About this topic
Summary See the category "Philosophy of Artificial Intelligence."
Key works See the category "Philosophy of Artificial Intelligence" for key works.
Introductions See the category "Philosophy of Artificial Intelligence" for introductions.
Related categories

147 found
Order:
1 — 50 / 147
  1. Revised: From Color, to Consciousness, toward Strong AI.Xinyuan Gu - manuscript
    This article cohesively discusses three topics, namely color and its perception, the yet-to-be-solved hard problem of consciousness, and the theoretical possibility of strong AI. First, the article restores color back into the physical world by giving cross-species evidence. Secondly, the article proposes a dual-field with function Q hypothesis (DFFQ) which might explain the ‘first-person point of view’ and so the hard problem of consciousness. Finally, the article discusses what DFFQ might bring to artificial intelligence and how it might allow strong (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  2. Probable General Intelligence algorithm.Anton Venglovskiy - manuscript
    Contains a description of a generalized and constructive formal model for the processes of subjective and creative thinking. According to the author, the algorithm presented in the article is capable of real and arbitrarily complex thinking and is potentially able to report on the presence of consciousness.
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  3. Truth & Understanding: Essays in Honor of John Haugeland.Zed Adams (ed.) - forthcoming
    Remove from this list  
     
    Export citation  
     
    Bookmark  
  4. Short-circuiting the definition of mathematical knowledge for an Artificial General Intelligence.Samuel Alexander - forthcoming - Lecture Notes in Computer Science.
    We propose that, for the purpose of studying theoretical properties of the knowledge of an agent with Artificial General Intelligence (that is, the knowledge of an AGI), a pragmatic way to define such an agent’s knowledge (restricted to the language of Epistemic Arithmetic, or EA) is as follows. We declare an AGI to know an EA-statement φ if and only if that AGI would include φ in the resulting enumeration if that AGI were commanded: “Enumerate all the EA-sentences which you (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  5. “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 (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  6. Designing new Intelligent Machines (COMETT European Symposium, Liège April 1992).D. M. Dubois - forthcoming - Communication and Cognition-Artificial Intelligence.
    Remove from this list  
     
    Export citation  
     
    Bookmark  
  7. Understanding Sophia? On human interaction with artificial agents.Thomas Fuchs - forthcoming - Phenomenology and the Cognitive Sciences:1-22.
    Advances in artificial intelligence create an increasing similarity between the performance of AI systems or AI-based robots and human communication. They raise the questions: whether it is possible to communicate with, understand, and even empathically perceive artificial agents; whether we should ascribe actual subjectivity and thus quasi-personal status to them beyond a certain level of simulation; what will be the impact of an increasing dissolution of the distinction between simulated and real encounters. To answer these questions, the paper argues that (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  8. Explaining Explanations in AI.Brent Mittelstadt - forthcoming - FAT* 2019 Proceedings 1.
    Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These models are a useful pedagogical device for teaching trained professionals how to predict what decisions will be made by the complex system, and most importantly how the system might break. However, when considering any such model it’s important to remember Box’s maxim that "All models are wrong but some are useful." We focus on (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   37 citations  
  9. The Best Game in Town: The Re-Emergence of the Language of Thought Hypothesis Across the Cognitive Sciences.Jake Quilty-Dunn, Nicolas Porot & Eric Mandelbaum - forthcoming - Behavioral and Brain Sciences:1-55.
    Mental representations remain the central posits of psychology after many decades of scrutiny. However, there is no consensus about the representational format(s) of biological cognition. This paper provides a survey of evidence from computational cognitive psychology, perceptual psychology, developmental psychology, comparative psychology, and social psychology, and concludes that one type of format that routinely crops up is the language of thought (LoT). We outline six core properties of LoTs: (i) discrete constituents; (ii) role-filler independence; (iii) predicate-argument structure; (iv) logical operators; (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  10. Some resonances between Eastern thought and Integral Biomathics in the framework of the WLIMES formalism for modelling living systems.Plamen L. Simeonov & Andree C. Ehresmann - forthcoming - Progress in Biophysics and Molecular Biology 131 (Special).
    Forty-two years ago, Capra published “The Tao of Physics” (Capra, 1975). In this book (page 17) he writes: “The exploration of the atomic and subatomic world in the twentieth century has …. necessitated a radical revision of many of our basic concepts” and that, unlike ‘classical’ physics, the sub-atomic and quantum “modern physics” shows resonances with Eastern thoughts and “leads us to a view of the world which is very similar to the views held by mystics of all ages and (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  11. Pseudo-visibility: A Game Mechanic Involving Willful Ignorance.Samuel Allen Alexander & Arthur Paul Pedersen - 2022 - FLAIRS-35.
