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  1. 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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  2. 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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  3. 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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  4. 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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  5. 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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  6. Representation, Analytic Pragmatism and AI.Raffaela Giovagnoli - 2013 - In Gordana Dodig-Crnkovic Raffaela Giovagnoli (ed.), Computing Nature. pp. 161--169.
    Our contribution aims at individuating a valid philosophical strategy for a fruitful confrontation between human and artificial representation. The ground for this theoretical option resides in the necessity to find a solution that overcomes, on the one side, strong AI (i.e. Haugeland) and, on the other side, the view that rules out AI as explanation of human capacities (i.e. Dreyfus). We try to argue for Analytic Pragmatism (AP) as a valid strategy to present arguments for a form of weak AI (...)
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  7. Architectures of Intelligent Systems.David Kirsh - 1992 - Exploring Brain Functions:293-321.
    Theories of intelligence can be of use to neuroscientists if they: 1. Provide illuminating suggestions about the functional architecture of neural systems; 2. Suggest specific models of processing that neural circuits might implement. The objective of our session was to stand back and consider the prospects for this interdisciplinary exchange.
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  8. El Mito de Lo Mental: El Proyecto de Investigación de la Inteligencia Artificial y la Transformación Hermenéutica de la Fenomenología (Primera Parte).Jethro Masís - 2011 - Eikasís. Revista de Filosofía (41).
    In its two parts, this study intends to reconstruct with some detail the fiasco of the Artificial Intelligence research project and the devastating critique carried out against it by Hubert Dreyfus in his magnum opus What Computers Still Can’t Do (1972, 1979, 1992). Part of these consequences is the emergence within this specialized field of a group of scholars who have called themselves ‘Heideggerian’. This definition shall be dealt with and criticized in the second part of this study. In this (...)
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  9. A Modal Defence of Strong AI.Steffen Borge - 2007 - In Dermot Moran Stephen Voss (ed.), The Proceedings of the Twenty-First World Congress of Philosophy. The Philosophical Society of Turkey. pp. 127-131.
    John Searle has argued that the aim of strong AI of creating a thinking computer is misguided. Searle’s Chinese Room Argument purports to show that syntax does not suffice for semantics and that computer programs as such must fail to have intrinsic intentionality. But we are not mainly interested in the program itself but rather the implementation of the program in some material. It does not follow by necessity from the fact that computer programs are defined syntactically that the implementation (...)
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  10. What's New Here?Bruce Mangan - 1999 - Behavioral and Brain Sciences 22 (1):160-161.
    O'Brien & Opie's (O&O's) theory demands a view of unconscious processing that is incompatible with virtually all current PDP models of neural activity. Relative to the alternatives, the theory is closer to an AI than a parallel distributed processing (PDP) perspective, and its treatment of phenomenology is ad hoc. It raises at least one important question: Could features of network relaxation be the “switch” that turns an unconscious into a conscious network?
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Artificial Intelligence Methodology
  1. The Feeling Body: Towards an Enactive Approach to Emotion.Giovanna Colombetti & Evan Thompson - 2008 - In W. F. Overton, U. Müller & J. L. Newman (eds.), Developmental Perspectives on Embodiment and Consciousness. Erlbaum.
    For many years emotion theory has been characterized by a dichotomy between the head and the body. In the golden years of cognitivism, during the nineteen-sixties and seventies, emotion theory focused on the cognitive antecedents of emotion, the so-called “appraisal processes.” Bodily events were seen largely as byproducts of cognition, and as too unspecific to contribute to the variety of emotion experience. Cognition was conceptualized as an abstract, intellectual, “heady” process separate from bodily events. Although current emotion theory has moved (...)
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  2. There is No General AI: Why Turing Machines Cannot Pass the Turing Test.Jobst Landgrebe & Barry Smith - 2019 - arXiv.
    Since 1950, when Alan Turing proposed what has since come to be called the Turing test, the ability of a machine to pass this test has established itself as the primary hallmark of general AI. To pass the test, a machine would have to be able to engage in dialogue in such a way that a human interrogator could not distinguish its behaviour from that of a human being. AI researchers have attempted to build machines that could meet this requirement, (...)
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  3. In 30 Schritten zum Mond? Zukünftiger Fortschritt in der KI.Vincent C. Müller - 2018 - Medienkorrespondenz 20 (05.10.2018):5-15.
