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국가 AI 경쟁력에 따른 OECD 국가 유형 분류: 퍼지셋 이상형 분석을 중심으로

Classification of OECD Countries Based on National AI Competitiveness: Employing Fuzzy-set Ideal Type Analysis

  • 신승윤
  • Shin, Seung-Yoon (Software Policy and Research Institute)
  • 투고 : 2024.02.21
  • 심사 : 2024.04.29
  • 발행 : 2024.06.30
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초록

본 연구는 AI 인적자본, AI 기반 인프라, AI 기술혁신역량 요인을 중심으로 OECD 38개국의 국가 AI 경쟁력 수준을 확인하고, 퍼지셋 이상형 분석방법을 활용하여 OECD 38개국을 국가 AI 경쟁력 수준에 따라 여덟 가지 유형으로 분류, 시사점을 도출하였다. 분석 결과, "AI 선도국" 유형에는 대체적으로 북미, 서유럽, 북유럽 국가와 함께, 대한민국을 포함하는 아시아 국가들이 포함되었다. 특히 미국은 국가 AI 경쟁력 3개 요인 모두에서 분석 대상 국가 중 가장 높은 퍼지점수를 보이는 등 글로벌 국가AI 경쟁력을 압도하는 모습을 보였다. 대한민국의 경우, 우수한 AI 기반 인프라 수준을 바탕으로 AI 선도국 유형에 포함되었으나, AI 인적자본과 AI 기술혁신역량 요인은 분석 대상 국가 중 중위권 수준에 머무르고 있어 향후 장기적 관점에서의 AI 인적자본 축적과 AI 기술혁신역량 강화가 요구된다.

This study assesses the national AI competitiveness of 38 OECD countries with focus on AI human capital, AI infrastructure, and AI innovation capacity. Utilizing the fuzzy-set ideal type analysis method, these countries were categorized into eight distinct types based on their national AI competitiveness levels, leading to the derivation of pertinent implications. The analysis identified a category termed "AI Leading Country" consisting of North American, Western European, and Nordic countries, along with several Asian nations including South Korea. Remarkably, the United States demonstrated dominant global national AI competitiveness, achieving the highest fuzzy scores across all three evaluative factors. South Korea was classified as an "AI Leading Country" primarily due to its superior AI infrastructure, but its performance in AI human capital and AI innovation capacity was found to be moderate relative to other analyzed nations; thus highlighting the necessity of sustained focus on the accumulation of AI human capital and bolstering of AI innovation capacity.

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