeka Onyeukaziri - 2023 - Philosophia: International Journal of Philosophy (Philippine e-journal) 24 (1):73-90.
    The objective of this work is to explore the notion of “action” and “agency” in artificial intelligence (AI). It employs a metaphysical notion of action and agency as an epistemological tool in the critique of the notion of “action” and “agency” in artificial intelligence. Hence, both a metaphysical and cognitive analysis is employed in the investigation of the quiddity and nature of action and agency per se, and how they are, by extension employed in the language and science of artificial (...)
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  26. Techniek, voorbij de nostalgie. [REVIEW]Massimiliano Simons - 2023 - de Uil Van Minerva 35 (4).
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  27. AI-aesthetics and the Anthropocentric Myth of Creativity.Emanuele Arielli & Lev Manovich - 2022 - NODES 1 (19-20).
    Since the beginning of the 21st century, technologies like neural networks, deep learning and “artificial intelligence” (AI) have gradually entered the artistic realm. We witness the development of systems that aim to assess, evaluate and appreciate artifacts according to artistic and aesthetic criteria or by observing people’s preferences. In addition to that, AI is now used to generate new synthetic artifacts. When a machine paints a Rembrandt, composes a Bach sonata, or completes a Beethoven symphony, we say that this is (...)
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  28. COVID-19 and Singularity: Can the Philippines Survive Another Existential Threat?Robert James M. Boyles, Mark Anthony Dacela, Tyrone Renzo Evangelista & Jon Carlos Rodriguez - 2022 - Asia-Pacific Social Science Review 22 (2):181–195.
    In general, existential threats are those that may potentially result in the extinction of the entire human species, if not significantly endanger its living population. Among the said threats include, but not limited to, pandemics and the impacts of a technological singularity. As regards pandemics, significant work has already been done on how to mitigate, if not prevent, the aftereffects of this type of disaster. For one, certain problem areas on how to properly manage pandemic responses have already been identified, (...)
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  29. Decentring the discoverer: how AI helps us rethink scientific discovery.Elinor Clark & Donal Khosrowi - 2022 - Synthese 200 (6):1-26.
    This paper investigates how intuitions about scientific discovery using artificial intelligence can be used to improve our understanding of scientific discovery more generally. Traditional accounts of discovery have been agent-centred: they place emphasis on identifying a specific agent who is responsible for conducting all, or at least the important part, of a discovery process. We argue that these accounts experience difficulties capturing scientific discovery involving AI and that similar issues arise for human discovery. We propose an alternative, collective-centred view as (...)
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  30. Interprétabilité et explicabilité de phénomènes prédits par de l’apprentissage machine.Christophe Denis & Franck Varenne - 2022 - Revue Ouverte d'Intelligence Artificielle 3 (3-4):287-310.
    Le déficit d’explicabilité des techniques d’apprentissage machine (AM) pose des problèmes opérationnels, juridiques et éthiques. Un des principaux objectifs de notre projet est de fournir des explications éthiques des sorties générées par une application fondée sur de l’AM, considérée comme une boîte noire. La première étape de ce projet, présentée dans cet article, consiste à montrer que la validation de ces boîtes noires diffère épistémologiquement de celle mise en place dans le cadre d’une modélisation mathéma- tique et causale d’un phénomène (...)
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  31. Artificial Intelligence and the Notions of the “Natural” and the “Artificial.”.Justin Nnaemeka Onyeukaziri - 2022 - Journal of Data Analysis 17 (No. 4):101-116.
    This paper argues that to negate the ontological difference between the natural and the artificial, is not plausible; nor is the reduction of the natural to the artificial or vice versa possible. Except if one intends to empty the semantic content of the terms and notions: “natural” and “artificial.” Most philosophical discussions on Artificial Intelligence (AI) have always been in relation to the human person, especially as it relates to human intelligence, consciousness and/or mind in general. This paper, intends to (...)
