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

Е. V. Zarova, G. К. Abdurakhmanova, В. О. Tursunov
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Abstract

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.
全球铝指数与就业水平的关系:评估跨国差异的聚类方法
文章论证了衡量和分析就业水平对经济和社会领域引入人工智能(AI)的 "反应 "问题。作者提出了一些方法,用于研究代表不同大洲和经济集团的一组国家的人工智能发展和就业水平的整体和组成部分评估的相互依存关系。评估基于 Tortoise Media 于 2023 年首次发布的 62 个国家的全球人工智能指数(GAII)和聚类分析方法,包括按人工智能的总体水平和组成部分对各国进行区分。人工智能子指数的数值被纳入考虑范围,其特征包括是否存在实施人工智能的国家战略、人工智能的商业基础、用于科学研究和开发的情况、运营环境的形成、基础设施的发展、对 "人才 "的支持--人工智能领域的知识领袖(包括机构领袖)。根据聚类分析的结果,确定了俄罗斯联邦在国家组中的位置,这些国家的特点是对人工智能发展的总体评估相对平均,并在实施将人工智能引入公共生活的国家战略计划方面处于领先地位。对选定国家组构建的散点图趋势进行分析和建模的结果表明,全球指数各组成部分的人工智能发展与就业水平之间的现有关系具有多向性和模糊性。同时,所有国家组群的就业水平与全球人工智能指数综合评估之间的现有关系在统计上被评估为较弱。得出的结论是,在预测人工智能对就业水平和结构变化的影响时,有必要考虑到已确定的统计估计差异(按国家和人工智能组成部分)。同时,作者认为,现阶段的初步结论表明了评估人工智能对就业影响问题的相关性、理论和实践意义,以及不同国家解决这一问题的模糊性。
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