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Computing machinery and intelligence

Mind 59 (236):433-60 (1950)

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  1. (1 other version)Minds, brains, and programs.John Searle - 1980 - Behavioral and Brain Sciences 3 (3):417-57.
    What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...)
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  • Welcoming Robots into the Moral Circle: A Defence of Ethical Behaviourism.John Danaher - 2020 - Science and Engineering Ethics 26 (4):2023-2049.
    Can robots have significant moral status? This is an emerging topic of debate among roboticists and ethicists. This paper makes three contributions to this debate. First, it presents a theory – ‘ethical behaviourism’ – which holds that robots can have significant moral status if they are roughly performatively equivalent to other entities that have significant moral status. This theory is then defended from seven objections. Second, taking this theoretical position onboard, it is argued that the performative threshold that robots need (...)
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  • (1 other version)A united framework of five principles for AI in society.Luciano Floridi & Josh Cowls - 2019 - Harvard Data Science Review 1 (1).
    Artificial Intelligence (AI) is already having a major impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles for the adoption of socially beneficial AI. Unfortunately, the sheer volume of proposed principles threatens to overwhelm and confuse. How might this problem of ‘principle proliferation’ be solved? In this paper, we report the results of a fine-grained analysis of several of the highest-profile sets of ethical principles for AI. We assess whether these (...)
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  • (1 other version)Some philosophical problems from the standpoint of artificial intelligence.John McCarthy & Patrick Hayes - 1969 - In B. Meltzer & Donald Michie (eds.), Machine Intelligence 4. Edinburgh University Press. pp. 463--502.
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  • Integrating psychology and neuroscience: functional analyses as mechanism sketches.Gualtiero Piccinini & Carl Craver - 2011 - Synthese 183 (3):283-311.
    We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...)
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  • Building machines that learn and think like people.Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum & Samuel J. Gershman - 2017 - Behavioral and Brain Sciences 40.
    Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking (...)
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  • Group Agency and Artificial Intelligence.Christian List - 2021 - Philosophy and Technology (4):1-30.
    The aim of this exploratory paper is to review an under-appreciated parallel between group agency and artificial intelligence. As both phenomena involve non-human goal-directed agents that can make a difference to the social world, they raise some similar moral and regulatory challenges, which require us to rethink some of our anthropocentric moral assumptions. Are humans always responsible for those entities’ actions, or could the entities bear responsibility themselves? Could the entities engage in normative reasoning? Could they even have rights and (...)
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  • GPT-3: its nature, scope, limits, and consequences.Luciano Floridi & Massimo Chiriatti - 2020 - Minds and Machines 30 (4):681–⁠694.
    In this commentary, we discuss the nature of reversible and irreversible questions, that is, questions that may enable one to identify the nature of the source of their answers. We then introduce GPT-3, a third-generation, autoregressive language model that uses deep learning to produce human-like texts, and use the previous distinction to analyse it. We expand the analysis to present three tests based on mathematical, semantic, and ethical questions and show that GPT-3 is not designed to pass any of them. (...)
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  • (1 other version)Minds, Machines and Gödel.John R. Lucas - 1961 - Philosophy 36 (137):112-127.
    Gödei's Theorem seems to me to prove that Mechanism is false, that is, that minds cannot be explained as machines. So also has it seemed to many other people: almost every mathematical logician I have put the matter to has confessed to similar thoughts, but has felt reluctant to commit himself definitely until he could see the whole argument set out, with all objections fully stated and properly met. This I attempt to do.
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  • The dynamical hypothesis in cognitive science.Tim van Gelder - 1998 - Behavioral and Brain Sciences 21 (5):615-28.
    According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, (...)
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  • (1 other version)Creating a large language model of a philosopher.Eric Schwitzgebel, David Schwitzgebel & Anna Strasser - 2023 - Mind and Language 39 (2):237-259.