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  32. Machine learning in scientific grant review: algorithmically predicting project efficiency in high energy physics.Vlasta Sikimić & Sandro Radovanović - 2022 - European Journal for Philosophy of Science 12 (3):1-21.
    As more objections have been raised against grant peer-review for being costly and time-consuming, the legitimate question arises whether machine learning algorithms could help assess the epistemic efficiency of the proposed projects. As a case study, we investigated whether project efficiency in high energy physics can be algorithmically predicted based on the data from the proposal. To analyze the potential of algorithmic prediction in HEP, we conducted a study on data about the structure and outcomes of HEP experiments with the (...)
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  33. Strictly Human: Limitations of Autonomous Systems.Sadjad Soltanzadeh - 2022 - Minds and Machines 32 (2):269-288.
    Can autonomous systems replace humans in the performance of their activities? How does the answer to this question inform the design of autonomous systems? The study of technical systems and their features should be preceded by the study of the activities in which they play roles. Each activity can be described by its overall goals, governing norms and the intermediate steps which are taken to achieve the goals and to follow the norms. This paper uses the activity realist approach to (...)
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  34. Walking Through The Turing Wall.Albert Efimov - 2021 - IFAC Papers Online 54 (13):215-220.
    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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  35. From Specialized to Hyper-Specialized Labour: Future Labor Markets as Helmed by Advanced Computer Intelligence.Tyler Jaynes - 2021 - In Pritika Nehra (ed.), Loneliness and the Crisis of Work. Newcastle upon Tyne, UK: Cambridge Scholars Publishing. pp. 159-175.
    With the transition of the pandemic-gripped labor market en masse to remote capabilities to avert from a national or international economic meltdown, a concern arises that many job seekers simply cannot fit into the new roles being developed and implemented. Beyond the loss of on-site work, the market is unable to reverse the loss of many roles that are, and have been, taken over by artificial (computer) intelligence systems. The “business-as-usual” mentality that many have come to associate with pre-pandemic life (...)
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  36. Artificial Intelligence as Philosophy.Giovanni Landi (ed.) - 2021 - Chișinău, Moldavia: Eliva Press.
    Artificial intelligence is not and has never been a technology. It began with Turing's famous "can machine think?", a philosophical question that too many were quick to transform into a more prosaic "can Thought be mechanized?" Only in this perspective can the history and the technological success of AI be duly explained and understood, one of the tasks this book engages in. -/- It is important for philosophers to take AI seriously, and for AI researchers to see their discipline through (...)
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  37. The Problem Of Moral Agency In Artificial Intelligence.Riya Manna & Rajakishore Nath - 2021 - 2021 IEEE Conference on Norbert Wiener in the 21st Century (21CW).
    Humans have invented intelligent machinery to enhance their rational decision-making procedure, which is why it has been named ‘augmented intelligence’. The usage of artificial intelligence (AI) technology is increasing enormously with every passing year, and it is becoming a part of our daily life. We are using this technology not only as a tool to enhance our rationality but also heightening them as the autonomous ethical agent for our future society. Norbert Wiener envisaged ‘Cybernetics’ with a view of a brain-machine (...)
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  38. Kantian Notion of freedom and Autonomy of Artificial Agency.Manas Kumar Sahu - 2021 - Prometeica - Revista De Filosofía Y Ciencias 23:136-149.
    The objective of this paper is to provide a critical analysis of the Kantian notion of freedom (especially the problem of the third antinomy and its resolution in the critique of pure reason); its significance in the contemporary debate on free-will and determinism, and the possibility of autonomy of artificial agency in the Kantian paradigm of autonomy. Kant's resolution of the third antinomy by positing the ground in the noumenal self resolves the problem of antinomies; however, invites an explanatory gap (...)
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  39. Moving beyond content‐specific computation in artificial neural networks.Nicholas Shea - 2021 - Mind and Language 38 (1):156-177.
