Results for 'artificial general intelligence'

996 found
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  1. Risks of Artificial General Intelligence.Vincent C. Müller (ed.) - 2014 - Taylor & Francis (JETAI).
    Special Issue “Risks of artificial general intelligence”, Journal of Experimental and Theoretical Artificial Intelligence, 26/3 (2014), ed. Vincent C. Müller. http://www.tandfonline.com/toc/teta20/26/3# - Risks of general artificial intelligence, Vincent C. Müller, pages 297-301 - Autonomous technology and the greater human good - Steve Omohundro - pages 303-315 - - - The errors, insights and lessons of famous AI predictions – and what they mean for the future - Stuart Armstrong, Kaj Sotala & Seán (...)
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  2. Literature Review: What Artificial General Intelligence Safety Researchers Have Written About the Nature of Human Values.Alexey Turchin & David Denkenberger - manuscript
    Abstract: The field of artificial general intelligence (AGI) safety is quickly growing. However, the nature of human values, with which future AGI should be aligned, is underdefined. Different AGI safety researchers have suggested different theories about the nature of human values, but there are contradictions. This article presents an overview of what AGI safety researchers have written about the nature of human values, up to the beginning of 2019. 21 authors were overviewed, and some of them have (...)
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  3. Post-Turing Methodology: Breaking the Wall on the Way to Artificial General Intelligence.Albert Efimov - 2020 - Lecture Notes in Computer Science 12177.
    This article offers comprehensive criticism of the Turing test and develops quality criteria for new artificial general intelligence (AGI) assessment tests. It is shown that the prerequisites A. Turing drew upon when reducing personality and human consciousness to “suitable branches of thought” re-flected the engineering level of his time. In fact, the Turing “imitation game” employed only symbolic communication and ignored the physical world. This paper suggests that by restricting thinking ability to symbolic systems alone Turing unknowingly (...)
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  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 (...)
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  5. Can the G Factor Play a Role in Artificial General Intelligence Research?Davide Serpico & Marcello Frixione - 2018 - In Proceedings of the Society for the Study of Artificial Intelligence and Simulation of Behaviour 2018. pp. 301-305.
    In recent years, a trend in AI research has started to pursue human-level, general artificial intelli-gence (AGI). Although the AGI framework is characterised by different viewpoints on what intelligence is and how to implement it in artificial systems, it conceptualises intelligence as flexible, general-purposed, and capable of self-adapting to different contexts and tasks. Two important ques-tions remain open: a) should AGI projects simu-late the biological, neural, and cognitive mecha-nisms realising the human intelligent behaviour? and (...)
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  6. 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 (...)
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  7. Advantages of Artificial Intelligences, Uploads, and Digital Minds.Kaj Sotala - 2012 - International Journal of Machine Consciousness 4 (01):275-291.
    I survey four categories of factors that might give a digital mind, such as an upload or an artificial general intelligence, an advantage over humans. Hardware advantages include greater serial speeds and greater parallel speeds. Self-improvement advantages include improvement of algorithms, design of new mental modules, and modification of motivational system. Co-operative advantages include copyability, perfect co-operation, improved communication, and transfer of skills. Human handicaps include computational limitations and faulty heuristics, human-centric biases, and socially motivated cognition. The (...)
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  8.  45
    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.
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  9. On Controllability of Artificial Intelligence.Roman Yampolskiy - manuscript
    Invention of artificial general intelligence is predicted to cause a shift in the trajectory of human civilization. In order to reap the benefits and avoid pitfalls of such powerful technology it is important to be able to control it. However, possibility of controlling artificial general intelligence and its more advanced version, superintelligence, has not been formally established. In this paper, we present arguments as well as supporting evidence from multiple domains indicating that advanced AI (...)
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  10. One Decade of Universal Artificial Intelligence.Marcus Hutter - 2012 - In Pei Wang & Ben Goertzel (eds.), Theoretical Foundations of Artificial General Intelligence. Springer. pp. 67--88.
    The first decade of this century has seen the nascency of the first mathematical theory of general artificial intelligence. This theory of Universal Artificial Intelligence (UAI) has made significant contributions to many theoretical, philosophical, and practical AI questions. In a series of papers culminating in book (Hutter, 2005), an exciting sound and complete mathematical model for a super intelligent agent (AIXI) has been developed and rigorously analyzed. While nowadays most AI researchers avoid discussing intelligence, (...)
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  11. Ethics of Artificial Intelligence and Robotics.Vincent C. Müller - 2020 - In Edward Zalta (ed.), Stanford Encyclopedia of Philosophy. Palo Alto, Cal.: CSLI, Stanford University. pp. 1-70.
    Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made (...)
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  12. Risks of Artificial Intelligence.Vincent C. Müller (ed.) - 2016 - CRC Press - Chapman & Hall.
    Papers from the conference on AI Risk (published in JETAI), supplemented by additional work. --- If the intelligence of artificial systems were to surpass that of humans, humanity would face significant risks. The time has come to consider these issues, and this consideration must include progress in artificial intelligence (AI) as much as insights from AI theory. -- Featuring contributions from leading experts and thinkers in artificial intelligence, Risks of Artificial Intelligence is (...)
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  13. 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 (...)
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  14.  42
    Artificial Intelligence as Art – What the Philosophy of Art Can Offer the Understanding of AI and Consciousness.Hutan Ashrafian - manuscript
    Defining Artificial Intelligence and Artificial General Intelligence remain controversial and disputed. They stem from a longer-standing controversy of what is the definition of consciousness, which if solved could possibly offer a solution to defining AI and AGI. Central to these problems is the paradox that appraising AI and Consciousness requires epistemological objectivity of domains that are ontologically subjective. I propose that applying the philosophy of art, which also aims to define art through a lens of (...)
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  15. Ethical Issues in Advanced Artificial Intelligence.Nick Bostrom - manuscript
    The ethical issues related to the possible future creation of machines with general intellectual capabilities far outstripping those of humans are quite distinct from any ethical problems arising in current automation and information systems. Such superintelligence would not be just another technological development; it would be the most important invention ever made, and would lead to explosive progress in all scientific and technological fields, as the superintelligence would conduct research with superhuman efficiency. To the extent that ethics is a (...)
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  16. First Steps Towards an Ethics of Robots and Artificial Intelligence.John Tasioulas - 2019 - Journal of Practical Ethics 7 (1):61-95.
    This article offers an overview of the main first-order ethical questions raised by robots and Artificial Intelligence (RAIs) under five broad rubrics: functionality, inherent significance, rights and responsibilities, side-effects, and threats. The first letter of each rubric taken together conveniently generates the acronym FIRST. Special attention is given to the rubrics of functionality and inherent significance given the centrality of the former and the tendency to neglect the latter in virtue of its somewhat nebulous and contested character. In (...)
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  17. Philosophy and Theory of Artificial Intelligence.Vincent C. Müller (ed.) - 2013 - Springer.
    [Müller, Vincent C. (ed.), (2013), Philosophy and theory of artificial intelligence (SAPERE, 5; Berlin: Springer). 429 pp. ] --- Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human (...)
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  18.  37
    The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence.David S. Watson - 2019 - Minds and Machines 29 (3):417-440.
    Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three (...)
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  19.  5
    How Does Artificial Intelligence Pose an Existential Risk?Karina Vold & Daniel R. Harris - forthcoming - In Carissa Véliz (ed.), Oxford Handbook of Digital Ethics.
    Alan Turing, one of the fathers of computing, warned that Artificial Intelligence (AI) could one day pose an existential risk to humanity. Today, recent advancements in the field AI have been accompanied by a renewed set of existential warnings. But what exactly constitutes an existential risk? And how exactly does AI pose such a threat? In this chapter we aim to answer these questions. In particular, we will critically explore three commonly cited reasons for thinking that AI poses (...)
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  20. Punishing Artificial Intelligence: Legal Fiction or Science Fiction.Alexander Sarch & Ryan Abbott - 2019 - UC Davis Law Review 53:323-384.
    Whether causing flash crashes in financial markets, purchasing illegal drugs, or running over pedestrians, AI is increasingly engaging in activity that would be criminal for a natural person, or even an artificial person like a corporation. We argue that criminal law falls short in cases where an AI causes certain types of harm and there are no practically or legally identifiable upstream criminal actors. This Article explores potential solutions to this problem, focusing on holding AI directly criminally liable where (...)
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  21. Ethics of Artificial Intelligence.Vincent C. Müller - forthcoming - In Anthony Elliott (ed.), The Routledge social science handbook of AI. London: Routledge. pp. 1-20.
    Artificial intelligence (AI) is a digital technology that will be of major importance for the development of humanity in the near future. AI has raised fundamental questions about what we should do with such systems, what the systems themselves should do, what risks they involve and how we can control these. - After the background to the field (1), this article introduces the main debates (2), first on ethical issues that arise with AI systems as objects, i.e. tools (...)
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  22.  91
    Making Moral Machines: Why We Need Artificial Moral Agents.Paul Formosa & Malcolm Ryan - forthcoming - AI and Society.