    We present a game mechanic called pseudo-visibility for games inhabited by non-player characters (NPCs) driven by reinforcement learning (RL). NPCs are incentivized to pretend they cannot see pseudo-visible players: the training environment simulates an NPC to determine how the NPC would act if the pseudo-visible player were invisible, and penalizes the NPC for acting differently. NPCs are thereby trained to selectively ignore pseudo-visible players, except when they judge that the reaction penalty is an acceptable tradeoff (e.g., a guard might accept (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  12. 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 (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  13. Extending the Is-ought Problem to Top-down Artificial Moral Agents.Robert James M. Boyles - 2022 - Symposion: Theoretical and Applied Inquiries in Philosophy and Social Sciences 9 (2):171–189.
    This paper further cashes out the notion that particular types of intelligent systems are susceptible to the is-ought problem, which espouses the thesis that no evaluative conclusions may be inferred from factual premises alone. Specifically, it focuses on top-down artificial moral agents, providing ancillary support to the view that these kinds of artifacts are not capable of producing genuine moral judgements. Such is the case given that machines built via the classical programming approach are always composed of two parts, namely: (...)
    Remove from this list   Direct download (6 more)  
     
    Export citation  
     
    Bookmark  
  14. Why is Information Retrieval a Scientific Discipline?Robert W. P. Luk - 2022 - Foundations of Science 27 (2):427-453.
    It is relatively easy to state that information retrieval is a scientific discipline but it is rather difficult to understand why it is science because what is science is still under debate in the philosophy of science. To be able to convince others that IR is science, our ability to explain why is crucial. To explain why IR is a scientific discipline, we use a theory and a model of scientific study, which were proposed recently. The explanation involves mapping the (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  15. ANNs and Unifying Explanations: Reply to Erasmus, Brunet, and Fisher.Yunus Prasetya - 2022 - Philosophy and Technology 35 (2):1-9.
    In a recent article, Erasmus, Brunet, and Fisher (2021) argue that Artificial Neural Networks (ANNs) are explainable. They survey four influential accounts of explanation: the Deductive-Nomological model, the Inductive-Statistical model, the Causal-Mechanical model, and the New-Mechanist model. They argue that, on each of these accounts, the features that make something an explanation is invariant with regard to the complexity of the explanans and the explanandum. Therefore, they conclude, the complexity of ANNs (and other Machine Learning models) does not make them (...)
    Remove from this list   Direct download (6 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  16. 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 (...)
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    Bookmark  
  17. Metaphysics , Meaning, and Morality: A Theological Reflection on A.I.Jordan Joseph Wales - 2022 - Journal of Moral Theology 11 (Special Issue 1):157-181.
    Theologians often reflect on the ethical uses and impacts of artificial intelligence, but when it comes to artificial intelligence techniques themselves, some have questioned whether much exists to discuss in the first place. If the significance of computational operations is attributed rather than intrinsic, what are we to say about them? Ancient thinkers—namely Augustine of Hippo (lived 354–430)—break the impasse, enabling us to draw forth the moral and metaphysical significance of current developments like the “deep neural networks” that are responsible (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  18. Measuring Intelligence and Growth Rate: Variations on Hibbard's Intelligence Measure.Samuel Alexander & Bill Hibbard - 2021 - Journal of Artificial General Intelligence 12 (1):1-25.
    In 2011, Hibbard suggested an intelligence measure for agents who compete in an adversarial sequence prediction game. We argue that Hibbard’s idea should actually be considered as two separate ideas: first, that the intelligence of such agents can be measured based on the growth rates of the runtimes of the competitors that they defeat; and second, one specific (somewhat arbitrary) method for measuring said growth rates. Whereas Hibbard’s intelligence measure is based on the latter growth-rate-measuring method, we survey other methods (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  19. Machine Learning and the Future of Scientific Explanation.Florian J. Boge & Michael Poznic - 2021 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 52 (1):171-176.
