SEMANTIC FIELDS OF ARTIFICIAL INTELLIGENCE TERMINOLOGY IN MODERN ENGLISH

Abstract

This study investigates the semantic organization and interpretation of terminology related to Artificial Intelligence (AI) in modern English, focusing on how these terms form distinct semantic fields. The rapid advancement of AI technology has not only introduced a vast array of new lexical items but also repurposed existing words, leading to the creation of novel conceptual domains within the language. Using a qualitative descriptive methodology, the research analyzes a corpus of AI-related terms drawn from academic texts, technical documentation, and popular media to identify patterns of meaning and grouping. The findings reveal four predominant semantic fields in AI terminology: cognitive, biological, technical, and ethical. The cognitive field includes terms that describe mental processes and functions, while the biological field features metaphors derived from living systems, such as neural networks. The technical field encompasses terms related to hardware, software, and computational methods, and the ethical field reflects concerns about the societal impact and moral considerations of AI technologies. Furthermore, this study highlights how metaphorical language plays a crucial role in expanding and shaping AI vocabulary, enabling users to conceptualize complex technological ideas through familiar human and natural phenomena. The research underscores the importance of semantic awareness for both educators and communicators, advocating for teaching AI terminology not only as isolated technical terms but as interconnected concepts influenced by metaphor and context. This approach can facilitate better understanding, clearer communication, and critical engagement with AI in diverse discourse communities.