What Can Artificial Intelligence Learn from Wittgenstein’s On Certainty?

Meta-philosophically speaking, the philosophy of artificial intelligence (AI) is intended not only to explore the theoretical possibility of building “thinking machines,” but also to reveal philosophical implications of specific AI approaches. Wittgenstein’s comments on the analytic/empirical dichot...

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Publicado en:Frontiers of Philosophy in China Vol. 9; no. 3; pp. 441 - 463
Autor principal: XU Yingjin
Formato: Artículo
Publicado: Higher Education Press Limited Company Sep2014
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Acceso en línea:Ver este registro en EBSCOhost
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        au: XU Yingjin
        affil: School of Philosophy, Fudan University, Shanghai 200433, China
      su:
        Artificial intelligence
        Bayesian analysis
        Connectionism
        Philosophy of mind
        Wittgenstein, Ludwig, 1889-1951
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        subj:
          Artificial intelligence
          Bayesian analysis
          Connectionism
          Philosophy of mind
          Wittgenstein, Ludwig, 1889-1951
      keyword:
        analytic/empirical dichotomy
        artificial intelligence
        axiomatic system
        Bayesian network
        connectionism
        context
      ab: Meta-philosophically speaking, the philosophy of artificial intelligence (AI) is intended not only to explore the theoretical possibility of building “thinking machines,” but also to reveal philosophical implications of specific AI approaches. Wittgenstein’s comments on the analytic/empirical dichotomy may offer inspirations for AI in the second sense. According to his “river metaphor” in On Certainty, the analytic/empirical boundary should be delimited in a way sensitive to specific contexts of practical reasoning. His proposal seems to suggest that any cognitive modeling project needs to render the system context-sensitive by avoiding representing large amounts of truisms in its cognitive processes, otherwise neither representational compactness nor computational efficiency can be achieved. In this article, different AI approaches (like the Common Sense Law of Inertia approach, the Bayesian approach and the connectionist approach) will be critically evaluated under the afore-mentioned Wittgensteinian criteria, followed by the author’s own constructive suggestion on what AI needs to try to do in the near future.
      pubtype: Academic Journal
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    language: English
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