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Society of mind

Artificial Intelligence 48 (3):371-396 (1991)

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  1. Précis of Origins of the modern mind: Three stages in the evolution of culture and cognition.Merlin Donald - 1993 - Behavioral and Brain Sciences 16 (4):737-748.
    This bold and brilliant book asks the ultimate question of the life sciences: How did the human mind acquire its incomparable power? In seeking the answer, Merlin Donald traces the evolution of human culture and cognition from primitive apes to the era of artificial intelligence, and presents an original theory of how the human mind evolved from its presymbolic form. In the emergence of modern human culture, Donald proposes, there were three radical transitions. During the first, our bipedal but still (...)
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  • Belief as Question‐Sensitive.Seth Yalcin - 2018 - Philosophy and Phenomenological Research 97 (1):23-47.
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  • The cultural ecosystem of human cognition.Edwin Hutchins - 2014 - Philosophical Psychology 27 (1):1-16.
    Everybody knows that humans are cultural animals. Although this fact is universally acknowledged, many opportunities to exploit it are overlooked. In this article, I propose shifting our attention from local examples of extended mind to the cultural-cognitive ecosystems within which human cognition is embedded. I conclude by offering a set of conjectures about the features of cultural-cognitive ecosystems.
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  • Precis of the emperor's new mind.Roger Penrose - 1990 - Behavioral and Brain Sciences 13 (4):643-705.
    The emperor's new mind (hereafter Emperor) is an attempt to put forward a scientific alternative to the viewpoint of according to which mental activity is merely the acting out of some algorithmic procedure. John Searle and other thinkers have likewise argued that mere calculation does not, of itself, evoke conscious mental attributes, such as understanding or intentionality, but they are still prepared to accept the action the brain, like that of any other physical object, could in principle be simulated by (...)
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  • Selecting for the con in consciousness.Deborah Hodgkin & Alasdair I. Houston - 1990 - Behavioral and Brain Sciences 13 (4):668-669.
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  • Computability, consciousness, and algorithms.Robert Wilensky - 1990 - Behavioral and Brain Sciences 13 (4):690-691.
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  • The modern mind: Its missing parts?R. I. M. Dunbar - 1993 - Behavioral and Brain Sciences 16 (4):758-759.
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  • The Future of Human Evolution.Nick Bostrom - unknown
    Evolutionary development is sometimes thought of as exhibiting an inexorable trend towards higher, more complex, and normatively worthwhile forms of life. This paper explores some dystopian scenarios where freewheeling evolutionary developments, while continuing to produce complex and intelligent forms of organization, lead to the gradual elimination of all forms of being that we care about. We then consider how such catastrophic outcomes could be avoided and argue that under certain conditions the only possible remedy would be a globally coordinated policy (...)
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  • Is mathematical insight algorithmic?Martin Davis - 1990 - Behavioral and Brain Sciences 13 (4):659-660.
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  • Evolution needs a modern theory of the mind.James H. Fetzer - 1993 - Behavioral and Brain Sciences 16 (4):759-760.
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  • False Vacuum: Early Universe Cosmology and the Development of Inflation.Chris Smeenk - 2005 - In Eisenstaedt Jean & Knox A. J. (eds.), The Universe of General Relativity. Birkhauser. pp. 223-257.
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  • Natural Language Processing With Modular Pdp Networks and Distributed Lexicon.Risto Miikkulainen & Michael G. Dyer - 1991 - Cognitive Science 15 (3):343-399.
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  • A framework for thinking about distributed cognition.Pierre Poirier & Guillaume Chicoisne - 2006 - Pragmatics and Cognition 14 (2):215-234.
    As is often the case when scientific or engineering fields emerge, new concepts are forged or old ones are adapted. When this happens, various arguments rage over what ultimately turns out to be conceptual misunderstandings. At that critical time, there is a need for an explicit reflection on the meaning of the concepts that define the field. In this position paper, we aim to provide a reasoned framework in which to think about various issues in the field of distributed cognition. (...)
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  • On “seeing” the truth of the Gödel sentence.George Boolos - 1990 - Behavioral and Brain Sciences 13 (4):655-656.
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  • Do Political Convictions Infect Every Fibre of Our Being?Joseph Ulatowski & David Lumsden - 2024 - Social Epistemology 38 (5):560-576.
    1. The current political scene in many countries is populated by polarised groups with sharply contrasting loyalties and beliefs implying that there are fundamental schisms between opposing groups....