    The workshop “Machine Learning: Prediction Without Explanation?” brought together philosophers of science and scholars from various fields who study and employ Machine Learning (ML) techniques, in order to discuss the changing face of science in the light of ML's constantly growing use. One major focus of the workshop was on the impact of ML on the concept and value of scientific explanation. One may speculate whether ML’s increased use in science exemplifies a paradigmatic turn towards mere pattern recognition and prediction (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  20. Measuring the intelligence of an idealized mechanical knowing agent.Samuel Alexander - 2020 - Lecture Notes in Computer Science 12226.
    We define a notion of the intelligence level of an idealized mechanical knowing agent. This is motivated by efforts within artificial intelligence research to define real-number intelligence levels of compli- cated intelligent systems. Our agents are more idealized, which allows us to define a much simpler measure of intelligence level for them. In short, we define the intelligence level of a mechanical knowing agent to be the supremum of the computable ordinals that have codes the agent knows to be codes (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   3 citations  
  21. Self-referential theories.Samuel A. Alexander - 2020 - Journal of Symbolic Logic 85 (4):1687-1716.
    We study the structure of families of theories in the language of arithmetic extended to allow these families to refer to one another and to themselves. If a theory contains schemata expressing its own truth and expressing a specific Turing index for itself, and contains some other mild axioms, then that theory is untrue. We exhibit some families of true self-referential theories that barely avoid this forbidden pattern.
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  22. The Archimedean trap: Why traditional reinforcement learning will probably not yield AGI.Samuel Allen Alexander - 2020 - Journal of Artificial General Intelligence 11 (1):70-85.
    After generalizing the Archimedean property of real numbers in such a way as to make it adaptable to non-numeric structures, we demonstrate that the real numbers cannot be used to accurately measure non-Archimedean structures. We argue that, since an agent with Artificial General Intelligence (AGI) should have no problem engaging in tasks that inherently involve non-Archimedean rewards, and since traditional reinforcement learning rewards are real numbers, therefore traditional reinforcement learning probably will not lead to AGI. We indicate two possible ways (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  23. A Critical Reflection on Automated Science: Will Science Remain Human?Marta Bertolaso & Fabio Sterpetti (eds.) - 2020 - Cham: Springer.
    This book provides a critical reflection on automated science and addresses the question whether the computational tools we developed in last decades are changing the way we humans do science. More concretely: Can machines replace scientists in crucial aspects of scientific practice? The contributors to this book rethink and refine some of the main concepts by which science is understood, drawing a fascinating picture of the developments we expect over the next decades of human-machine co-evolution. The volume covers examples from (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  24. WG-A: A Framework for Exploring Analogical Generalization and Argumentation.Michael Cooper, Lindsey Fields, Marc Gabriel Badilla & John Licato - 2020 - CogSci 2020.
    Reasoning about analogical arguments is known to be subject to a variety of cognitive biases, and a lack of clarity about which factors can be considered strengths or weaknesses of an analogical argument. This can make it difficult both to design empirical experiments to study how people reason about analogical arguments, and to develop scalable tutoring tools for teaching how to reason and analyze analogical arguments. To address these concerns, we describe WG-A (Warrant Game — Analogy), a framework for people (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  25. Why Attention is Not Explanation: Surgical Intervention and Causal Reasoning about Neural Models.Christopher Grimsley, Elijah Mayfield & Julia Bursten - 2020 - Proceedings of the 12th Conference on Language Resources and Evaluation.
    As the demand for explainable deep learning grows in the evaluation of language technologies, the value of a principled grounding for those explanations grows as well. Here we study the state-of-the-art in explanation for neural models for natural-language processing (NLP) tasks from the viewpoint of philosophy of science. We focus on recent evaluation work that finds brittleness in explanations obtained through attention mechanisms.We harness philosophical accounts of explanation to suggest broader conclusions from these studies. From this analysis, we assert the (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  26. Legg-Hutter universal intelligence implies classical music is better than pop music for intellectual training.Samuel Alexander - 2019 - The Reasoner 13 (11):71-72.
    In their thought-provoking paper, Legg and Hutter consider a certain abstrac- tion of an intelligent agent, and define a universal intelligence measure, which assigns every such agent a numerical intelligence rating. We will briefly summarize Legg and Hutter’s paper, and then give a tongue-in-cheek argument that if one’s goal is to become more intelligent by cultivating music appreciation, then it is bet- ter to use classical music (such as Bach, Mozart, and Beethoven) than to use more recent pop music. The (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  27. Intelligence via ultrafilters: structural properties of some intelligence comparators of deterministic Legg-Hutter agents.Samuel Alexander - 2019 - Journal of Artificial General Intelligence 10 (1):24-45.
