Author:
Olga T. Ergunova
Peter the Great St. Petersburg Polytechnic University (St. Petersburg, Russia)
Andrey G. Somov
Peter the Great St. Petersburg Polytechnic University (St. Petersburg, Russia)
Abstract:
The article analyzes the role of neural network technologies in the transformation of socio-labor relations in Russian megacities in the context of the transition to noonomy. The authors identify eight key factors in the implementation of AI-based solutions, including personalized employment analysis, conflict prediction, adaptive learning, and digital inclusion. The relevance of the topic is emphasized in light of the labor shortage — which by 2024 is estimated at 4.8 million people, with a shortfall of up to 700 thousand IT specialists. It is noted that fewer than 5% of Russian companies use AI in HR processes, despite its potential to enhance the resilience, productivity, and inclusiveness of labor systems. Promising areas for development are explored, such as labor behavior neuroanalysis, labor metaverses, generative AI, and digital assistants. The authors conclude that the active implementation of neural network solutions is a necessary tool for the sustainable management of labor resources in megacities.
Keywords: neural network technologies, socio-labor relations, noonomy, megacity, digital inclusion, AI in personnel management
For citation:Ergunova O. T., Somov A. G. (2025). Neural Network Technologies in the Management of Socio-Labor Relations in Megacities in the Context of Noonomy. Noonomy and Noosociety. Almanac of Scientific Works of the S. Y. Witte INID, Vol. 4, No. 2, pp. 102–113. DOI: 10.37930/2782-
6465-2025-4-2-102-113