This paper develops an approach to human–machine interaction in complex socio-technical systems that focuses on the role of natural language as a means of influencing the operator’s cognitive state, rather than merely transmitting information. Building on earlier work on human factors and interaction in safety-critical environments, the study examines how the effectiveness of communication depends not only on message content, but also on its linguistic structure and its alignment with the operator’s current cognitive condition. A conceptual framework is presented that distinguishes multiple levels of linguistic organization in human–machine communication and relates them to their functional role in supporting operator performance. Particular attention is given to adaptive, context-sensitive communication strategies aimed at reducing cognitive overload, improving decision-making, and enhancing system safety. The paper contributes to the ongoing development of cognitively adaptive interaction systems and may be relevant for domains such as aviation, industrial environments, and other safety-critical applications. It also aligns with current research directions in human-aware and intelligent systems, providing a basis for further interdisciplinary work at the intersection of engineering psychology, psycholinguistics, and system design.
Petrenko et al. (2026) studied this question.