    Legg and Hutter, as well as subsequent authors, considered intelligent agents through the lens of interaction with reward-giving environments, attempting to assign numeric intelligence measures to such agents, with the guiding principle that a more intelligent agent should gain higher rewards from environments in some aggregate sense. In this paper, we consider a related question: rather than measure numeric intelligence of one Legg- Hutter agent, how can we compare the relative intelligence of two Legg-Hutter agents? We propose an elegant answer (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   3 citations  
  28. Considerazioni sull’infosfera. S&F : a colloquio con Luciano Floridi.Luciano Floridi & Christian Fuschetto - 2019 - Scientia et Fides 22:131–136.
    New developments in the field of communication and information technology will profoundly reshape the answers to questions of deep interest for humanity and philosophy. Who are we and what kind of relationship we establish among us? The boundaries between real life and virtual life tend to evanish. We are progressively becoming part of a global “infosphere”. This candid interview with professor Floridi try to shed some light on these issues, by considering the philosophical framework developed by the “infosphere philosopher”.
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  29. Gods of Transhumanism.Alex V. Halapsis - 2019 - Anthropological Measurements of Philosophical Research 16:78-90.
    Purpose of the article is to identify the religious factor in the teaching of transhumanism, to determine its role in the ideology of this flow of thought and to identify the possible limits of technology interference in human nature. Theoretical basis. The methodological basis of the article is the idea of transhumanism. Originality. In the foreseeable future, robots will be able to pass the Turing test, become “electronic personalities” and gain political rights, although the question of the possibility of machine (...)
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  30. The Pragmatic Turn in Explainable Artificial Intelligence (XAI).Andrés Páez - 2019 - Minds and Machines 29 (3):441-459.
    In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies will (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark   23 citations  
  31. Machine Decisions and Human Consequences.Teresa Scantamburlo, Andrew Charlesworth & Nello Cristianini - 2019 - In Karen Yeung & Martin Lodge (eds.), Algorithmic Regulation. Oxford: Oxford University Press.
    As we increasingly delegate decision-making to algorithms, whether directly or indirectly, important questions emerge in circumstances where those decisions have direct consequences for individual rights and personal opportunities, as well as for the collective good. A key problem for policymakers is that the social implications of these new methods can only be grasped if there is an adequate comprehension of their general technical underpinnings. The discussion here focuses primarily on the case of enforcement decisions in the criminal justice system, but (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   3 citations  
  32. Building machines that learn and think about morality.Christopher Burr & Geoff Keeling - 2018 - In Proceedings of the Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB 2018). Society for the Study of Artificial Intelligence and Simulation of Behaviour.
    Lake et al. propose three criteria which, they argue, will bring artificial intelligence (AI) systems closer to human cognitive abilities. In this paper, we explore the application of these criteria to a particular domain of human cognition: our capacity for moral reasoning. In doing so, we explore a set of considerations relevant to the development of AI moral decision-making. Our main focus is on the relation between dual-process accounts of moral reasoning and model-free/model-based forms of machine learning. We also discuss (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   2 citations  
  33. Crítica da Razão Positrônica.Sandro Rinaldi Feliciano - 2018 - Dissertation, Universidade Federal Do Abc
    Existe um horizonte à frente. Este horizonte está longe de ser aquele aqui descrito em sua forma, mas talvez o seja em sua essência. O que quero dizer com isso é que existe uma possibilidade de os cérebros positrônicos do título nunca existirem para além das brilhantes mentes que os conceberam na Ficção Científica, mas isto não quer dizer que não existirão sistemas análogos em suas funções, principalmente quanto à racionalidade. A Crítica da Razão Positrônica é um texto que tem (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  34. In Pursuit of the Functional Definition of a Mind: The Inevitability of the Language Ontology.Vitalii Shymko - 2018 - Psycholinguistics 23 (1):327-346.
    In this article, the results of conceptualization of the definition of mind as an object of interdisciplinary applied research are described. The purpose of the theoretical analysis is to generate a methodological discourse suitable for a functional understanding of the mind in the context of the problem of natural language processing as one of the components of developments in the field of artificial intelligence. The conceptual discourse was realized with the help of the author's method of structural-ontological analysis, and developed (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  35. Philosophical Signposts for Artificial Moral Agent Frameworks.Robert James M. Boyles - 2017 - Suri 6 (2):92–109.
