THE ROLE OF LINGUISTICS IN AI: UNDERSTANDING HUMAN LANGUAGE PROCESSING BY MACHINES

Abstract

The advent of artificial intelligence (AI) has greatly changed the processing, interpretation, and production of human language. In this study, the use of linguistics in AI is explored through investigating how phonology, morphology, syntax, semantics, pragmatics, and discourse influence natural language processing (NLP). Qualitative, descriptive, and literature-based research methodologies were employed using selected literature written between 2022 and 2025. The paper will be concerned with the evolution of NLP from rule-based to statistical models, followed by machine learning, deep learning, and large language models. The research has shown that linguistic principles play a vital role in creating the basis for grammatical parsing, semantic interpretation, context comprehension, and human-computer interaction. Some of the main applications of NLP include chatbots, healthcare and public health, software requirements engineering, business analytics, and automated communications. Nonetheless, issues such as linguistic ambiguity, cultural diversity, multilingualism, small data sets, algorithmic biases, and lack of transparency still hinder reliable functioning of AI language applications. The paper further draws the distinction between natural language understanding and natural language generation and demonstrates that fluency in language does not mean comprehension. Conclusively, the paper argues that AI-based language processing is contingent on collaboration among linguistic theories and computational approaches. The suggestions include developing multilingual data sets, developing explanations for NLP, ethics of evaluation, contextual processing, and inter-disciplinary research. This study adds value to knowledge of how linguistics may contribute to the development of better AI-based language technologies.