Human-Artificial intelligence interaction in the system of digital political communication: theoretical and methodological foundations and empirical approbation experience

Introduction. Digital transformation of political processes makes the problem of integrating artificial intelligence (AI) technologies into political communication practice highly relevant. Every year, there is an increasing penetration of algorithms and neural networks into political communication processes, which inevitably attracts the attention of the state and society. At the same time, the scientific understanding of specific formats of human–AI interaction in political discourse remains fragmented, and empirical studies documenting the results of practical AI tool approbation at the level of grassroots party organizations are extremely scarce. 
The purpose of the study is a theoretical and methodological analysis of human–AI interaction in the system of digital political communication, as well as the presentation and scientific interpretation of the results of empirical approbation of AI tool integration into political education practice at the level of primary party organizations. 
Materials and methods. The methodological basis of the research was an interdisciplinary approach based on the aggregation of political science, communicative, and technological concepts.  Institutional and communicative approaches, participant observation, and qualitative analysis of documents and expert data were applied. The empirical basis was an educational forum for secretaries of primary party cells using an AI stenographer, deepfake video demonstration, and practical laboratories. 
Results. The theoretical foundations for AI integration into digital political communication in  the context of transition to the fourth age of political communication have been systematized.  The experience of creating a collective document “Algorithmic Memo of a Primary Cell Secretary v1.0,” developed by forum participants jointly with AI, is presented. Qualitative changes in participants’ perception of the role of digital technologies and AI have been recorded. Risks associated with deepfake technologies have been demonstrated. 
Conclusions. The article proves that human–AI interaction in digital political communication is complementary in nature and can be effectively implemented through targeted improvement of political actors’ digital literacy. The results confirm the prospects of the symbiotic “human + algorithm” model for developing political communication at the local level. 

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