RuEn

Journal section "Science, technology and innovation studies"

A System for Classification of Technologies in the Field of Artificial Intelligence for Personnel Forecasting

Gurtov V.A., Averyanov A.O., Korzun D.Z., Smirnov N.V.

Volume 15, Issue 3, 2022

Gurtov V.A., Averyanov A.O., Korzun D.Zh., Smirnov N.V. (2022). A system for classification of technologies in the field of artificial intelligence for personnel forecasting. Economic and Social Changes: Facts, Trends, Forecast, 15(3), 113–133. DOI: 10.15838/esc.2022.3.81.6

DOI: 10.15838/esc.2022.3.81.6

Abstract   |   Authors   |   References
The development of the Russian economy, including through large-scale introduction of digital technology and artificial intelligence technology, requires appropriate resources. Qualified personnel is one of them. The need for trained specialists poses important questions to state institutions – whom to train and in what quantity; this, in turn, demands a detailed elaboration on the issue of staffing requirement. The article presents the results of development of a classification system of artificial intelligence technology for solving personnel forecasting problems. Theoretical significance of the research findings consists in the creation of a classification system that structures existing knowledge about technologies in the field of artificial intelligence and has the potential to gain new knowledge. The novelty of the approach to the classification of artificial intelligence technologies consists in using a three-component structure of technologies “methods – tools – application areas” and adjusting the classification to suit the tasks of forecasting the demand of the economy for personnel with competencies in the field of artificial intelligence. The classification is based on the results of analysis of scientific publications on AI (journals of the first quartile Q1 and conferences of the A/A* level). “The Systematic Literature Review” method was used for their research. All thematic publications indexed in Scopus were also analyzed. Practical significance of the results is revealed in relation to the tasks of personnel forecasting in the field of artificial intelligence. The developed classification makes it possible to structure the personnel need at different levels of refinement of artificial intelligence technologies. Another direction in the development of the proposed classification is to compare competencies (knowledge, skills and practical experience) in popular groups of professions with components of artificial intelligence technologies (methods, tools, applications) to design educational programs in the relevant field. The proposed classification has the potential for development: one of the ways is an expert assessment of priority areas for the development of artificial intelligence. The article presents an overview of the results of application of the classification

Keywords

forecasting, classification, technologies, digital economy, artificial intelligence, staffing requirement, frontiers

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