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Ascribing mental qualities to machines

In Martin Ringle (ed.), Philosophical Perspectives in Artificial Intelligence. Humanities Press (1979)

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  1. Philosophy and theory of artificial intelligence 2017.Vincent C. Müller (ed.) - 2017 - Berlin: Springer.
    This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; (...)
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  • Searle's and Penrose's Noncomputational Frameworks for Naturalizing the Mind.Napoleon M. Mabaquiao - unknown
    John Searle and Roger Penrose are two staunch critics of computationalism who nonetheIess believe that with the right framework the mind can be naturalized. while they may be successful in showing the shortcomings of computationalism, I argue that their alternative noncomputational frameworks equally fail to carry out the project to naturalize the mind. The main reason is their failure to resolve some fundamental incompatibilities between mind and science. Searle tries to resolve the incompatibility between the subjectivity of consciousness and the (...)
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  • Philosophy of Mind: Classical and Contemporary Readings.David John Chalmers (ed.) - 2002 - New York: Oxford University Press USA.
    What is the mind? Is consciousness a process in the brain? How do our minds represent the world? Philosophy of Mind: Classical and Contemporary Readings is a grand tour of writings on these and other perplexing questions about the nature of the mind. The most comprehensive collection of its kind, the book includes sixty-three selections that range from the classical contributions of Descartes to the leading edge of contemporary debates. Extensive sections cover foundational issues, the nature of consciousness, and the (...)
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  • Where is the material of the emperor's mind?David L. Gilden & Joseph S. Lappin - 1990 - Behavioral and Brain Sciences 13 (4):665-666.
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  • Time-delays in conscious processes.Benjamin Libet - 1990 - Behavioral and Brain Sciences 13 (4):672-672.
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  • The powers of machines and minds.Chris Mortensen - 1990 - Behavioral and Brain Sciences 13 (4):678-679.
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  • Steadfast intentions.Keith K. Niall - 1990 - Behavioral and Brain Sciences 13 (4):679-680.
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  • The nonalgorithmic mind.Roger Penrose - 1990 - Behavioral and Brain Sciences 13 (4):692-705.
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  • Systematic, unconscious thought is the place to anchor quantum mechanics in the mind.Thomas Roeper - 1990 - Behavioral and Brain Sciences 13 (4):681-682.
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  • Seeing truth or just seeming true?Adina Roskies - 1990 - Behavioral and Brain Sciences 13 (4):682-683.
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  • The pretender's new clothes.Tim Smithers - 1990 - Behavioral and Brain Sciences 13 (4):683-684.
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  • And then a miracle happens….Keith E. Stanovich - 1990 - Behavioral and Brain Sciences 13 (4):684-685.
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  • Exactly which emperor is Penrose talking about?John K. Tsotsos - 1990 - Behavioral and Brain Sciences 13 (4):686-687.
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  • Penrose's grand unified mystery.David Waltz & James Pustejovsky - 1990 - Behavioral and Brain Sciences 13 (4):688-690.
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  • Minds beyond brains and algorithms.Jan M. Zytkow - 1990 - Behavioral and Brain Sciences 13 (4):691-692.
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  • Computing the thinkable.David J. Chalmers - 1990 - Behavioral and Brain Sciences 13 (4):658-659.
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  • Physics of brain-mind interaction.John C. Eccles - 1990 - Behavioral and Brain Sciences 13 (4):662-663.
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  • Mental phenomena and behavior.B. Libet - 1980 - Behavioral and Brain Sciences 3 (3):434-434.
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  • Beliefs, machines, and theories.John McCarthy - 1980 - Behavioral and Brain Sciences 3 (3):435-435.
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  • A dualist-interactionist perspective.John C. Eccles - 1980 - Behavioral and Brain Sciences 3 (3):430-431.
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  • Searle on what only brains can do.J. A. Fodor - 1980 - Behavioral and Brain Sciences 3 (3):431-432.
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  • Programs, causal powers, and intentionality.John Haugeland - 1980 - Behavioral and Brain Sciences 3 (3):432-433.
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  • Understanding Searle.Roger C. Schank - 1980 - Behavioral and Brain Sciences 3 (3):446-447.
