SEMIOTIC CODES IN ARTIFICIAL INTELLIGENCE DISCOURSE AND THE PRAGMATIC MODEL OF HUMAN-TECHNOLOGY COMMUNICATION

Abstract

This article analyzes semiotic codes in artificial intelligence discourse and proposes a pragmatic model of human-technology communication. In contemporary digital culture, artificial intelligence is no longer perceived only as a technical instrument; it functions as a communicative participant that produces, transforms and interprets verbal, visual and symbolic signs. The study focuses on the semiotic nature of AI-generated discourse, including prompts, algorithmic responses, interface symbols, dialogic structures and user expectations. The purpose of the article is to identify the main types of semiotic codes in AI discourse and explain how they influence pragmatic meaning-making between humans and technological systems. The research uses descriptive, semiotic, discourse-analytical and functional-pragmatic methods. The results show that AI discourse is formed through the interaction of linguistic code, algorithmic code, interface code, visual-symbolic code and pragmatic-contextual code. These codes shape the user's communicative intention, trust, interpretation and response behavior. The study concludes that human-technology communication should be analyzed as a hybrid pragmatic process in which meaning is created not only by language, but also by technological mediation.