PRINCIPLES OF TERM FORMATION IN ARTIFICIAL INTELLIGENCE AND NEUROTECHNOLOGY

Abstract

This article examines the linguistic, structural, and semantic principles that guide the formation of terminology in the fields of artificial intelligence (AI) and neurotechnology. With the rapid advancement of machine learning, neural engineering, and cognitive computing, researchers must create precise and internationally standardized terms to ensure clarity and interdisciplinary communication. The study identifies key mechanisms of term formation—affixation, compounding, blending, and acronymization—and analyzes challenges associated with the adaptation of AI and neurotechnology terms in different languages. The findings highlight the importance of conceptual transparency, semantic precision, and cultural neutrality in the creation of new scientific terminology.