    Die Entwicklungen in der Künstlichen Intelligenz (KI) sind spannend. Aber wohin geht die Reise? Ich stelle eine Analyse vor, der zufolge exponentielles Wachstum von Rechengeschwindigkeit und Daten die entscheidenden Faktoren im bisherigen Fortschritt waren. Im Folgenden erläutere ich, unter welchen Annahmen dieses Wachstum auch weiterhin Fortschritt ermöglichen wird: 1) Intelligenz ist eindimensional und messbar, 2) Kognitionswissenschaft wird für KI nicht benötigt, 3) Berechnung (computation) ist hinreichend für Kognition, 4) Gegenwärtige Techniken und Architektur sind ausreichend skalierbar, 5) Technological Readiness Levels (TRL) (...)
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  4. Making AI Meaningful Again.Jobst Landgrebe & Barry Smith - 2019 - Synthese:arXiv:1901.02918v1.
    Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial (...)
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  5. From Human to Artificial Cognition and Back: New Perspectives on Cognitively Inspired AI Systems.Antonio Lieto & Daniele Radicioni - 2016 - Cognitive Systems Research 39 (c):1-3.
    We overview the main historical and technological elements characterising the rise, the fall and the recent renaissance of the cognitive approaches to Artificial Intelligence and provide some insights and suggestions about the future directions and challenges that, in our opinion, this discipline needs to face in the next years.
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  6. An Expert System for Feeding Problems in Infants and Children.Samy S. Abu Naser & Mariam W. Alawar - 2016 - International Journal of Medicine Research 1 (2):79--82.
    A lot of infants have significant food-related problems, as well as spitting up, rejecting new foods, or not accepting to eat at specific times. These issues are frequently ordinary and are not a sign that the baby is unwell. According to the National Institutes of Health, 25% of generally developing infants and 35% of babies with neurodevelopmental disabilities are tormented by some sort of feeding problem. Some, for example rejecting to eat specific foods or being overly finicky, are momentary and (...)
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  7. La subjectivité artificielle : ébauche d'un projet de recherche.Jean-Jacques Pinto - manuscript
    Subjectivité artificielle: -/- •pléonasme, s'il est exact que la subjectivité humaine ne peut être qu'artificielle, cf infra subjiciel© -/- •terme proposé par l'auteur de l'A.L.S.© (Jean-Jacques Pinto) pour faire pendant à celui d'Intelligence artificielle -/- Subjiciel© : terme forgé (et déposé comme marque à l'I.N.P.I. en 1984) par l'auteur de l'A.L.S. : Jacques Pinto) : -/- 1. programmesubjectif "naturel", mais il se pourrait bien que la subjectivité humaine ne puisse être qu'artificielle : il n'y a pas de "nature humaine", seulement (...)
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  8. Why Build a Virtual Brain? Large-Scale Neural Simulations as Jump Start for Cognitive Computing.Matteo Colombo - 2016 - Journal of Experimental and Theoretical Artificial Intelligence.
    Despite the impressive amount of financial resources recently invested in carrying out large-scale brain simulations, it is controversial what the pay-offs are of pursuing this project. One idea is that from designing, building, and running a large-scale neural simulation, scientists acquire knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. It has been claimed that this knowledge may usher in a new era of neuromorphic, cognitive computing systems. This study elucidates (...)
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  9. Simple or Complex Bodies? Trade-Offs in Exploiting Body Morphology for Control.Matej Hoffmann & Vincent C. Müller - 2017 - In Gordana Dodig-Crnkovic & Raffaela Giovagnoli (eds.), Representation of Reality: Humans, Other Living Organisms and Intelligent Machines. Berlin: Springer. pp. 335-345.
    Engineers fine-tune the design of robot bodies for control purposes, however, a methodology or set of tools is largely absent, and optimization of morphology (shape, material properties of robot bodies, etc.) is lagging behind the development of controllers. This has become even more prominent with the advent of compliant, deformable or ”soft” bodies. These carry substantial potential regarding their exploitation for control—sometimes referred to as ”morphological computation”. In this article, we briefly review different notions of computation by physical systems and (...)
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  10. Theory and Philosophy of AI (Minds and Machines, 22/2 - Special Volume).Vincent C. Müller (ed.) - 2012 - Springer.