    A basic deep neural network (DNN) is trained to exhibit a large set of input–output dispositions. While being a good model of the way humans perform some tasks automatically, without deliberative reasoning, more is needed to approach human‐like artificial intelligence. Analysing recent additions brings to light a distinction between two fundamentally different styles of computation: content‐specific and non‐content‐specific computation (as first defined here). For example, deep episodic RL networks draw on both. So does human conceptual reasoning. Combining the two takes (...)
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  40. Performance vs. competence in human–machine comparisons.Chaz Firestone - 2020 - Proceedings of the National Academy of Sciences 41.
    Does the human mind resemble the machines that can behave like it? Biologically inspired machine-learning systems approach “human-level” accuracy in an astounding variety of domains, and even predict human brain activity—raising the exciting possibility that such systems represent the world like we do. However, even seemingly intelligent machines fail in strange and “unhumanlike” ways, threatening their status as models of our minds. How can we know when human–machine behavioral differences reflect deep disparities in their underlying capacities, vs. when such failures (...)
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  41. In Defence of a Reciprocal Turing Test.Fintan Mallory - 2020 - Minds and Machines 30 (4):659-680.
    The traditional Turing test appeals to an interrogator's judgement to determine whether or not their interlocutor is an intelligent agent. This paper argues that this kind of asymmetric experimental set-up is inappropriate for tracking a property such as intelligence because intelligence is grounded in part by symmetric relations of recognition between agents. In place, it proposes a reciprocal test which takes into account the judgments of both interrogators and competitors to determine if an agent is intelligent. This form of social (...)
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  42. AI-Completeness: Using Deep Learning to Eliminate the Human Factor.Kristina Šekrst - 2020 - In Sandro Skansi (ed.), Guide to Deep Learning Basics. Springer. pp. 117-130.
    Computational complexity is a discipline of computer science and mathematics which classifies computational problems depending on their inherent difficulty, i.e. categorizes algorithms according to their performance, and relates these classes to each other. P problems are a class of computational problems that can be solved in polynomial time using a deterministic Turing machine while solutions to NP problems can be verified in polynomial time, but we still do not know whether they can be solved in polynomial time as well. A (...)
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  43. Cosa significano Paraconsistente, Indecifrabile, Casuale, Calcolabile e Incompleto? Una recensione di Godel's Way: sfrutta in un mondo indecidibile (Godel's Way: Exploits into an Undecidable World) di Gregory Chaitin, Francisco A Doria, Newton C.A. da Costa 160p (2012) (rivisto 2019).Michael Richard Starks - 2020 - In Benvenuti all'inferno sulla Terra: Bambini, Cambiamenti climatici, Bitcoin, Cartelli, Cina, Democrazia, Diversità, Disgenetica, Uguaglianza, Pirati Informatici, Diritti umani, Islam, Liberalismo, Prosperità, Web, Caos, Fame, Malattia, Violenza, Intellige. Las Vegas, NV, USA: Reality Press. pp. 163-176.
    Nel 'Godel's Way' tre eminenti scienziati discutono questioni come l'indecidibilità, l'incompletezza, la casualità, la computabilità e la paracoerenza. Affronto questi problemi dal punto di vista di Wittgensteinian che ci sono due questioni fondamentali che hanno soluzioni completamente diverse. Ci sono le questioni scientifiche o empiriche, che sono fatti sul mondo che devono essere studiati in modo osservante e filosofico su come il linguaggio può essere usato in modo intelligibilmente (che include alcune domande in matematica e logica), che devono essere decise (...)
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  44. パラコンシステント、決定不能、ランダム、計算可能、不完全とはどういう意味 ですか? 「ゴーデルの方法:決定不可能な世界への冒険:」のレビュー(Godel's Way: exploits into an Undecidable World) byA. da Costa 160p (2012) (2019年のレビュー改訂).Michael Richard Starks - 2020 - In 地獄へようこそ 赤ちゃん、気候変動、ビットコイン、カルテル、中国、民主主義、多様性、ディスジェニックス、平等、ハッカー、人権、イスラム教、自由主義、繁栄、ウェブ、カオス、飢餓、病気、暴力、人工知能、戦争. Las Vegas, NV , USA: Reality Press. pp. 158-171.
