HYBRID COGNITIVE SYSTEM IN THE INTERACTION OF HUMAN, ARTIFICIAL INTELLIGENCE AND ENVIRONMENT

Abstract

The study provides a theoretical and methodological analysis of the prerequisites and mechanisms for the formation of a hybrid cognitive system resulting from the interaction of three interrelated agents: humans, artificial intelligence, and the socio-technical environment. It is
substantiated that the spread of generative artificial intelligence transforms its functional status from an instrumental means to an autonomous cognitive agent capable of influencing the structure, dynamics, and logic of cognitive processes. This transformation necessitates a revision of traditional approaches to understanding the nature of cognition and the mechanisms of organizing educational activities and actualizes the conceptualization of hybrid consciousness as an emergent phenomenon formed in conditions of biosociotechnical interaction. The theoretical basis of the study is the provisions of distributed learning theory and the biosociotechnical model, which interpret thinking as a dynamic, networked, and ecologically embedded system. In this context, modern digital technologies, in particular generative AI, are considered as cognitive extenders capable of expanding the boundaries of individual cognition by supporting analytical, simulative, and prognostic processes. Within the framework of tri-subject didactics, artificial intelligence is defined as a full-fledged subject of educational interaction that participates in the formation of individualized learning trajectories, adaptive content selection, and cognitive support for the learner. A special place in the structure of the hybrid cognitive system is given to the concept of digital twins, which are interpreted as dynamic models capable of reproducing and predicting the state and behavior of key educational agents. Three types of digital twins are distinguished—the student, the teacher, and the university infrastructure environment—which function as part of a single cognitive circuit. Their interaction ensures the cyclical nature of information and analytical processes, which include sensory data collection, cognitive-analytical processing, adaptive formation of pedagogical decisions, and reflective updating of cognitive models. The algorithmic structure of the cognitive cycle of a hybrid system is outlined, which includes sensory, analytical, integrative, and reflective modules that function as coordinated elements of a single socio-technical ecosystem. It is shown that in such a system, cognitive processes acquire a distributed, polycentric, and networked character, in which human intentionality, algorithmic information processing, and socio-technical contexts emerge as complementary determinants of the thinking process and learning activity.