Is the Artificial Intelligent? A Perspective on AI-based Natural Language Processors
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The issue of the relation between AI and human mind has been riddling the scientific world since ages. Being the mother lode of research, AI can be scrutinised from a plethora of perspectives. One of them is a linguistic perspective, which encompasses AI’s capability to understand language. Having been an innate and exclusive faculty of human mind, language is now manifested in a countless number of ways, transcending beyond the human-only production. There are applications that can not only understand what is meant by an utterance, but also engage in a quasi-humane discourse. The manner of their operating is perfectly organised and can be accounted for by incorporating linguistic theories. The main theory used in this article is Fluid Construction Grammar, which has been developed by Luc Steels. It is concerned with parsing and segmentation of any utterance – two processes that are pivotal in AI’s understanding and production of language. This theory, in addition with five main facets of languages (phonological, morphological, semantic, syntactic and pragmatic) provides a valuable insight into the discrepancies between natural and artificial perception of language. Though there are similarities between them, the article shall conclude with what makes two adjacent capabilities different. The aim of this paper is to display the mechanisms of AI natural language processors with the aid of contemporary linguistic theories, and present possible issues which may ensue from using artificial language-recognising systems.
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