    As robots and Artificial Intelligences become more enmeshed in rich social contexts, it seems inevitable that we will have to make them into moral machines equipped with moral skills. Apart from the technical difficulties of how we could achieve this goal, we can also ask the ethical question of whether we should seek to create such Artificial Moral Agents (AMAs). Recently, several papers have argued that we have strong reasons not to develop AMAs. In response, we develop a (...)
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  23. An Analysis of the Interaction Between Intelligent Software Agents and Human Users.Christopher Burr, Nello Cristianini & James Ladyman - 2018 - Minds and Machines 28 (4):735-774.
    Interactions between an intelligent software agent and a human user are ubiquitous in everyday situations such as access to information, entertainment, and purchases. In such interactions, the ISA mediates the user’s access to the content, or controls some other aspect of the user experience, and is not designed to be neutral about outcomes of user choices. Like human users, ISAs are driven by goals, make autonomous decisions, and can learn from experience. Using ideas from bounded rationality, we frame these interactions (...)
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  24. Artificial Brains and Hybrid Minds.Paul Schweizer - 2017 - In Vincent C. Müller (ed.), Philosophy and Theory of Artificial Intelligence 2017. Cham, Switzerland: Springer. pp. 81-91.
    The paper develops two related thought experiments exploring variations on an ‘animat’ theme. Animats are hybrid devices with both artificial and biological components. Traditionally, ‘components’ have been construed in concrete terms, as physical parts or constituent material structures. Many fascinating issues arise within this context of hybrid physical organization. However, within the context of functional/computational theories of mentality, demarcations based purely on material structure are unduly narrow. It is abstract functional structure which does the key work in characterizing the (...)
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  25. 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 (...)
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  26. Updating the Frame Problem for Artificial Intelligence Research.Lisa Miracchi - 2020 - Journal of Artificial Intelligence and Consciousness 7 (2):217-230.
    The Frame Problem is the problem of how one can design a machine to use information so as to behave competently, with respect to the kinds of tasks a genuinely intelligent agent can reliably, effectively perform. I will argue that the way the Frame Problem is standardly interpreted, and so the strategies considered for attempting to solve it, must be updated. We must replace overly simplistic and reductionist assumptions with more sophisticated and plausible ones. In particular, the standard interpretation assumes (...)
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  27. How Feasible is the Rapid Development of Artificial Superintelligence?Kaj Sotala - 2017 - Physica Scripta 11 (92).
    What kinds of fundamental limits are there in how capable artificial intelligence (AI) systems might become? Two questions in particular are of interest: (1) How much more capable could AI become relative to humans, and (2) how easily could superhuman capability be acquired? To answer these questions, we will consider the literature on human expertise and intelligence, discuss its relevance for AI, and consider how AI could improve on humans in two major aspects of thought and expertise, (...)
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  28.  93
    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 (...)
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  29. Human ≠ AGI.Roman Yampolskiy - manuscript
    Terms Artificial General Intelligence (AGI) and Human-Level Artificial Intelligence (HLAI) have been used interchangeably to refer to the Holy Grail of Artificial Intelligence (AI) research, creation of a machine capable of achieving goals in a wide range of environments. However, widespread implicit assumption of equivalence between capabilities of AGI and HLAI appears to be unjustified, as humans are not general intelligences. In this paper, we will prove this distinction.
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  30. There is No General AI.Jobst Landgrebe & Barry Smith - 2020 - arXiv.
    The goal of creating Artificial General Intelligence (AGI) – or in other words of creating Turing machines (modern computers) that can behave in a way that mimics human intelligence – has occupied AI researchers ever since the idea of AI was first proposed. One common theme in these discussions is the thesis that the ability of a machine to conduct convincing dialogues with human beings can serve as at least a sufficient criterion of AGI. We argue (...)
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  31. Presumptuous Aim Attribution, Conformity, and the Ethics of Artificial Social Cognition.Owen C. King - 2020 - Ethics and Information Technology 22 (1):25-37.
    Imagine you are casually browsing an online bookstore, looking for an interesting novel. Suppose the store predicts you will want to buy a particular novel: the one most chosen by people of your same age, gender, location, and occupational status. The store recommends the book, it appeals to you, and so you choose it. Central to this scenario is an automated prediction of what you desire. This article raises moral concerns about such predictions. More generally, this article examines the ethics (...)
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  32. Responses to Catastrophic AGI Risk: A Survey.Kaj Sotala & Roman V. Yampolskiy - 2015 - Physica Scripta 90.