    Invited papers from PT-AI 2011. - Vincent C. Müller: Introduction: Theory and Philosophy of Artificial Intelligence - Nick Bostrom: The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents - Hubert L. Dreyfus: A History of First Step Fallacies - Antoni Gomila, David Travieso and Lorena Lobo: Wherein is Human Cognition Systematic - J. Kevin O'Regan: How to Build a Robot that Is Conscious and Feels - Oron Shagrir: Computation, Implementation, Cognition.
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  11. Challenges for Artificial Cognitive Systems.Antoni Gomila & Vincent C. Müller - 2012 - Journal of Cognitive Science 13 (4):452-469.
    The declared goal of this paper is to fill this gap: “... cognitive systems research needs questions or challenges that define progress. The challenges are not (yet more) predictions of the future, but a guideline to what are the aims and what would constitute progress.” – the quotation being from the project description of EUCogII, the project for the European Network for Cognitive Systems within which this formulation of the ‘challenges’ was originally developed (http://www.eucognition.org). So, we stick out our neck (...)
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  12. Cognitive Behavioural Systems.Esposito Anna, Esposito Antonietta M., Hoffmann Rüdiger, Müller Vincent C. & Vinciarelli Alessandro (eds.) - 2012 - Springer.
    This book constitutes refereed proceedings of the COST 2102 International Training School on Cognitive Behavioural Systems held in Dresden, Germany, in February 2011. The 39 revised full papers presented were carefully reviewed and selected from various submissions. The volume presents new and original research results in the field of human-machine interaction inspired by cognitive behavioural human-human interaction features. The themes covered are on cognitive and computational social information processing, emotional and social believable Human-Computer Interaction (HCI) systems, behavioural and contextual analysis (...)
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  13. Knowledge Bases and Neural Network Synthesis.Todd R. Davies - 1991 - In Hozumi Tanaka (ed.), Artificial Intelligence in the Pacific Rim: Proceedings of the Pacific Rim International Conference on Artificial Intelligence. IOS Press. pp. 717-722.
    We describe and try to motivate our project to build systems using both a knowledge based and a neural network approach. These two approaches are used at different stages in the solution of a problem, instead of using knowledge bases exclusively on some problems, and neural nets exclusively on others. The knowledge base (KB) is defined first in a declarative, symbolic language that is easy to use. It is then compiled into an efficient neural network (NN) representation, run, and the (...)
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  14. A Logical Approach to Reasoning by Analogy.Todd R. Davies & Stuart J. Russell - 1987 - In John P. McDermott (ed.), Proceedings of the 10th International Joint Conference on Artificial Intelligence (IJCAI'87). Morgan Kaufmann Publishers. pp. 264-270.
    We analyze the logical form of the domain knowledge that grounds analogical inferences and generalizations from a single instance. The form of the assumptions which justify analogies is given schematically as the "determination rule", so called because it expresses the relation of one set of variables determining the values of another set. The determination relation is a logical generalization of the different types of dependency relations defined in database theory. Specifically, we define determination as a relation between schemata of first (...)
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  15. Evaluating Artificial Models of Cognition.Marcin Miłkowski - 2015 - Studies in Logic, Grammar and Rhetoric 40 (1):43-62.
    Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue that proper evaluation ofmodels (...)
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  16. Was Roboter nicht können. Die Roboterantwort als knapp misslungene Verteidigung der starken KI-These.Geert Keil - 1998 - In Andreas Engel & Peter Gold (eds.), Der Mensch in der Perspektive der Kognitionswissenschaften. Suhrkamp. pp. 98-131.
    Theoretiker der Künstlichen Intelligenz und deren Wegbegleiter in der Philosophie des Geistes haben auf unterschiedliche Weise auf Kritik am ursprünglichen Theorieziel der KI reagiert. Eine dieser Reaktionen ist die Zurücknahme dieses Theorieziels zugunsten der Verfolgung kleinerformatiger Projekte. Eine andere Reaktion ist die Propagierung konnektionistischer Systeme, die mit ihrer dezentralen Arbeitsweise die neuronalen Netze des menschlichen Gehirns besser simulieren sollen. Eine weitere ist die sogenannte robot reply. Die Roboterantwort besteht aus zwei Elementen. Sie enthält (a) das Zugeständnis, daß das Systemverhalten eines (...)
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  17. Applied Ontology: A New Discipline is Born.B. Smith - 1998 - Philosophy Today 12 (29):5-6.