    Can large language models produce expert‐quality philosophical texts? To investigate this, we fine‐tuned GPT‐3 with the works of philosopher Daniel Dennett. To evaluate the model, we asked the real Dennett 10 philosophical questions and then posed the same questions to the language model, collecting four responses for each question without cherry‐picking. Experts on Dennett's work succeeded at distinguishing the Dennett‐generated and machine‐generated answers above chance but substantially short of our expectations. Philosophy blog readers performed similarly to the experts, while ordinary (...)
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  • Operationalising AI ethics: barriers, enablers and next steps.Jessica Morley, Libby Kinsey, Anat Elhalal, Francesca Garcia, Marta Ziosi & Luciano Floridi - 2023 - AI and Society 38 (1):411-423.
    By mid-2019 there were more than 80 AI ethics guides available in the public domain. Despite this, 2020 saw numerous news stories break related to ethically questionable uses of AI. In part, this is because AI ethics theory remains highly abstract, and of limited practical applicability to those actually responsible for designing algorithms and AI systems. Our previous research sought to start closing this gap between the ‘what’ and the ‘how’ of AI ethics through the creation of a searchable typology (...)
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  • Mental Representation.David Pitt - 2020 - Stanford Encyclopedia of Philosophy.
    The notion of a "mental representation" is, arguably, in the first instance a theoretical construct of cognitive science. As such, it is a basic concept of the Computational Theory of Mind, according to which cognitive states and processes are constituted by the occurrence, transformation and storage (in the mind/brain) of information-bearing structures (representations) of one kind or another.
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  • Robot Betrayal: a guide to the ethics of robotic deception.John Danaher - 2020 - Ethics and Information Technology 22 (2):117-128.
    If a robot sends a deceptive signal to a human user, is this always and everywhere an unethical act, or might it sometimes be ethically desirable? Building upon previous work in robot ethics, this article tries to clarify and refine our understanding of the ethics of robotic deception. It does so by making three arguments. First, it argues that we need to distinguish between three main forms of robotic deception (external state deception; superficial state deception; and hidden state deception) in (...)
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  • Mind the gap: responsible robotics and the problem of responsibility.David J. Gunkel - 2020 - Ethics and Information Technology 22 (4):307-320.
    The task of this essay is to respond to the question concerning robots and responsibility—to answer for the way that we understand, debate, and decide who or what is able to answer for decisions and actions undertaken by increasingly interactive, autonomous, and sociable mechanisms. The analysis proceeds through three steps or movements. It begins by critically examining the instrumental theory of technology, which determines the way one typically deals with and responds to the question of responsibility when it involves technology. (...)
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  • New Materialism: Interviews and Cartographies.Rick Dolphijn & Iris van der Tuin - 2012 - Open Humanities Press.
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  • Book: Cognitive Design for Artificial Minds.Antonio Lieto - 2021 - London, UK: Routledge, Taylor & Francis Ltd.
    Book Description (Blurb): Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. -/- Beginning with an overview of the historical, methodological and technical issues in the field of Cognitively-Inspired Artificial Intelligence, (...)
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  • AI-Testimony, Conversational AIs and Our Anthropocentric Theory of Testimony.Ori Freiman - 2024 - Social Epistemology 38 (4):476-490.
    The ability to interact in a natural language profoundly changes devices’ interfaces and potential applications of speaking technologies. Concurrently, this phenomenon challenges our mainstream theories of knowledge, such as how to analyze linguistic outputs of devices under existing anthropocentric theoretical assumptions. In section 1, I present the topic of machines that speak, connecting between Descartes and Generative AI. In section 2, I argue that accepted testimonial theories of knowledge and justification commonly reject the possibility that a speaking technological artifact can (...)
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  • Modularity in cognition: Framing the debate.H. Clark Barrett & Robert Kurzban - 2006 - Psychological Review 113 (3):628-647.