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  • How to turn an information processor into an understander.Aaron Sloman & Monica Croucher - 1980 - Behavioral and Brain Sciences 3 (3):447-448.
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  • Decentralized minds.Marvin Minsky - 1980 - Behavioral and Brain Sciences 3 (3):439-440.
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  • Science, philosophy, and interpretation.Daniel C. Dennett - 1988 - Behavioral and Brain Sciences 11 (3):535.
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  • Intentional system theory and experimental psychology.Michael H. Van Kleeck - 1988 - Behavioral and Brain Sciences 11 (3):533.
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  • What is the intentional stance?Gilbert Harman - 1988 - Behavioral and Brain Sciences 11 (3):515.
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  • The intentional stance and the knowledge level.Allen Newell - 1988 - Behavioral and Brain Sciences 11 (3):520.
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  • Another “Just So” story: How the leopardguarders spot.Dorothy Cheney & Robert Seyfarth - 1988 - Behavioral and Brain Sciences 11 (3):506.
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  • The role of emotions in inter-action selection.Jekaterina Novikova, Leon Watts & Joanna J. Bryson - 2014 - Interaction Studies 15 (2):216-223.
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  • A logic of situated resource-bounded agents.Natasha Alechina & Brian Logan - 2009 - Journal of Logic, Language and Information 18 (1):79-95.
    We propose a framework for modelling situated resource-bounded agents. The framework is based on an objective ascription of intentional modalities and can be easily tailored to the system we want to model and the properties we wish to specify. As an elaboration of the framework, we introduce a logic, OBA, for describing the observations, beliefs, goals and actions of simple agents, and show that OBA is complete, decidable and has an efficient model checking procedure, allowing properties of agents specified in (...)
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  • ML systems: A proof theory for contexts. [REVIEW]Luciano Serafini & Fausto Giunchiglia - 2002 - Journal of Logic, Language and Information 11 (4):471-518.
    In the last decade the concept of context has been extensivelyexploited in many research areas, e.g., distributed artificialintelligence, multi agent systems, distributed databases, informationintegration, cognitive science, and epistemology. Three alternative approaches to the formalization of the notion ofcontext have been proposed: Giunchiglia and Serafini's Multi LanguageSystems (ML systems), McCarthy's modal logics of contexts, andGabbay's Labelled Deductive Systems.Previous papers have argued in favor of ML systems with respect to theother approaches. Our aim in this paper is to support these arguments froma (...)
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  • "Every man in his notions" or alchemists' discussion on artificial intelligence.Mariusz Flasiński - 1997 - Foundations of Science 2 (1):107-121.
    A survey of the main approaches in a mind study -oriented part of Artificial Intelligence is made focusing on controversial issues and extreme hypotheses. Various meanings of terms: "intelligence" and "artificial intelligence" are discussed. Limitations for constructing intelligent systems resulting from the lack of formalized models of cognitive activity are shown. The approaches surveyed are then recapitulated in the light of these limitations.
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  • Artificial intelligence and consciousness.Drew McDermott - 2007 - In Morris Moscovitch, Philip Zelazo & Evan Thompson (eds.), Cambridge Handbook of Consciousness. New York: Cambridge University Press. pp. 117--150.
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  • 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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  • The indeterminacy of color vision.Richard Montgomery - 1996 - Synthese 106 (2):167-203.
    A critical survey of recent work on the ontological status of colors supports the conclusion that, while some accounts of color can plausibly be dismissed, no single account can yet be endorsed. Among the remaining options are certain forms of color realism according which familiar colors are instantiated by objects in our extra-cranial visual environment. Also still an option is color anti-realism, the view that familiar colors are, at best, biologically adaptive fictions, instantiated nowhere.I argue that there is simply no (...)
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  • Why paramecia don't have mental representations.Jerry A. Fodor - 1986 - Midwest Studies in Philosophy 10 (1):3-23.
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  • Precis of the intentional stance.Daniel C. Dennett - 1988 - Behavioral and Brain Sciences 11 (3):495-505.