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  • Big Historical Foundations for Deep Future Speculations: Cosmic Evolution, Atechnogenesis, and Technocultural Civilization.Cadell Last - 2017 - Foundations of Science 22 (1):39-124.
    Big historians are attempting to construct a general holistic narrative of human origins enabling an approach to studying the emergence of complexity, the relation between evolutionary processes, and the modern context of human experience and actions. In this paper I attempt to explore the past and future of cosmic evolution within a big historical foundation characterized by physical, biological, and cultural eras of change. From this analysis I offer a model of the human future that includes an addition and/or reinterpretation (...)
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  • From the History of Science to the History of Knowledge - and Back.Jürgen Renn - 2015 - Centaurus 57 (1):37-53.
    The history of science can be better understood against the background of a history of knowledge comprising not only theoretical but also intuitive and practical knowledge. This widening of scope necessitates a more concise definition of the concept of knowledge, relating its cognitive to its material and social dimensions. The history of knowledge comprises the history of institutions in which knowledge is produced and transmitted. This is an essential but hitherto neglected aspect of cultural evolution. Taking this aspect into account (...)
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  • Computing the Human.N. Katherine Hayles - 2005 - Theory, Culture and Society 22 (1):131-151.
    Researchers in artificial intelligence and robotics often include a timeline stretching into the future in which they predict the convergence between human and artificial intelligence. Ray Kurzweil, for example, predicts that in a mere 100 years humans and intelligent machines will become indistinguishable from one another, both ceasing to have permanent corporeal forms. This article argues that the one thing we can know for sure about the future is that when it arrives, it will be different from what we imagined. (...)
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  • Cognitive architectures for artificial intelligence ethics.Steve J. Bickley & Benno Torgler - 2023 - AI and Society 38 (2):501-519.
    As artificial intelligence (AI) thrives and propagates through modern life, a key question to ask is how to include humans in future AI? Despite human involvement at every stage of the production process from conception and design through to implementation, modern AI is still often criticized for its “black box” characteristics. Sometimes, we do not know what really goes on inside or how and why certain conclusions are met. Future AI will face many dilemmas and ethical issues unforeseen by their (...)
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  • The nonalgorithmic mind.Roger Penrose - 1990 - Behavioral and Brain Sciences 13 (4):692-705.
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  • (1 other version)Where am I? Who am I? The Relation Between Spatial Cognition, Social Cognition and Individual Differences in the Built Environment.Michael J. Proulx, Orlin S. Todorov, Amanda Taylor Aiken & Alexandra A. de Sousa - 2016 - Frontiers in Psychology 7.
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  • Computing the thinkable.David J. Chalmers - 1990 - Behavioral and Brain Sciences 13 (4):658-659.
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  • “Pop science” versus understanding the emergence of the modern mind.C. Loring Brace - 1993 - Behavioral and Brain Sciences 16 (4):750-751.
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  • Virtualist representation.Robert W. Clowes & Ron Chrisley - 2012 - International Journal of Machine Consciousness 4 (2):503-522.
    This paper seeks to identify, clarify, and perhaps rehabilitate the virtual reality metaphor as applied to the goal of understanding consciousness. Some proponents of the metaphor apply it in a way that implies a representational view of experience of a particular, extreme form that is indirect, internal and inactive (what we call “presentational virtualism”). In opposition to this is an application of the metaphor that eschews representation, instead preferring to view experience as direct, external and enactive (“enactive virtualism”). This paper (...)
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  • Putting cognitive carts before linguistic horses.Derek Bickerton - 1993 - Behavioral and Brain Sciences 16 (4):749-750.
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  • Lucas revived? An undefended flank.Jeremy Butterfield - 1990 - Behavioral and Brain Sciences 13 (4):658-658.
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  • Mythos and logos.John Halverson - 1993 - Behavioral and Brain Sciences 16 (4):762-762.
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  • Penrose's Platonism.James Higginbotham - 1990 - Behavioral and Brain Sciences 13 (4):667-668.
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  • Parallelism and patterns of thought.R. W. Kentridge - 1990 - Behavioral and Brain Sciences 13 (4):670-671.
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  • Memory, text and the Greek Revolution.Jocelyn Penny Small - 1993 - Behavioral and Brain Sciences 16 (4):769-770.
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  • Situated Language Understanding as Filtering Perceived Affordances.Peter Gorniak & Deb Roy - 2007 - Cognitive Science 31 (2):197-231.