    The discipline of applied ethics already has a certain familiarity in the Anglo-Saxon world, above all through the work of Peter Singer. Applied ethics uses the tools of moral philosophy to resolve practical problems of the sort which arise, for example, in the running of hospitals. In the University at Buffalo (New York) there was organized on April 24-25 1998 the world's first conference on a new, sister discipline, the discipline of applied ontology. Applied ontologists seek to apply ontological tools (...)
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  18. A Lesson From Subjective Computing: Autonomous Self-Referentiality and Social Interaction as Conditions for Subjectivity.Patrick Grüneberg & Kenji Suzuki - 2013 - AISB Proceedings 2012:18-28.
    In this paper, we model a relational notion of subjectivity by means of two experiments in subjective computing. The goal is to determine to what extent a cognitive and social robot can be regarded to act subjectively. The system was implemented as a reinforcement learning agent with a coaching function. To analyze the robotic agent we used the method of levels of abstraction in order to analyze the agent at four levels of abstraction. At one level the agent is described (...)
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  19. Dealing with Concepts: From Cognitive Psychology to Knowledge Representation.Marcello Frixione & Antonio Lieto - 2013 - Frontiers of Psychological and Behevioural Science 2 (3):96-106.
    Concept representation is still an open problem in the field of ontology engineering and, more generally, of knowledge representation. In particular, the issue of representing “non classical” concepts, i.e. concepts that cannot be defined in terms of necessary and sufficient conditions, remains unresolved. In this paper we review empirical evidence from cognitive psychology, according to which concept representation is not a unitary phenomenon. On this basis, we sketch some proposals for concept representation, taking into account suggestions from psychological research. In (...)
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  20. The Discovery of the Artificial: Behavior, Mind and Machines Before and Beyond Cybernetics.Roberto Cordeschi - 2002 - Kluwer Academic Publishers.
    Since the second half of the XXth century, researchers in cybernetics and AI, neural nets and connectionism, Artificial Life and new robotics have endeavoured to build different machines that could simulate functions of living organisms, such as adaptation and development, problem solving and learning. In this book these research programs are discussed, particularly as regard the epistemological issues of the behaviour modelling. One of the main novelty of this book consists of the fact that certain projects involving the building of (...)
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  21. A Plea for Automated Language-to-Logical-Form Converters.Joseph S. Fulda - 2006 - RASK 24:87-102.
    This has been made available gratis by the publisher. -/- This piece gives the raison d'etre for the development of the converters mentioned in the title. Three reasons are given, one linguistic, one philosophical, and one practical. It is suggested that at least /two/ independent converters are needed. -/- This piece ties together the extended paper "Abstracts from Logical Form I/II," and the short piece providing the comprehensive theory alluded to in the abstract of that extended paper in "Pragmatics, Montague, (...)
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  22. Gdzie jesteś, HAL?Jarek Gryz - 2013 - Przegląd Filozoficzny 22 (2):167-184.
    Sztuczna inteligencja pojawiła się jako dziedzina badawcza ponad 60 lat temu. Po spektakularnych sukcesach na początku jej istnienia oczekiwano pojawienia się maszyn myślących w ciągu kilku lat. Prognoza ta zupełnie się nie sprawdziła. Nie dość, że maszyny myślącej dotąd nie zbudowano, to nie ma zgodności wśród naukowców czym taka maszyna miałaby się charakteryzować ani nawet czy warto ją w ogóle budować. W artykule tym postaramy się prześledzić dyskusję metodologiczną towarzyszącą sztucznej inteligencji od początku jej istnienia i określić relację między sztuczną (...)
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  23. Framework of Consciousness From Semblance of Activity at Functionally LINKed Postsynaptic Membranes.Kunjumon Vadakkan - 2010 - Frontiers in Consciousness Research 1 (1):1-12.
    Consciousness is seen as a difficult “binding” problem. Binding, a process where different sensations evoked by an item are associated in the nervous system, can be viewed as a process similar to associative learning. Several reports that consciousness is associated with some form of memory imply that different forms of memories have a common feature contributing to consciousness. Based on a proposed synaptic mechanism capable of explaining different forms of memory, we developed a framework for consciousness. It is based on (...)
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  24. Determination, Uniformity, and Relevance: Normative Criteria for Generalization and Reasoning by Analogy.Todd R. Davies - 1988 - In David H. Helman (ed.), Analogical Reasoning. Kluwer Academic Publishers. pp. 227-250.