    Modularity has been the subject of intense debate in the cognitive sciences for more than 2 decades. In some cases, misunderstandings have impeded conceptual progress. Here the authors identify arguments about modularity that either have been abandoned or were never held by proponents of modular views of the mind. The authors review arguments that purport to undermine modularity, with particular attention on cognitive architecture, development, genetics, and evolution. The authors propose that modularity, cleanly defined, provides a useful framework for directing (...)
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  • Consciousness, Machines, and Moral Status.Henry Shevlin - manuscript
    In light of recent breakneck pace in machine learning, questions about whether near-future artificial systems might be conscious and possess moral status are increasingly pressing. This paper argues that as matters stand these debates lack any clear criteria for resolution via the science of consciousness. Instead, insofar as they are settled at all, it is likely to be via shifts in public attitudes brought about by the increasingly close relationships between humans and AI users. Section 1 of the paper I (...)
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  • ChatGPT.Andrej Poleev - 2023 - Enzymes 21.
    As testing of ChatGPT has shown, this form of artificial intelligence has the potential to develop, which requires improving its software and other hardware that allows it to learn, i.e., to acquire and use new knowledge, to contact its developers with suggestions for improvement, or to reprogram itself without their participation. Как показало тестирование ChatGPT, эта форма искусственного интеллекта имеет потенциал развития, для чего необходимо усовершенствовать её программное и прочее техническое обеспечение, позволяющее ей учиться, т.е. приобретать и использовать новые знания, (...)
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  • If materialism is true, the United States is probably conscious.Eric Schwitzgebel - 2015 - Philosophical Studies 172 (7):1697-1721.
    If you’re a materialist, you probably think that rabbits are conscious. And you ought to think that. After all, rabbits are a lot like us, biologically and neurophysiologically. If you’re a materialist, you probably also think that conscious experience would be present in a wide range of naturally-evolved alien beings behaviorally very similar to us even if they are physiologically very different. And you ought to think that. After all, to deny it seems insupportable Earthly chauvinism. But a materialist who (...)
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  • A history of transhumanist thought.Nick Bostrom - 2005 - Journal of Evolution and Technology 14 (1):1-25.
    The human desire to acquire new capacities is as ancient as our species itself. We have always sought to expand the boundaries of our existence, be it socially, geographically, or mentally. There is a tendency in at least some individuals always to search for a way around every obstacle and limitation to human life and happiness.
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  • AI and society: a virtue ethics approach.Mirko Farina, Petr Zhdanov, Artur Karimov & Andrea Lavazza - 2024 - AI and Society 39 (3):1127-1140.
    Advances in artificial intelligence and robotics stand to change many aspects of our lives, including our values. If trends continue as expected, many industries will undergo automation in the near future, calling into question whether we can still value the sense of identity and security our occupations once provided us with. Likewise, the advent of social robots driven by AI, appears to be shifting the meaning of numerous, long-standing values associated with interpersonal relationships, like friendship. Furthermore, powerful actors’ and institutions’ (...)
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  • Is the brain a digital computer?John R. Searle - 1990 - Proceedings and Addresses of the American Philosophical Association 64 (3):21-37.
    There are different ways to present a Presidential Address to the APA; the one I have chosen is simply to report on work that I am doing right now, on work in progress. I am going to present some of my further explorations into the computational model of the mind.\**.
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  • The mind as the software of the brain.Ned Block - 1990 - In Daniel N. Osherson & Edward E. Smith (eds.), An Invitation to Cognitive Science: Visual cognition. 2. MIT Press. pp. 377-425.
    In this section, we will start with an influential attempt to define `intelligence', and then we will move to a consideration of how human intelligence is to be investigated on the machine model. The last part of the section will discuss the relation between the mental and the biological.
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  • Legal Personhood for Artificial Intelligence: Citizenship as the Exception to the Rule.Tyler L. Jaynes - 2020 - AI and Society 35 (2):343-354.
