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Socioeconomic and Cultural Determinants of the Development of Artificial Intelligence

Author

Listed:
  • Sorin Paul Lazar
  • Iustin Atanasiu Pop
  • Maria Mortan

Abstract

This study assesses the impact of socioeconomic and cultural factors that are likely to have effects on the development of artificial intelligence at the national level. This technology is evaluated both globally and in terms of its components: qualified users, technical capabilities, regulations, societal support, academic support, algorithms and platforms, support from public authorities, and private economic initiatives. Socioeconomic determinants include economic development and the speed of economic growth, funding for education and research and development, high-tech exports, urbanisation, population, and workforce. Cultural determinants are represented by national aggregate Hofstede s cultural indicators. The available data cover 60 countries from all continents and the period from 2012 to 2022. The research methodology employs hierarchical clustering and robust cross-sectional regression models to avoid heteroscedasticity. The main results indicate highly significant effects of GDP per capita, its growth rate, research and development funding, and the degree of urbanisation. Among cultural factors, only uncertainty avoidance is statistically significant. The multidimensional hierarchical clustering identified six groups corresponding to different national behaviours regarding preferences for the development of certain artificial intelligence technologies and activities.

Suggested Citation

  • Sorin Paul Lazar & Iustin Atanasiu Pop & Maria Mortan, 2024. "Socioeconomic and Cultural Determinants of the Development of Artificial Intelligence," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(66), pages 494-494, Aprilie.
  • Handle: RePEc:aes:amfeco:v:26:y:2024:i:66:p:494
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    More about this item

    Keywords

    artificial intelligence; socioeconomic determinants; Hofstede cultural values; robust cross-sectional regressions; hierarchical clustering;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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