    This paper defines the form of prior knowledge that is required for sound inferences by analogy and single-instance generalizations, in both logical and probabilistic reasoning. In the logical case, the first order determination rule defined in Davies (1985) is shown to solve both the justification and non-redundancy problems for analogical inference. The statistical analogue of determination that is put forward is termed 'uniformity'. Based on the semantics of determination and uniformity, a third notion of "relevance" is defined, both logically and (...)
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  25. Computationalism Under Attack.Roberto Cordeschi & Marcello Frixione - 2007 - In M. Marraffa, M. De Caro & F. Ferretti (eds.), Cartographies of the Mind: Philosophy and Psychology in Intersection. Springer.
    Since the early eighties, computationalism in the study of the mind has been “under attack” by several critics of the so-called “classic” or “symbolic” approaches in AI and cognitive science. Computationalism was generically identified with such approaches. For example, it was identified with both Allen Newell and Herbert Simon’s Physical Symbol System Hypothesis and Jerry Fodor’s theory of Language of Thought, usually without taking into account the fact ,that such approaches are very different as to their methods and aims. Zenon (...)
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  26. Decision Theory, Intelligent Planning and Counterfactuals.Michael John Shaffer - 2009 - Minds and Machines 19 (1):61-92.
    The ontology of decision theory has been subject to considerable debate in the past, and discussion of just how we ought to view decision problems has revealed more than one interesting problem, as well as suggested some novel modifications of classical decision theory. In this paper it will be argued that Bayesian, or evidential, decision-theoretic characterizations of decision situations fail to adequately account for knowledge concerning the causal connections between acts, states, and outcomes in decision situations, and so they are (...)
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The Nature of Artificial Intelligence
  1. Social Machinery and Intelligence.Nello Cristianini, James Ladyman & Teresa Scantamburlo - manuscript
    Social machines are systems formed by technical and human elements interacting in a structured manner. The use of digital platforms as mediators allows large numbers of human participants to join such mechanisms, creating systems where interconnected digital and human components operate as a single machine capable of highly sophisticated behaviour. Under certain conditions, such systems can be described as autonomous and goal-driven agents. Many examples of modern Artificial Intelligence (AI) can be regarded as instances of this class of mechanisms. We (...)
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  2. Del hombre-máquina a la máquina-hombre: materialismo, mecanicismo y transhumanismo.Martín López Corredoira - 2019 - Naturaleza y Libertad. Revista de Estudios Interdisciplinares 12:179-190.
    El materialismo de la Edad Moderna nos describe al hombre como una máquina, comparable a un complejo artilugio mecánico. Cabe entonces imaginar que una máquina no-biológica pueda constituir un ser pensante como lo son los seres humanos, e incluso cabría pensar en la posibilidad de codificación de una mente humana real para su posterior trasvase a un sustrato artificial. Considero que estas últimas posiciones son más propias de la cultura friki o de amantes de la ciencia ficción que de una (...)
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  3. Challenges for an Ontology of Artificial Intelligence.Scott H. Hawley - forthcoming - Perspectives on Science and Christian Faith.
    Of primary importance in formulating a response to the increasing prevalence and power of artificial intelligence (AI) applications in society are questions of ontology. Questions such as: What “are” these systems? How are they to be regarded? How does an algorithm come to be regarded as an agent? We discuss three factors which hinder discussion and obscure attempts to form a clear ontology of AI: (1) the various and evolving definitions of AI, (2) the tendency for pre-existing technologies to be (...)
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  4. Will Hominoids or Androids Destroy the Earth? —A Review of How to Create a Mind by Ray Kurzweil (2012) (Review Revised 2019).Michael Starks - 2019 - In Suicidal Utopian Delusions in the 21st Century -- Philosophy, Human Nature and the Collapse of Civilization-- Articles and Reviews 2006-2019 4th Edition Michael Starks. Las Vegas, NV USA: Reality Press. pp. 265-277.
    Some years ago, I reached the point where I can usually tell from the title of a book, or at least from the chapter titles, what kinds of philosophical mistakes will be made and how frequently. In the case of nominally scientific works these may be largely restricted to certain chapters which wax philosophical or try to draw general conclusions about the meaning or long term significance of the work. Normally however the scientific matters of fact are generously interlarded with (...)
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  5. In 30 Schritten zum Mond? Zukünftiger Fortschritt in der KI.Vincent C. Müller - 2018 - Medienkorrespondenz 20 (05.10.2018):5-15.