    The concept of artificial intelligence is not new nor is the notion that it should be granted legal protections given its influence on human activity. What is new, on a relative scale, is the notion that artificial intelligence can possess citizenship—a concept reserved only for humans, as it presupposes the idea of possessing civil duties and protections. Where there are several decades’ worth of writing on the concept of the legal status of computational artificial artefacts in the USA and elsewhere, (...)
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  • The physical basis of memory.C. R. Gallistel - 2021 - Cognition 213 (C):104533.
    Neuroscientists are searching for the engram within the conceptual framework established by John Locke's theory of mind. This framework was elaborated before the development of information theory, before the development of information processing machines and the science of computation, before the discovery that molecules carry hereditary information, before the discovery of the codon code and the molecular machinery for editing the messages written in this code and translating it into transcription factors that mark abstract features of organic structure such as (...)
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  • The hard problem of AI rights.Adam J. Andreotta - 2021 - AI and Society 36 (1):19-32.
    In the past few years, the subject of AI rights—the thesis that AIs, robots, and other artefacts (hereafter, simply ‘AIs’) ought to be included in the sphere of moral concern—has started to receive serious attention from scholars. In this paper, I argue that the AI rights research program is beset by an epistemic problem that threatens to impede its progress—namely, a lack of a solution to the ‘Hard Problem’ of consciousness: the problem of explaining why certain brain states give rise (...)
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  • Foundations for Moral Relativism.James David Velleman - 2013 - Cambridge, UK: OpenBook Publishers.
    In Foundations for Moral Relativism, J. David Velleman shows that different communities can indeed be subject to incompatible moralities, because their local mores are rationally binding. At the same time, he explains why the mores of different communities, even when incompatible, are still variations on the same moral themes. The book thus maps out a universe of many moral worlds without, as Velleman puts it, "moral black holes”. The five self-standing chapters discuss such diverse topics as online avatars and virtual (...)
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  • Can machines think? The controversy that led to the Turing test.Bernardo Gonçalves - 2023 - AI and Society 38 (6):2499-2509.
    Turing’s much debated test has turned 70 and is still fairly controversial. His 1950 paper is seen as a complex and multilayered text, and key questions about it remain largely unanswered. Why did Turing select learning from experience as the best approach to achieve machine intelligence? Why did he spend several years working with chess playing as a task to illustrate and test for machine intelligence only to trade it out for conversational question-answering in 1950? Why did Turing refer to (...)
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  • Minds Online: The Interface between Web Science, Cognitive Science, and the Philosophy of Mind.Paul Smart, Robert William Clowes & Richard Heersmink - 2017 - Foundations and Trends in Web Science 6 (1-2):1-234.
    Alongside existing research into the social, political and economic impacts of the Web, there is a need to study the Web from a cognitive and epistemic perspective. This is particularly so as new and emerging technologies alter the nature of our interactive engagements with the Web, transforming the extent to which our thoughts and actions are shaped by the online environment. Situated and ecological approaches to cognition are relevant to understanding the cognitive significance of the Web because of the emphasis (...)
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  • A Defense of the Rights of Artificial Intelligences.Eric Schwitzgebel & Mara Garza - 2015 - Midwest Studies in Philosophy 39 (1):98-119.
    There are possible artificially intelligent beings who do not differ in any morally relevant respect from human beings. Such possible beings would deserve moral consideration similar to that of human beings. Our duties to them would not be appreciably reduced by the fact that they are non-human, nor by the fact that they owe their existence to us. Indeed, if they owe their existence to us, we would likely have additional moral obligations to them that we don’t ordinarily owe to (...)
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  • The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence.David 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 alternative supervised learning (...)
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  • Microfunctionalism: Connectionism and the Scientific Explanation of Mental States.Andy Clark - 1989 - In Microcognition: Philosophy, Cognitive Science, and Parallel Distributed Processing. Cambridge: MIT Press.