    This article focuses on a particular issue under machine ethics—that is, the nature of Artificial Moral Agents. Machine ethics is a branch of artificial intelligence that looks into the moral status of artificial agents. Artificial moral agents, on the other hand, are artificial autonomous agents that possess moral value, as well as certain rights and responsibilities. This paper demonstrates that attempts to fully develop a theory that could possibly account for the nature of Artificial Moral Agents may consider certain philosophical (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  36. Between Language and Consciousness: Linguistic Qualia, Awareness, and Cognitive Models.Piotr Konderak - 2017 - Studies in Logic, Grammar and Rhetoric 48 (1):285-302.
    The main goal of the paper is to present a putative role of consciousness in language capacity. The paper contrasts the two approaches characteristic for cognitive semiotics and cognitive science. Language is treated as a mental phenomenon and a cognitive faculty. The analysis of language activity is based on the Chalmers’ distinction between the two forms of consciousness: phenomenal and psychological. The approach is seen as an alternative to phenomenological analyses typical for cognitive semiotics. Further, a cognitive model of the (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  37. Why Computers are not Intelligent: An Argument.Richard Oxenberg - 2017 - Political Animal Magazine.
    Computers can mimic human intelligence, sometimes quite impressively. This has led some to claim that, a.) computers can actually acquire intelligence, and/or, b.) the human mind may be thought of as a very sophisticated computer. In this paper I argue that neither of these inferences are sound. The human mind and computers, I argue, operate on radically different principles.
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  38. From Biological to Synthetic Neurorobotics Approaches to Understanding the Structure Essential to Consciousness (Part 3).Jeffrey White - 2017 - APA Newsletter on Philosophy and Computers 17 (1):11-22.
    This third paper locates the synthetic neurorobotics research reviewed in the second paper in terms of themes introduced in the first paper. It begins with biological non-reductionism as understood by Searle. It emphasizes the role of synthetic neurorobotics studies in accessing the dynamic structure essential to consciousness with a focus on system criticality and self, develops a distinction between simulated and formal consciousness based on this emphasis, reviews Tani and colleagues' work in light of this distinction, and ends by forecasting (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  39. The Case for Government by Artificial Intelligence.Steven James Bartlett - 2016 - Willamette University Faculty Research Website: Http://Www.Willamette.Edu/~Sbartlet/Documents/Bartlett_The%20Case%20for%20Government%20by%20Artifici al%20Intelligence.Pdf.
    THE CASE FOR GOVERNMENT BY ARTIFICIAL INTELLIGENCE. Tired of election madness? The rhetoric of politicians? Their unreliable promises? And less than good government? -/- Until recently, it hasn’t been hard for people to give up control to computers. Not very many people miss the effort and time required to do calculations by hand, to keep track of their finances, or to complete their tax returns manually. But relinquishing direct human control to self-driving cars is expected to be more of a (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  40. A minimalist model of the artificial autonomous moral agent (AAMA).Ioan Muntean & Don Howard - 2016 - In SSS-16 Symposium Technical Reports. Association for the Advancement of Artificial Intelligence. AAAI.
    This paper proposes a model for an artificial autonomous moral agent (AAMA), which is parsimonious in its ontology and minimal in its ethical assumptions. Starting from a set of moral data, this AAMA is able to learn and develop a form of moral competency. It resembles an “optimizing predictive mind,” which uses moral data (describing typical behavior of humans) and a set of dispositional traits to learn how to classify different actions (given a given background knowledge) as morally right, wrong, (...)
    Remove from this list  
     
    Export citation  
     
    Bookmark   4 citations  
  41. Phenomenology and Science.Jack Reynolds & Richard Sebold (eds.) - 2016 - New York: Palgrave-Macmillan.
    This book investigates the complex, sometimes fraught relationship between phenomenology and the natural sciences. The contributors attempt to subvert and complicate the divide that has historically tended to characterize the relationship between the two fields. Phenomenology has traditionally been understood as methodologically distinct from scientific practice, and thus removed from any claim that philosophy is strictly continuous with science. There is some substance to this thinking, which has dominated consideration of the relationship between phenomenology and science throughout the twentieth century. (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  42. Simulation, self-extinction, and philosophy in the service of human civilization.Jeffrey White - 2016 - AI and Society 31 (2):171-190.