    「ゴーデルの道」では、3人の著名な科学者が、デシッド不能、不完全性、ランダム性、計算可能性、パラコンシステンションなどの問題について議論しています。私は、ウィトゲンシュタイニアンの視点から、全く異なる 解決策を持つ2つの基本的な問題があることをこれらの問題に取り組んでいます。科学的または経験的な問題は、言語がどのように理解的に使用できるか(数学と論理に特定の質問を含む)、特定の文脈で実際にどのように 単語を使用するかを調べて決定する必要がある、観察的および哲学的な問題を調査する必要がある世界に関する事実です。私たちがプレイしている言語ゲームについて明確になると、これらのトピックは他の人と同じように 普通の科学的、数学的な質問であると見なされます。ウィトゲンシュタインの洞察はめったに等しくなく、決して上回ることはなく、彼がブルーブックスとブラウンブックスを口述した80年前と同じくらい適切です。失敗 にもかかわらず、本当に完成した本ではなく一連のノートは、半世紀以上にわたって物理学、数学、哲学の出血エッジで働いてきたこれらの3人の有名な学者の作品のユニークな源です。ダ・コスタとドリアは、普遍的な計 算に書いて以来、ウォルパート(以下または私の記事を参照)によって引用されています(ウォルパートとヤナフスキーの「理由の外側の限界」の私のレビューを参照)、,そして彼の多くの成果の中で、ダ・コスタはパラ コンシタンションのパイオニアです。 現代の2つのシス・エムスの見解から人間の行動のための包括的な最新の枠組みを望む人は、私の著書「ルートヴィヒ・ヴィトゲンシュタインとジョン・サールの第2回(2019)における哲学、心理学、ミンと言語の論 理的構造」を参照することができます。私の著作の多くにご興味がある人は、運命の惑星における「話す猿--哲学、心理学、科学、宗教、政治―記事とレビュー2006-2019 第3回(2019)」と21世紀4日(2019年)の自殺ユートピア妄想st Century 4th ed (2019)などを見ることができます。 .
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  45. Was bedeuten Parakonsistente, Unentscheidbar, Zufällig, Berechenbar und Unvollständige? Eine Rezension von „Godels Weg: Exploits in eine unentscheidbare Welt“ (Godels Way: Exploits into a unecidable world) von Gregory Chaitin, Francisco A Doria, Newton C.A. da Costa 160p (2012).Michael Richard Starks - 2020 - In Willkommen in der Hölle auf Erden: Babys, Klimawandel, Bitcoin, Kartelle, China, Demokratie, Vielfalt, Dysgenie, Gleichheit, Hacker, Menschenrechte, Islam, Liberalismus, Wohlstand, Internet, Chaos, Hunger, Krankheit, Gewalt, Künstliche Intelligenz, Krieg. Reality Press. pp. 1171-185.
    In "Godel es Way" diskutieren drei namhafte Wissenschaftler Themen wie Unentschlossenheit, Unvollständigkeit, Zufälligkeit, Berechenbarkeit und Parakonsistenz. Ich gehe diese Fragen aus Wittgensteiner Sicht an, dass es zwei grundlegende Fragen gibt, die völlig unterschiedliche Lösungen haben. Es gibt die wissenschaftlichen oder empirischen Fragen, die Fakten über die Welt sind, die beobachtungs- und philosophische Fragen untersuchen müssen, wie Sprache verständlich verwendet werden kann (die bestimmte Fragen in Mathematik und Logik beinhalten), die entschieden werden müssen, indem man sich anschaut,wie wir Wörter in bestimmten (...)