    This is an amended version of material that first appeared in A. Clark, Microcognition: Philosophy, Cognitive Science, and Parallel Distributed Processing (MIT Press, Cambridge, MA, 1989), Ch. 1, 2, and 6. It appears in German translation in Metzinger,T (Ed) DAS LEIB-SEELE-PROBLEM IN DER ZWEITEN HELFTE DES 20 JAHRHUNDERTS (Frankfurt am Main: Suhrkamp. 1999).
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  • Subjectology • Субъектология.Andrej Poleev - 2023 - Enzymes 21.
    Subjectology (from Latin subject and logos) studies the internal states of living and nonliving systems capable of symbolic representation of any real content, i.e. to display sensory perceptible information and to transform it into world pictures, the elements of which are symbols whose meaning or sense is determined in the context of the symbolic representation. Субъектология (от лат. subject и logos) изучает внутренние состояния живых и неживых систем, способных к символической репрезентации какого–либо реального содержания, т.е. к отображению чувственно воспринимаемой информации (...)
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  • Debate: What is Personhood in the Age of AI?David J. Gunkel & Jordan Joseph Wales - 2021 - AI and Society 36 (2):473–486.
    In a friendly interdisciplinary debate, we interrogate from several vantage points the question of “personhood” in light of contemporary and near-future forms of social AI. David J. Gunkel approaches the matter from a philosophical and legal standpoint, while Jordan Wales offers reflections theological and psychological. Attending to metaphysical, moral, social, and legal understandings of personhood, we ask about the position of apparently personal artificial intelligences in our society and individual lives. Re-examining the “person” and questioning prominent construals of that category, (...)
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  • Why Be Random?Thomas Icard - 2021 - Mind 130 (517):111-139.
    When does it make sense to act randomly? A persuasive argument from Bayesian decision theory legitimizes randomization essentially only in tie-breaking situations. Rational behaviour in humans, non-human animals, and artificial agents, however, often seems indeterminate, even random. Moreover, rationales for randomized acts have been offered in a number of disciplines, including game theory, experimental design, and machine learning. A common way of accommodating some of these observations is by appeal to a decision-maker’s bounded computational resources. Making this suggestion both precise (...)
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  • Reward is enough.David Silver, Satinder Singh, Doina Precup & Richard S. Sutton - 2021 - Artificial Intelligence 299 (C):103535.
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  • On being a lonely brain‐in‐a‐vat: Structuralism, solipsism, and the threat from external world skepticism.Grace Helton - 2024 - Analytic Philosophy 65 (3):353-373.
    David Chalmers has recently developed a novel strategy of refuting external world skepticism, one he dubs the structuralist solution. In this paper, I make three primary claims: First, structuralism does not vindicate knowledge of other minds, even if it is combined with a functionalist approach to the metaphysics of minds. Second, because structuralism does not vindicate knowledge of other minds, the structuralist solution vindicates far less worldly knowledge than we would hope for from a solution to skepticism. Third, these results (...)
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  • Feeling robots and human zombies: Mind perception and the uncanny valley.Kurt Gray & Daniel M. Wegner - 2012 - Cognition 125 (1):125-130.
    The uncanny valley—the unnerving nature of humanlike robots—is an intriguing idea, but both its existence and its underlying cause are debated. We propose that humanlike robots are not only unnerving, but are so because their appearance prompts attributions of mind. In particular, we suggest that machines become unnerving when people ascribe to them experience, rather than agency. Experiment 1 examined whether a machine’s humanlike appearance prompts both ascriptions of experience and feelings of unease. Experiment 2 tested whether a machine capable (...)
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  • On Political Theory and Large Language Models.Emma Rodman - 2024 - Political Theory 52 (4):548-580.
    Political theory as a discipline has long been skeptical of computational methods. In this paper, I argue that it is time for theory to make a perspectival shift on these methods. Specifically, we should consider integrating recently developed generative large language models like GPT-4 as tools to support our creative work as theorists. Ultimately, I suggest that political theorists should embrace this technology as a method of supporting our capacity for creativity—but that we should do so in a way that (...)