    Nick Bostrom’s recently patched ‘‘simulation argument’’ (Bostrom in Philos Q 53:243–255, 2003; Bos- trom and Kulczycki in Analysis 71:54–61, 2011) purports to demonstrate the probability that we ‘‘live’’ now in an ‘‘ancestor simulation’’—that is as a simulation of a period prior to that in which a civilization more advanced than our own—‘‘post-human’’—becomes able to simulate such a state of affairs as ours. As such simulations under consid- eration resemble ‘‘brains in vats’’ (BIVs) and may appear open to similar objections, the (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  43. Künstliche Intelligenz: Chancen und Risiken.Mannino Adriano, David Althaus, Jonathan Erhardt, Lukas Gloor, Adrian Hutter & Thomas Metzinger - 2015 - Diskussionspapiere der Stiftung Für Effektiven Altruismus 2:1-17.
    Die Übernahme des KI-Unternehmens DeepMind durch Google für rund eine halbe Milliarde US-Dollar signalisierte vor einem Jahr, dass von der KI-Forschung vielversprechende Ergebnisse erwartet werden. Spätestens seit bekannte Wissenschaftler wie Stephen Hawking und Unternehmer wie Elon Musk oder Bill Gates davor warnen, dass künstliche Intelligenz eine Bedrohung für die Menschheit darstellt, schlägt das KI-Thema hohe Wellen. Die Stiftung für Effektiven Altruismus (EAS, vormals GBS Schweiz) hat mit der Unterstützung von Experten/innen aus Informatik und KI ein umfassendes Diskussionspapier zu den Chancen (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  44. The species problem and its logic: Inescapable ambiguity and framework-relativity.Steven James Bartlett - 2015 - Willamette University Faculty Research Website, ArXiv.Org, and Cogprints.Org.
    For more than fifty years, taxonomists have proposed numerous alternative definitions of species while they searched for a unique, comprehensive, and persuasive definition. This monograph shows that these efforts have been unnecessary, and indeed have provably been a pursuit of a will o’ the wisp because they have failed to recognize the theoretical impossibility of what they seek to accomplish. A clear and rigorous understanding of the logic underlying species definition leads both to a recognition of the inescapable ambiguity that (...)
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  45. Automatic apple grading model development based on back propagation neural network and machine vision, and its performance evaluation.A. K. Bhatt & D. Pant - 2015 - AI and Society 30 (1):45-56.
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  46. On a Cognitive Model of Semiosis.Piotr Konderak - 2015 - Studies in Logic, Grammar and Rhetoric 40 (1):129-144.
    What is the class of possible semiotic systems? What kinds of systems could count as such systems? The human mind is naturally considered the prototypical semiotic system. During years of research in semiotics the class has been broadened to include i.e. living systems like animals, or even plants. It is suggested in the literature on artificial intelligence that artificial agents are typical examples of symbol-processing entities. It also seems that semiotic processes are in fact cognitive processes. In consequence, it is (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  47. Mind uploading: a philosophical counter-analysis.Massimo Pigliucci - 2014 - In Russell Blackford & Damien Broderick (eds.), Intelligence Unbound: The Future of Uploaded and Machine Minds. Wiley. pp. 119-130.
    A counter analysis of David Chalmers' claims about the possibility of mind uploading within the context of the Singularity event.
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   5 citations  
  48. Levels of abstraction, emergentism and artificial life.Emanuele Ratti - 2014 - Journal of Experimental & Theoretical Artificial Intelligence:1-12.
    I diagnose the current debate between epistemological and ontological emergentism as a Kantian antinomy, which has reasonable but irreconcilable thesis and antithesis. Kantian antinomies have recently returned to contemporary philosophy in part through the work of Luciano Floridi, and the method of levels of abstraction. I use a thought experiment concerning a computer simulation to show how to resolve the epistemological/ontological antinomy about emergence. I also use emergentism and simulations in artificial life to illuminate both levels of abstraction and theoretical (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  49. Fast-Collapsing Theories.Samuel A. Alexander - 2013 - Studia Logica (1):1-21.
    Reinhardt’s conjecture, a formalization of the statement that a truthful knowing machine can know its own truthfulness and mechanicalness, was proved by Carlson using sophisticated structural results about the ordinals and transfinite induction just beyond the first epsilon number. We prove a weaker version of the conjecture, by elementary methods and transfinite induction up to a smaller ordinal.
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  50. Sobre s História da Paraconsistência e a Obra de Da Costa: A Instauração da Lógica Paraconsistente.Evandro Luis Gomes - 2013 - Dissertation, University of Campinas, Brazil
1 — 50 / 147