    The intentional stance is the strategy of prediction and explanation that attributes beliefs, desires, and other states to systems and predicts future behavior from what it would be rational for an agent to do, given those beliefs and desires. Any system whose performance can be thus predicted and explained is an intentional system, whatever its innards. The strategy of treating parts of the world as intentional systems is the foundation of but is also exploited in artificial intelligence and cognitive science (...)
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  • Beliefs and sentences in the head.Ken Warmbrod - 1989 - Synthese 79 (2):201-30.
    It is argued thatde dicto andde re beliefs are attitudes towards syntactically structured entities (sentences) in the head. In order to identify the content of ade dicto orde re belief, we must be able to match causal relations of belief states to natural language inferences. Such match-ups provide sufficient empirical justification for regarding those causal relations as syntactic transformations, that is, inferences. But only syntactically structured entities are capable of enjoying such inferential relations. Hence,de dicto andde re beliefs must be (...)
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  • Are Language Models More Like Libraries or Like Librarians? Bibliotechnism, the Novel Reference Problem, and the Attitudes of LLMs.Harvey Lederman & Kyle Mahowald - forthcoming - Transactions of the Association for Computational Linguistics.
    Are LLMs cultural technologies like photocopiers or printing presses, which transmit information but cannot create new content? A challenge for this idea, which we call bibliotechnism, is that LLMs generate novel text. We begin with a defense of bibliotechnism, showing how even novel text may inherit its meaning from original human-generated text. We then argue that bibliotechnism faces an independent challenge from examples in which LLMs generate novel reference, using new names to refer to new entities. Such examples could be (...)
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  • Pictures, Plants, and Propositions.Alex Morgan - 2019 - Minds and Machines 29 (2):309-329.
    Philosophers have traditionally held that propositions mark the domain of rational thought and inference. Many philosophers have held that only conceptually sophisticated creatures like us could have propositional attitudes. But in recent decades, philosophers have adopted increasingly liberal views of propositional attitudes that encompass the mental states of various non-human animals. These views now sit alongside more traditional views within the philosophical mainstream. In this paper I argue that liberalized views of propositional attitudes are so liberal that they encompass states (...)
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  • Pictures, Plants, and Propositions.Alex Morgan - 2019 - Minds and Machines 29 (2):309-329.
    Philosophers have traditionally held that propositions mark the domain of rational thought and inference. Many philosophers have held that only conceptually sophisticated creatures like us could have propositional attitudes. But in recent decades, philosophers have adopted increasingly liberal views of propositional attitudes that encompass the mental states of various non-human animals. These views now sit alongside more traditional views within the philosophical mainstream. In this paper I argue that liberalized views of propositional attitudes are so liberal that they encompass states (...)
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  • The role of emotions in inter-action selection.Jekaterina Novikova, Leon Watts & Joanna J. Bryson - 2014 - Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies / Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies 15 (2):216-223.
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  • Towards a conceptual and methodological framework for determining robot believability.Robert Rose, Matthias Scheutz & Paul Schermerhorn - 2010 - Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies / Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies 11 (2):314-335.
    Making interactions between humans and artificial agents successful is a major goal of interaction design. The aim of this paper is to provide researchers conducting interaction studies a new framework for the evaluation of robot believability. By critically examining the ordinary sense of believability, we first argue that currently available notions of it are underspecified for rigorous application in an experimental setting. We then define four concepts that capture different senses of believability, each of which connects directly to an empirical (...)
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  • Gödel redux.Alexis Manaster-Ramer, Walter J. Savitch & Wlodek Zadrozny - 1990 - Behavioral and Brain Sciences 13 (4):675-676.
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  • The thinker dreams of being an emperor.M. M. Taylor - 1990 - Behavioral and Brain Sciences 13 (4):685-686.
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  • Algorithms and physical laws.Franklin Boyle - 1990 - Behavioral and Brain Sciences 13 (4):656-657.
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  • AI and the Turing model of computation.Thomas M. Breuel - 1990 - Behavioral and Brain Sciences 13 (4):657-657.
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  • Is mathematical insight algorithmic?Martin Davis - 1990 - Behavioral and Brain Sciences 13 (4):659-660.
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