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  46. Gli ominoidi o gli androidi distruggeranno la Terra? Una recensione di Come Creare una Mente (How to Create a Mind) di Ray Kurzweil (2012) (recensione rivista nel 2019).Michael Richard Starks - 2020 - In Benvenuti all'inferno sulla Terra: Bambini, Cambiamenti climatici, Bitcoin, Cartelli, Cina, Democrazia, Diversità, Disgenetica, Uguaglianza, Pirati Informatici, Diritti umani, Islam, Liberalismo, Prosperità, Web, Caos, Fame, Malattia, Violenza, Intellige. Las Vegas, NV, USA: Reality Press. pp. 150-162.
    Alcuni anni fa, ho raggiunto il punto in cui di solito posso dire dal titolo di un libro, o almeno dai titoli dei capitoli, quali tipi di errori filosofici saranno fatti e con quale frequenza. Nel caso di opere nominalmente scientifiche queste possono essere in gran parte limitate a determinati capitoli che sono filosofici o cercanodi trarre conclusioni generali sul significato o sul significato a lungoterminedell'opera. Normalmente però le questioni scientifiche di fatto sono generosamente intrecciate con incomprodellami filosofici su ciò (...)
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  47. Wolpert, Chaitin and Wittgenstein 不可能性、不完全性、嘘つきパラドックス、 無神論、計算の限界、非量子力学的不確実性原理、そしてコンピューターとして の宇宙-チューリング機械理論の究極の定理 (2019年改訂レビュー).Michael Richard Starks - 2020 - In 地獄へようこそ 赤ちゃん、気候変動、ビットコイン、カルテル、中国、民主主義、多様性、ディスジェニックス、平等、ハッカー、人権、イスラム教、自由主義、繁栄、ウェブ、カオス、飢餓、病気、暴力、人工知能、戦争. Las Vegas,, NV , USA: Reality Press. pp. 173-177.
    私は計算と宇宙の限界に関する最近の議論をコンピュータとして読み、ポリマス物理学者と意思決定理論家デビッド・ウォルパートの驚くべき仕事に関するいくつかのコメントを見つけることを望んでいますが、単一の引用 を見つけていないので、私はこの非常に簡単な要約を提示します。ウォルパートは、計算を行うデバイスから独立し、物理学の法則から独立している推論(計算)の限界に関する驚くべき不可能または不完全な定理(199 2年から2008年のarxiv.org参照)を証明したので、コンピュータ、物理学、人間の行動に適用されます。彼らは、カントールの対角化、嘘つきのパラドックス、ワールドラインを利用して、チューリングマシ ン理論の究極の定理である可能性のあるものを提供し、不可能、不完全性、計算の限界、そしてコンピュータとしての宇宙に関する洞察を提供し、すべての可能な宇宙とすべての存在またはメカニズムを生み出し、とりわけ 非量子機械不確実性原理と単一主義の証明を生み出します。チャイティン、ソロモノフ、コモルガロフ、ヴィトゲンシュタインの古典的な作品と、どのプログラム(したがってデバイスも)が所有するよりも複雑なシーケン ス(またはデバイス)を生成できないという考えには明らかなつながりがあります。この作品の体は、物理的な宇宙よりも複雑な存在はあり得ないので無テズムを意味すると言うかもしれませんし、ヴィトゲンチニアンの観 点から見ると、「より複雑な」は無意味です(満足の条件はありません、すなわち、真実のメーカーやテスト)。「神」(つまり、無限の時間/空間とエネルギーを持つ「デバイス」)でさえ、与えられた「数」が「ランダ ム」であるかどうかを判断したり、与えられた「公式」、定理または「文章」または「デバイス」(これらはすべて複雑な言語ゲームである)が特定の「システム」の一部であることを示す特定の方法を見つけることができ ません。 現代の2つのシス・エムスの見解から人間の行動のための包括的な最新の枠組みを望む人は、私の著書「ルートヴィヒ・ヴィトゲンシュタインとジョン・サールの第2回(2019)における哲学、心理学、ミンと言語の論 理的構造」を参照することができます。私の著作の多くにご興味がある人は、21世紀4日(2019年)の「話す猿--哲学、心理学、科学、宗教、政治」を見ることができます。 .