    Die Entwicklungen in der Künstlichen Intelligenz (KI) sind spannend. Aber wohin geht die Reise? Ich stelle eine Analyse vor, der zufolge exponentielles Wachstum von Rechengeschwindigkeit und Daten die entscheidenden Faktoren im bisherigen Fortschritt waren. Im Folgenden erläutere ich, unter welchen Annahmen dieses Wachstum auch weiterhin Fortschritt ermöglichen wird: 1) Intelligenz ist eindimensional und messbar, 2) Kognitionswissenschaft wird für KI nicht benötigt, 3) Berechnung (computation) ist hinreichend für Kognition, 4) Gegenwärtige Techniken und Architektur sind ausreichend skalierbar, 5) Technological Readiness Levels (TRL) (...)
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  6. Making AI Meaningful Again.Jobst Landgrebe & Barry Smith - 2019 - Synthese:arXiv:1901.02918v1.
    Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial (...)
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  7. Modeling Economic Systems as Locally-Constructive Sequential Games.Leigh Tesfatsion - 2017 - Journal of Economic Methodology 24 (4):1-26.
    Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these essential properties imply real-world economies are locally-constructive sequential games. This paper discusses a modeling approach, (...)
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  8. Will Hominoids or Androids Destroy the Earth? —A Review of How to Create a Mind by Ray Kurzweil (2012).Michael Starks - 2017 - In Suicidal Utopian Delusions in the 21st Century 4th ed (2019). Henderson, NV USA: Michael Starks. pp. 675.
    Some years ago I reached the point where I can usually tell from the title of a book, or at least from the chapter titles, what kinds of philosophical mistakes will be made and how frequently. In the case of nominally scientific works these may be largely restricted to certain chapters which wax philosophical or try to draw general conclusions about the meaning or long term significance of the work. Normally however the scientific matters of fact are generously interlarded with (...)
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  9. Artificial Consciousness and the Consciousness-Attention Dissociation.Harry Haroutioun Haladjian & Carlos Montemayor - 2016 - Consciousness and Cognition 45:210-225.
    Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to implement sophisticated forms of human intelligence in machines. This research attempts to model specific forms of intelligence through brute-force search heuristics and also reproduce features of human perception and cognition, including emotions. Such goals have implications for artificial consciousness, with some arguing that it will be achievable once we overcome short-term engineering challenges. We believe, however, that phenomenal consciousness cannot be implemented in machines. This becomes (...)
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  10. Analogy, Mind, and Life.Vitor Manuel Dinis Pereira - 2015 - In Quoc Nam Tran & Hamid Arabnia (eds.), Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology. Elsevier. pp. 377–388.
    I'll show that the kind of analogy between life and information – that seems to be central to the effect that artificial mind may represents an expected advance in the life evolution in Universe – is like the design argument and that if the design argument is unfounded and invalid, the argument to the effect that artificial mind may represents an expected advance in the life evolution in Universe is also unfounded and invalid. However, if we are prepared to admit (...)
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  11. 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.
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  12. New Developments in the Philosophy of AI.Vincent Müller - 2016 - In Fundamental Issues of Artificial Intelligence. Springer.
    The philosophy of AI has seen some changes, in particular: 1) AI moves away from cognitive science, and 2) the long term risks of AI now appear to be a worthy concern. In this context, the classical central concerns – such as the relation of cognition and computation, embodiment, intelligence & rationality, and information – will regain urgency.
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  13. Future Progress in Artificial Intelligence: A Survey of Expert Opinion.Vincent C. Müller & Nick Bostrom - 2016 - In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence. Springer. pp. 553-571.
    There is, in some quarters, concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development, and how fast they see these developing. We thus (...)
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  14. Editorial: Risks of General Artificial Intelligence.Vincent C. Müller - 2014 - Journal of Experimental and Theoretical Artificial Intelligence 26 (3):297-301.
    This is the editorial for a special volume of JETAI, featuring papers by Omohundro, Armstrong/Sotala/O’Heigeartaigh, T Goertzel, Brundage, Yampolskiy, B. Goertzel, Potapov/Rodinov, Kornai and Sandberg. - If the general intelligence of artificial systems were to surpass that of humans significantly, this would constitute a significant risk for humanity – so even if we estimate the probability of this event to be fairly low, it is necessary to think about it now. We need to estimate what progress we can expect, what (...)
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