    We introduce a computational theory of situated language understanding in which the meaning of words and utterances depends on the physical environment and the goals and plans of communication partners. According to the theory, concepts that ground linguistic meaning are neither internal nor external to language users, but instead span the objective‐subjective boundary. To model the possible interactions between subject and object, the theory relies on the notion of perceived affordances: structured units of interaction that can be used for prediction (...)
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  • How functionalist and process approaches to behavior can explain trait covariation.Dustin Wood, Molly Hensler Gardner & P. D. Harms - 2015 - Psychological Review 122 (1):84-111.
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  • Towards Scalable Governance: Sensemaking and Cooperation in the Age of Social Media.Iyad Rahwan - 2017 - Philosophy and Technology 30 (2):161-178.
    Cybernetics, or self-governance of animal and machine, requires the ability to sense the world and to act on it in an appropriate manner. Likewise, self-governance of a human society requires groups of people to collectively sense and act on their environment. I argue that the evolution of political systems is characterized by a series of innovations that attempt to solve two ‘scalability’ problems: scaling up a group’s ability to make sense of an increasingly complex world, and to cooperate in increasingly (...)
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  • Recursive Ontology: A Systemic Theory of Reality.Valerio Velardo - 2016 - Axiomathes 26 (1):89-114.
    The article introduces recursive ontology, a general ontology which aims to describe how being is organized and what are the processes that drive it. In order to answer those questions, I use a multidisciplinary approach that combines the theory of levels, philosophy and systems theory. The main claim of recursive ontology is that being is the product of a single recursive process of generation that builds up all of reality in a hierarchical fashion from fundamental physical particles to human societies. (...)
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  • Language, thought and consciousness in the modern mind.Evan Thompson - 1993 - Behavioral and Brain Sciences 16 (4):770-771.
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  • The discomforts of dualism.Bruce MacLennan - 1990 - Behavioral and Brain Sciences 13 (4):673-674.
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  • Computation and consciousness.Drew McDermott - 1990 - Behavioral and Brain Sciences 13 (4):676-678.
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  • From AI to cybernetics.Keizo Sato - 1991 - AI and Society 5 (2):155-161.
    Well-known critics of AI such as Hubert Dreyfus and Michael Polanyi tend to confuse cybernetics with AI. Such a confusion is quite misleading and should not be overlooked. In the first place, cybernetics is not vulnerable to criticism of AI as cognitivistic and behaviouristic. In the second place, AI researchers are recommended to consider the cybernetics approach as a way of overcoming the limitations of cognitivism and behaviourism.
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  • From cooperative computation to man/machine symbiosis.Michael A. Arbib - 1993 - Behavioral and Brain Sciences 16 (4):748-749.
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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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  • Mimetic culture and modern sports: A synthesis.Bruce Bridgeman & Margarita Azmitia - 1993 - Behavioral and Brain Sciences 16 (4):751-752.
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  • Archaeology and the cognitive sciences in the study of human evolution.Philip G. Chase - 1993 - Behavioral and Brain Sciences 16 (4):752-753.
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  • Inner Speech Generation in a Video Game Non-Player Character: From Explanation to Self?Raúl Arrabales - 2012 - International Journal of Machine Consciousness 4 (2):367-381.
    The use of human language is a hallmark of human consciousness, even when it is not used publicly. Inner speech is the way humans consciously communicate with themselves and arguably a key factor contributing to the formation of more self-aware selves. From the perspective of cognitive science and artificial cognitive architectures, inner speech can be also seen as a meta-management system that modulates some cognitive processes of the subject. In this paper, we describe a preliminary version of a computational model (...)
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  • A natural history of the mind: A guide for cognitive science.Thomas L. Clarke - 1993 - Behavioral and Brain Sciences 16 (4):754-755.
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  • Symbolic invention: The missing (computational) link?Andy Clark - 1993 - Behavioral and Brain Sciences 16 (4):753-754.
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  • The place of cognition in human evolution.Alan Costall - 1993 - Behavioral and Brain Sciences 16 (4):755-755.
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  • Human evolution: Emergence of the group-self.Vilmos Csányi - 1993 - Behavioral and Brain Sciences 16 (4):755-756.
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  • Ethological foxes and cognitive hedgehogs.Jeffrey Cynx & Stephen J. Clark - 1993 - Behavioral and Brain Sciences 16 (4):756-757.
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  • Betting your life on an algorithm.Daniel C. Dennett - 1990 - Behavioral and Brain Sciences 13 (4):660-661.
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