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데이터 분석 기반 AI 발전을 조성하는 경제사회적 요인 분석
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Publication Year
2024-12
Journal
시스템엔지니어링학술지
Publisher
한국시스템엔지니어링학회
Citation
시스템엔지니어링학술지, Vol.20, pp.63-78
Keyword
AI Readiness IndexClusteringDecision treeAI and GDPAI and PopulationAI and Health expenditure
Abstract
This study proposes a novel framework for developing tailored AI strategies at the national level. Employing the Oxford Insights AI Readiness Index, we clustered 193 countries based on similarities in their governmental policies, technological capabilities, data & infrastructure. Subsequently, we analyzed socio-economic factors characterizing these clusters. Clustering was performed using the index's 10 dimensions, while a decision tree analysis identified the relative importance of 6 key socio-economic variables (population, GDP per capita, employment rate, healthcare expenditure as a percentage of GDP, education expenditure as a percentage of GDP, and press freedom index) impacting AI development. Our results empirically validate existing theoretical frameworks by highlighting the significant influence of GDP per capita, population size, and government healthcare expenditure, while demonstrating the limited impact of other considered variables. This combined clustering and decision tree approach provides actionable insights for policymakers navigating the complexities of AI development. The findings offer valuable implications for the design and implementation of effective national AI strategies.
ISSN
1738-480X
Language
Kor
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36115
Type
Article
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Joo, Yeoun.Lee Image
Joo, Yeoun.Lee이주연
Department of Industrial Engineering
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