Discursive Specifics of Human–Machine Interaction in Contemporary Digital Communication

Abstract

The proliferation of artificial intelligence and machine learning technologies has fundamentally transformed the landscape of digital communication, creating new paradigms of human-machine interaction (HMI) that demand systematic linguistic and discursive analysis. This research examines the specific discursive characteristics that emerge when humans engage with intelligent machines through various digital platforms, including chatbots, virtual assistants, and AI-powered communication systems. Through a mixed-methods approach combining computational linguistics analysis, discourse analysis, and qualitative content analysis of human-machine conversations across multiple platforms, this study identifies distinct linguistic patterns, communicative strategies, and pragmatic adaptations that characterize contemporary human-machine discourse. The findings reveal that human users exhibit specific discursive behaviors when interacting with machines, including simplified syntactic structures, increased use of imperative forms, reduced linguistic complexity, and adaptive politeness strategies. Furthermore, the study demonstrates that machine responses increasingly incorporate human-like discursive markers, creating a hybrid communicative space that challenges traditional boundaries between human and artificial discourse. The implications of these findings extend beyond computational linguistics to encompass broader questions of digital literacy, human-computer interaction design, and the evolving nature of communication in an increasingly automated world.