dc.creatorGonzález, Rodrigo
dc.date.accessioned2019-10-30T15:33:16Z
dc.date.available2019-10-30T15:33:16Z
dc.date.created2019-10-30T15:33:16Z
dc.date.issued2020
dc.identifier14355655
dc.identifier09515666
dc.identifier10.1007/s00146-019-00906-x
dc.identifierhttps://repositorio.uchile.cl/handle/2250/172490
dc.description.abstractThis paper examines an insoluble Cartesian problem for classical AI, namely, how linguistic understanding involves knowledge and awareness of u’s meaning, a cognitive process that is irreducible to algorithms. As analyzed, Descartes’ view about reason and intelligence has paradoxically encouraged certain classical AI researchers to suppose that linguistic understanding suffices for machine intelligence. Several advocates of the Turing Test, for example, assume that linguistic understanding only comprises computational processes which can be recursively decomposed into algorithmic mechanisms. Against this background, in the first section, I explain Descartes’ view about language and mind. To show that Turing bites the bullet with his imitation game and in the second section I analyze this method to assess intelligence. Then, in the third section, I elaborate on Schank and Abelsons’ Script Applier Mechanism (SAM, hereby), which supposedly casts doubt on Descartes’ denial that machines can think. Finally, in the fourth section, I explore a challenge that any algorithmic decomposition of linguistic understanding faces. This challenge, I argue, is the core of the Cartesian problem: knowledge and awareness of meaning require a first-person viewpoint which is irreducible to the decomposition of algorithmic mechanisms.
dc.languageen
dc.publisherSpringer London
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
dc.sourceAI and Society
dc.subjectAI
dc.subjectAwareness
dc.subjectDescartes
dc.subjectMeaning
dc.subjectTuring test
dc.titleClassical AI linguistic understanding and the insoluble Cartesian problem
dc.typeArtículo de revista


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