The Relationship of the Global Al Index and the Level of Employment: A Cluster Approach in Assessing Cross-Country Differences

The article substantiates the problem of measuring and analyzing the «response» of the employment level to the introduction of artificial intelligence (AI) in the economic and social spheres. The authors propose methods for studying the interdependence of integral and component assessments of the development of artificial intelligence and the level of employment for a set of countries representing different continents and economic groups. An assessment was made based on the first ever Global AI Index (GAII) published by Tortoise Media in 2023 for 62 countries and cluster analysis methods, including differentiation of countries by general level and components of artificial intelligence. The values of AI sub-indices were taken into account, characterizing such components as the presence of a state strategy for the implementation of AI, its commercial basis, use for scientific research and development, the formation of an operating environment, infrastructure development, support for «talents» - intellectual leaders (including institutional ones) in the field of AI. Based on the results of cluster analysis, the Russian Federation’s place in the group of countries characterized by a relatively average overall assessment of the development of artificial intelligence and leading in the implementation of statestrategic programs for the introduction of AI into public life has been established.

The results of the analysis and modeling of trends in scatter diagrams constructed for selected clusters of countries show the multidirectionality and ambiguous strength of the existing relationship between the development of artificial intelligence for individual components of the Global Index and the level of employment. At the same time, the existing relationship between the level of employment and the integral assessment of the Global AI Index was assessed as statistically weak for all clusters of countries. Conclusions were drawn about the need to take into account the identified differences in statistical estimates (both by country and by AI components) when predicting the impact of AI on changes in the level and structure of employment.

As this topic is filled with statistical research, the conclusions drawn from the results of the study will be deepened and continued by the authors. At the same time, according to the authors, the formulated conclusions, which are preliminary at this stage, indicate the relevance, theoretical and practical significance of the problem of assessing the impact of AI on employment, as well as the ambiguity of its solution in different countries.

1. Turing A.M. Computing Machinery and Intelligence. Mind. 1950;LIX(236):433–460. Available from: https://redirect.cs.umbc.edu/courses/471/papers/turing.pdf.

2. Abdurakhmanov K.Kh. Transformation of the Labor Market in the Context of the Introduction of Artificial Intelligence. Russian Journal of Labour Economics. 2023;10(2):227–246. (In Russ.) Available from: https://doi.org/10.18334/et.10.2.117364; https://1economic.ru/lib/117364.

3. Abdurakhmanov K.Kh. Features of Development of Digital Economy in Uzbekistan. Academic Journal of Digital Economics and Stability. Special Issue on «Innovative Economy: Challenges, Analysis and Prospects for Development». 2021;370–375. Available from: https://economics.academicjournal.io/index.php/economics/article/view/192.

4. Akyulov R.I. Modern Artificial Intelligence Technology and Employment: Problems and Prospects of Control. Management Issues. 2019;59(4):89–97. (In Russ.)

5. Kamara P. Influence of Artificial Intelligence on Employment on the Example of Transport Industry of France. Vestnik Universiteta. 2019;(12):71–77. (In Russ.) Available from: https://cyberleninka.ru/article/n/vliyanie-iskusstvennogo-intellekta-na-trudovuyu-zanyatost-na-primere-transportnoy-otrasli-frantsii (accessed 14.01.2024).

6. Petrovskaya N.E. The Impact of New Technologies and Robotics on Employment in the United States. UPRAVLENIE/MANAGEMENT (Russia). 2020;8(3):81–90. (In Russ.) Available from: https://doi.org/10.26425/2309-3633-2020-8-3-81-90.

7. Filipova I.A. Transformation of Legal Regulation of Labor in a Digital Society. Artificial Intelligence and Labor Law: Scientific Publication. Nizhny Novgorod: Lobachevsky State University of Nizhny Novgorod; 2019. 89 p. (In Russ.)

8. Makarov M.Yu. The Impact of Artificial Intelligence on Productivity. Economics and Management. 2020;26(5):479–486. (In Russ.) Available from: https://doi.org/10.35854/1998-1627-2020-5-479-486.

9. Friedrich S. et al. Is There a Role for Statistics in Artificial Intelligence? Advances in Data Analysis and Classification. 2022;(16):823–846. Available from: https://doi.org/10.1007/s11634-021-00455-6.

10. Searle J.R. Minds, Brains, and Programs. Behavioral and Brain Sciences. 1980;3(3):417–424. Available from: https://doi.org/10.1017/S0140525X00005756.

11. McCarthy J. What is Artificial Intelligence? Computer Science Department, Stanford University; 2007. Available from: https://www-formal.stanford.edu/jmc/whatisai.pdf.