    Many researchers have argued that humanity will create artificial general intelligence (AGI) within the next twenty to one hundred years. It has been suggested that AGI may inflict serious damage to human well-being on a global scale ('catastrophic risk'). After summarizing the arguments for why AGI may pose such a risk, we review the fieldʼs proposed responses to AGI risk. We consider societal proposals, proposals for external constraints on AGI behaviors and proposals for creating AGIs that are (...)
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  33.  56
    The Generalized Darwinian Research Programme.Nicholas Maxwell - 1984 - In From Knowledge to Wisdom. Blackwell. pp. 269-275.
    The generalized Darwinian research programme accepts physicalism, but holds that all life is purposive in character. It seeks to understand how and why all purposiveness has evolved in the universe – especially purposiveness associated with what we value most in human life, such as sentience, consciousness, person-to-person understanding, science, art, free¬dom, love. As evolution proceeds, the mechanisms of evolution themselves evolve to take into account the increasingly important role that purposive action can play - especially when quasi-Lamarckian evolution by cultural (...)
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  34. Experience, Memory and Intelligence.John T. Sanders - 1985 - The Monist 68 (4):507-521.
    What characterizes most technical or theoretical accounts of memory is their reliance upon an internal storage model. Psychologists and neurophysiologists have suggested neural traces (either dynamic or static) as the mechanism for this storage, and designers of artificial intelligence have relied upon the same general model, instantiated magnetically or electronically instead of neurally, to do the same job. Both psychology and artificial intelligence design have heretofore relied, without much question, upon the idea that memory is (...)
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  35. Should Machines Be Tools or Tool-Users? Clarifying Motivations and Assumptions in the Quest for Superintelligence.Dan J. Bruiger - manuscript
    Much of the basic non-technical vocabulary of artificial intelligence is surprisingly ambiguous. Some key terms with unclear meanings include intelligence, embodiment, simulation, mind, consciousness, perception, value, goal, agent, knowledge, belief, optimality, friendliness, containment, machine and thinking. Much of this vocabulary is naively borrowed from the realm of conscious human experience to apply to a theoretical notion of “mind-in-general” based on computation. However, if there is indeed a threshold between mechanical tool and autonomous agent (and a tipping (...)
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  36. Global Catastrophic Risks Connected with Extra-Terrestrial Intelligence.Alexey Turchin - manuscript
    In this article, a classification of the global catastrophic risks connected with the possible existence (or non-existence) of extraterrestrial intelligence is presented. If there are no extra-terrestrial intelligences (ETIs) in our light cone, it either means that the Great Filter is behind us, and thus some kind of periodic sterilizing natural catastrophe, like a gamma-ray burst, should be given a higher probability estimate, or that the Great Filter is ahead of us, and thus a future global catastrophe is high (...)
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  37. Why AI Doomsayers Are Like Sceptical Theists and Why It Matters.John Danaher - 2015 - Minds and Machines 25 (3):231-246.
    An advanced artificial intelligence could pose a significant existential risk to humanity. Several research institutes have been set-up to address those risks. And there is an increasing number of academic publications analysing and evaluating their seriousness. Nick Bostrom’s superintelligence: paths, dangers, strategies represents the apotheosis of this trend. In this article, I argue that in defending the credibility of AI risk, Bostrom makes an epistemic move that is analogous to one made by so-called sceptical theists in the debate (...)
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  38. Genes, Affect, and Reason: Why Autonomous Robot Intelligence Will Be Nothing Like Human Intelligence.Henry Moss - 2016 - Techné: Research in Philosophy and Technology 20 (1):1-15.
    Abstract: Many believe that, in addition to cognitive capacities, autonomous robots need something similar to affect. As in humans, affect, including specific emotions, would filter robot experience based on a set of goals, values, and interests. This narrows behavioral options and avoids combinatorial explosion or regress problems that challenge purely cognitive assessments in a continuously changing experiential field. Adding human-like affect to robots is not straightforward, however. Affect in organisms is an aspect of evolved biological systems, from the taxes of (...)
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  39. Model for Human, Artificial & Collective Consciousness (Part I).Andy E. Williams - 2019 - Journal of Consciousness Exploration and Research 10 (4):1-20.
    Borrowing the functional modeling approach common in systems and software engineering, an implementable model of the functions of human consciousness proposed to have the capacity for general problem solving ability transferable to any domain, or true self-aware intelligence, is presented. Being a functional model that is independent of implementation, this model is proposed to also be applicable to artificial consciousness, and to platforms that organize individuals into what is defined here as a first order collective consciousness, or (...)
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  40. The Motivations and Risks of Machine Ethics.Stephen Cave, Rune Nyrup, Karina Vold & Adrian Weller - 2019 - Proceedings of the IEEE 107 (3):562-574.