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  • Computational psychiatry.P. Read Montague, Raymond J. Dolan, Karl J. Friston & Peter Dayan - 2012 - Trends in Cognitive Sciences 16 (1):72-80.
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  • The Simulation Hypothesis, Social Knowledge, and a Meaningful Life.Grace Helton - 2024 - Oxford Studies in Philosophy of Mind 4:447-60.
    In Reality+: Virtual Worlds and the Problems of Philosophy, David Chalmers argues, among other things, that: if we are living in a full-scale simulation, we would still enjoy broad swathes of knowledge about non-psychological entities, such as atoms and shrubs; and, our lives might still be deeply meaningful. Chalmers views these claims as at least weakly connected: The former claim helps forestall a concern that if objects in the simulation are not genuine (and so not knowable), then life in the (...)
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  • (1 other version)Subsymbolic computation and the chinese room.David J. Chalmers - 1992 - In John Dinsmore (ed.), The Symbolic and Connectionist Paradigms: Closing the Gap. Lawrence Erlbaum. pp. 25--48.
    More than a decade ago, philosopher John Searle started a long-running controversy with his paper “Minds, Brains, and Programs” (Searle, 1980a), an attack on the ambitious claims of artificial intelligence (AI). With his now famous _Chinese Room_ argument, Searle claimed to show that despite the best efforts of AI researchers, a computer could never recreate such vital properties of human mentality as intentionality, subjectivity, and understanding. The AI research program is based on the underlying assumption that all important aspects of (...)
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  • Against digital ontology.Luciano Floridi - 2009 - Synthese 168 (1):151 - 178.
    The paper argues that digital ontology (the ultimate nature of reality is digital, and the universe is a computational system equivalent to a Turing Machine) should be carefully distinguished from informational ontology (the ultimate nature of reality is structural), in order to abandon the former and retain only the latter as a promising line of research. Digital vs. analogue is a Boolean dichotomy typical of our computational paradigm, but digital and analogue are only “modes of presentation” of Being (to paraphrase (...)
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  • Universal intelligence: A definition of machine intelligence.Shane Legg & Marcus Hutter - 2007 - Minds and Machines 17 (4):391-444.
    A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: we take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of intelligence for arbitrary machines. (...)
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  • Meaning in Life in AI Ethics—Some Trends and Perspectives.Sven Nyholm & Markus Rüther - 2023 - Philosophy and Technology 36 (2):1-24.
    In this paper, we discuss the relation between recent philosophical discussions about meaning in life (from authors like Susan Wolf, Thaddeus Metz, and others) and the ethics of artificial intelligence (AI). Our goal is twofold, namely, to argue that considering the axiological category of meaningfulness can enrich AI ethics, on the one hand, and to portray and evaluate the small, but growing literature that already exists on the relation between meaning in life and AI ethics, on the other hand. We (...)
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  • AI, Explainability and Public Reason: The Argument from the Limitations of the Human Mind.Jocelyn Maclure - 2021 - Minds and Machines 31 (3):421-438.
    Machine learning-based AI algorithms lack transparency. In this article, I offer an interpretation of AI’s explainability problem and highlight its ethical saliency. I try to make the case for the legal enforcement of a strong explainability requirement: human organizations which decide to automate decision-making should be legally obliged to demonstrate the capacity to explain and justify the algorithmic decisions that have an impact on the wellbeing, rights, and opportunities of those affected by the decisions. This legal duty can be derived (...)
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  • To Each Technology Its Own Ethics: The Problem of Ethical Proliferation.Henrik Skaug Sætra & John Danaher - 2022 - Philosophy and Technology 35 (4):1-26.
    Ethics plays a key role in the normative analysis of the impacts of technology. We know that computers in general and the processing of data, the use of artificial intelligence, and the combination of computers and/or artificial intelligence with robotics are all associated with ethically relevant implications for individuals, groups, and society. In this article, we argue that while all technologies are ethically relevant, there is no need to create a separate ‘ethics of X’ or ‘X ethics’ for each and (...)
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