Abstract
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.
Highlights
Being a vital and valuable factor in our lives, technology has grown to aid people in most everyday activities
Enclosed within a miniscule case of the Central Processing Unit (CPU), it can carry out millions of operations per second replacing humans and relieving them from tedious and, at times, tiresome efforst
This article focuses on the Natural Language Processors (NLP) – applications found in phones, computers or digital readers, which are to emulate the process of conversation and all its facets
Summary
The main theory used in this article is Fluid Construction Grammar, which has been developed by Luc Steels. It is concerned with parsing and the segmentation of any utterance – two processes that are pivotal in AI’s understanding and production of language. This theory, in addition to five main facets of languages (phonological, morphological, semantic, syntactic and pragmatic), provides valuable insight into discrepancies between the natural and artificial perceptions of language. 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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