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  48. Gli ominoidi o gli androidi distruggeranno la Terra? Una recensione di Come Creare una Mente (How to Create a Mind) di Ray Kurzweil (2012) (recensione rivista nel 2019).Michael Richard Starks - 2020 - In Benvenuti all'inferno sulla Terra: Bambini, Cambiamenti climatici, Bitcoin, Cartelli, Cina, Democrazia, Diversità, Disgenetica, Uguaglianza, Pirati Informatici, Diritti umani, Islam, Liberalismo, Prosperità, Web, Caos, Fame, Malattia, Violenza, Intellige. Las Vegas, NV, USA: Reality Press. pp. 150-162.
    Alcuni anni fa, ho raggiunto il punto in cui di solito posso dire dal titolo di un libro, o almeno dai titoli dei capitoli, quali tipi di errori filosofici saranno fatti e con quale frequenza. Nel caso di opere nominalmente scientifiche queste possono essere in gran parte limitate a determinati capitoli che sono filosofici o cercanodi trarre conclusioni generali sul significato o sul significato a lungoterminedell'opera. Normalmente però le questioni scientifiche di fatto sono generosamente intrecciate con incomprodellami filosofici su ciò (...)
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  49. 인간이나 안드로이드가 지구를 파괴 할 것인가? — '마음 만드는 법'의 검토 (How to Create a Mind) Ray Kurzweil (2010).Michael Richard Starks - 2020 - In 지구상의 지옥에 오신 것을 환영합니다 : 아기, 기후 변화, 비트 코인, 카르텔, 중국, 민주주의, 다양성, 역학, 평등, 해커, 인권, 이슬람, 자유주의, 번영, 웹, 혼돈, 기아, 질병, 폭력, 인공 지능, 전쟁. Las Vegas, NV USA: Reality Press. pp. 172-186.
    몇 년전, 저는 보통 책의 제목이나 적어도 장 제목에서 어떤 종류의 철학적 실수를 저지르고 얼마나 자주 알 수 있는지 를 알 수 있는 지점에 도달했습니다. 명목상 과학적 작품의 경우, 이들은 크게 철학적 왁스 또는 의미 또는 긴에 대한 일반적인 결론을 그리려는 특정 장으로 제한 될 수있다-작업의기간 의의. 그러나 일반적으로 사실의 과학적 문제는 이러한 사실이 무엇을 의미하는지에 관해서는 철학적 횡설수설과 관대하게 얽혀있다. Wittgenstein이 약 80 년 전에 과학 문제와 다양한 언어 게임에 의한 설명 사이에 설명 한 명확한 차이점은 거의 고려되지 않으므로 (...)
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  50. Wolpert, Chaitin et Wittgenstein sur l’impossibilité, l’incomplétude, le paradoxe menteur, le théisme, les limites du calcul, un principe d’incertitude mécanique non quantique et l’univers comme ordinateur, le théorème ultime dans Turing Machine Theory (révisé 2019).Michael Richard Starks - 2020 - In Bienvenue en Enfer sur Terre : Bébés, Changement climatique, Bitcoin, Cartels, Chine, Démocratie, Diversité, Dysgénique, Égalité, Pirates informatiques, Droits de l'homme, Islam, Libéralisme, Prospérité, Le Web, Chaos, Famine, Maladie, Violence, Intellige. Las Vegas, NV , USA: Reality Press. pp. 185-189.
    J’ai lu de nombreuses discussions récentes sur les limites du calcul et de l’univers en tant qu’ordinateur, dans l’espoir de trouver quelques commentaires sur le travail étonnant du physicien polymathe et théoricien de la décision David Wolpert, mais n’ont pas trouvé une seule citation et je présente donc ce résumé très bref. Wolpert s’est avéré quelques théoricaux d’impossibilité ou d’incomplétude renversants (1992 à 2008-voir arxiv dot org) sur les limites de l’inférence (computation) qui sont si généraux qu’ils sont indépendants de (...)
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