Content area

Abstract

Abstract—

The article examines the directions for improving the information and analytical infrastructure in the field of artificial intelligence (AI) and the development of its individual elements. It is proposed to form a comprehensive data collection system capable of providing government bodies, business and society with high-quality information about the current and forecast conditions of the object. The need to institutionalize the concept of “artificial intelligence” for the purposes of government monitoring is proven. An analysis of the main parameters of the state of the artificial intelligence market, the most relevant from the point of view of modern analysts, is given, on the basis of which it is concluded that the global AI market has become one of the important factors in GDP growth. Analysis of the AI segment in Russia shows that in the coming years it can reach statistically significant volumes, and therefore it is necessary to actively include and expand data on AI in the national information and analytical infrastructure, in particular in the state statistical observation system. Recommendations are given regarding the methodological elaboration of the features and specifics of the development of the information infrastructure of AI. The most significant challenges facing this area are discussed: formalization of the definition of AI, development of a unified measurement and monitoring infrastructure, problems of reflection in statistical accounting, adaptation of existing statistical observations in order to obtain up-to-date data on its current and forecast state. It is proven that the measurement infrastructure and monitoring system for AI should not only reflect its contribution to achieving strategic goals, but also be specified in accordance with the current institutional framework for implementing the innovation economy model as a whole.

Details

10000008
Title
Methodological Problems of Information DevelopmentAnalytical Infrastructure for Assessing the State and Forecasting the Sphere of Artificial Intelligence
Author
Matraeva, L. V. 1 ; Vasiutina, E. S. 1 ; Bashina, O. E. 2 

 MIREA Russian Technological University, Moscow, Russia (GRID:grid.466477.0) (ISNI:0000 0000 9620 717X) 
 Moscow Humanitarian University, Moscow, Russia (GRID:grid.466477.0) 
Publication title
Volume
35
Issue
1
Pages
80-90
Publication year
2024
Publication date
Feb 2024
Publisher
Springer Nature B.V.
Place of publication
Moscow
Country of publication
Netherlands
ISSN
10757007
e-ISSN
15318664
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2024-03-14
Milestone dates
2024-03-03 (Registration); 2023-04-25 (Received); 2023-08-01 (Accepted); 2023-07-17 (Rev-Recd)
Publication history
 
 
   First posting date
14 Mar 2024
ProQuest document ID
2956992391
Document URL
https://www.proquest.com/scholarly-journals/b-methodological-problems-information-development/docview/2956992391/se-2?accountid=208611
Copyright
© Pleiades Publishing, Ltd. 2024. ISSN 1075-7007, Studies on Russian Economic Development, 2024, Vol. 35, No. 1, pp. 80–90. © Pleiades Publishing, Ltd., 2024. Russian Text c The Author(s), 2024.
Last updated
2025-11-08
Database
ProQuest One Academic