    Many authors have proposed constraining the behaviour of intelligent systems with ‘machine ethics’ to ensure positive social outcomes from the development of such systems. This paper critically analyses the prospects for machine ethics, identifying several inherent limitations. While machine ethics may increase the probability of ethical behaviour in some situations, it cannot guarantee it due to the nature of ethics, the computational limitations of computational agents and the complexity of the world. In addition, machine ethics, even if it were to (...)
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  41. Multistage Acquisition of Intelligent Behaviour.Brian D. Josephson & H. M. Hauser - 1981 - Kybernetes 10:11–15.
    Human skills are acquired not by a single uniform process, but in a series of stages, as Piaget has shown. We have investigated such a sequential process by taking as an illustrative example the game of table tennis. The aims in each stage of learning are qualitatively different, and we show in detail how knowledge gained during one stage provides essential information for subsequent stages. Conclusions are drawn which may be important for artificial intelligence work generally. The question (...)
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  42. 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 (...)
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  43.  66
    Consciousness for the Ouroboros Model.Knud Thomsen - 2011 - International Journal of Machine Consciousness 3 (01):163-175.
    The Ouroboros Model features a biologically inspired cognitive architecture. At its core lies a self-referential recursive process with alternating phases of data acquisition and evaluation. Memory entries are organized in schemata. The activation at a time of part of a schema biases the whole structure and, in particular, missing features, thus triggering expectations. An iterative recursive monitor process termed "consumption analysis" is then checking how well such expectations fit with successive activations. Mismatches between anticipations based on previous experience and actual (...)
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  44. Manufacturing Morality A General Theory of Moral Agency Grounding Computational Implementations: The ACTWith Model.Jeffrey White - 2013 - In Floares (ed.), Computational Intelligence. Nova Publications. pp. 1-65.
    The ultimate goal of research into computational intelligence is the construction of a fully embodied and fully autonomous artificial agent. This ultimate artificial agent must not only be able to act, but it must be able to act morally. In order to realize this goal, a number of challenges must be met, and a number of questions must be answered, the upshot being that, in doing so, the form of agency to which we must aim in developing (...)
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  45.  5
    Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation.Sandra Wachter, Brent Mittelstadt & Luciano Floridi - 2017 - International Data Privacy Law 1 (2):76-99.
    Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In contrast to (...)
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  46.  89
    Simulation Typology and Termination Risks.Alexey Turchin & Roman Yampolskiy - manuscript
    The goal of the article is to explore what is the most probable type of simulation in which humanity lives (if any) and how this affects simulation termination risks. We firstly explore the question of what kind of simulation in which humanity is most likely located based on pure theoretical reasoning. We suggest a new patch to the classical simulation argument, showing that we are likely simulated not by our own descendants, but by alien civilizations. Based on this, we provide (...)
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  47. Could Slaughterbots Wipe Out Humanity? Assessment of the Global Catastrophic Risk Posed by Autonomous Weapons.Alexey Turchin - manuscript
    Recently criticisms against autonomous weapons were presented in a video in which an AI-powered drone kills a person. However, some said that this video is a distraction from the real risk of AI—the risk of unlimitedly self-improving AI systems. In this article, we analyze arguments from both sides and turn them into conditions. The following conditions are identified as leading to autonomous weapons becoming a global catastrophic risk: 1) Artificial General Intelligence (AGI) development is delayed relative to (...)
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  48.  60
    Artificial Intelligence and the ‘Good Society’: The US, EU, and UK Approach.Corinne Cath, Sandra Wachter, Brent Mittelstadt, Mariarosaria Taddeo & Luciano Floridi - 2018 - Science and Engineering Ethics 24 (2):505-528.
    In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a ‘good AI society’. To do so, we examine how each report addresses the following three topics: the development of (...)
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  49. Artificial Intelligence and Patient-Centered Decision-Making.Jens Christian Bjerring & Jacob Busch - 2020 - Philosophy and Technology 34 (2):349-371.
    Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: the details of their contents, calculations, (...)
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  50. Narrow AI Nanny: Reaching Strategic Advantage Via Narrow AI to Prevent Creation of the Dangerous Superintelligence.Alexey Turchin - manuscript
    Abstract: As there are no currently obvious ways to create safe self-improving superintelligence, but its emergence is looming, we probably need temporary ways to prevent its creation. The only way to prevent it is to create a special type of AI that is able to control and monitor the entire world. The idea has been suggested by Goertzel in the form of an AI Nanny, but his Nanny is still superintelligent, and is not easy to control. We explore here ways (...)
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