Earticle

초록

영어

This paper deals with studying strategy about impact of deep learning (DL) on the factor of Korean economic growth. To study classification of impact factors of Korean economic growth, we suggest dynamic equation of microeconomy and study methods on economic growth impact of deep learning. Next step is to suggest DL model to dynamic equation with Korean economy data with growth related factors to classify what factor is import and dominant factors to build policy and education. DL gives an influence in many areas because it can be implemented with ease as just normal editing works and speak including code development by using huge data. Currently, young generations will take a big impact on their job selection because generative AI can do well as much as humans can do it everywhere. Therefore, policy and education methods should be rearranged as new paradigm. However, government and officers do not understand well how it is serious in policy and education. This paper provides method of policy and education for AI education including generative AI through analysing many papers and reports, and experience.

목차

Abstract
1. Introduction
2. Prior research
2.1 Methodological Status of Deep Learning
2.2 Prior case of Deep Learning
3. Economic Effects of DL
3.1 Economic Growth Leading of Generative AI Techniques
3.2 Areas
4. Research strategies and methods for analysis of factors influencing Korean economic growth based on generative AI-based emerging technologies
4.1 Formula Equation Analysis
4.2 Empirical Suggestion
5. Conclusions
References

키워드

저자

• Dong Hwa Kim [ Executive, DSTSC, S. Korea ]
• Dae Sung Seo [ Professor, Paideia Department, Sungkyul University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Internet, Broadcasting and Communication

• 간기

  계간

• pISSN

  2288-4920

• eISSN

  2288-4939

• 수록기간

  2009~2025

• 십진분류

  KDC 326 DDC 380