한국전산구조공학회논문집 (Journal of the Computational Structural Engineering Institute of Korea)

  • 제34권5호
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  • Pages.327-337
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  • 2021
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  • 1229-3059(pISSN)
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  • 2287-2302(eISSN)
한국전산구조공학회 (Computational Structural Engineering Institute of Korea)
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4차 산업혁명시대의 디지털 경공업

Flip Side of Artificial Intelligence Technologies: New Labor-Intensive Industry of the 21st Century

  • Heo, Seokjae (Remodeling Research Center, Dankook University) ;
  • Na, Seunguk (Department of Architectural Engineering, Dankook University) ;
  • Han, Sehee (Department of Architectural Engineering, Dankook University) ;
  • Shin, Yoonsoo (Department of Architectural Engineering, Dankook University) ;
  • Lee, Sanghyun (Department of Architectural Engineering, Dankook University)
  • 투고 : 2021.08.17
  • 심사 : 2021.09.24
  • 발행 : 2021.10.31
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초록

본 연구는 인공지능 연구개발과정에 많은 인적자원이 필요함을 인지하고 현 개발방식 고려할 사항에 대해 논의한다. 결론적으로 인공지능 개발의 효율성 향상을 위해서는 소수의 관리자와 많은 일반작업자들의 분업화가 이루어져야 가능하며, 이는 마치 일종의 경공업의 형태와 유사하다고 생각된다. 따라서 본 연구진은 컴퓨터라는 기계장치로 데이터라는 디지털 자원을 다루어 생산의 효율성을 높이는 인공지능 개발과정을 4차산업시대의 디지털 경공업이라고 명명한다. 이전 산업혁명시대에서 경험한 것과 마찬가지로 인적자원을 효율적으로 배분화하고 활용한다면 디지털 경공업은 2차산업혁명 못 지 않는 발전을 기대할 수 있을 것이며, 이를 위한 인력양성이 시급하다고 판단된다.

The paper acknowledges that many human resources are needed on the research and development (R&D) process of artificial intelligence (AI), and discusses on factors to consider on the current method of development. Enfin, in order to enhance efficiency of AI development, it seems possible through labour division of a few managers and numerous ordinary workers as a type of light industry. Thus, the research team names the development process of AI, which maximizes production efficiency by handling digital resources named 'data' with mechanical equipment called 'computer', as digital light industry of fourth industrial era. As experienced during the previous Industrial Revolution, if human resources are efficiently distributed and utilized, digital light industry would be able to expect progress no less than the second Industrial Revolution, and human resources development for this is considered urgent.

키워드

과제정보

본 연구는 한국과학재단이 주관하는 대학중점연구소지원사업(No. NRF-2018R1A6A1A07025819)과 신진연구지원사업(No. NRF-2020R1C1C1005406)의 지원을 받아 수행되었습니다.

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