Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry

The paper examines that many human resources are needed on the research and development (R&D) process of artificial intelligence (AI) and discusses factors to consider on the current method of development. Labor division of a few managers and numerous ordinary workers as a form of light industry...

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Autores principales:	Seokjae Heo, Sehee Han, Yoonsoo Shin, Seunguk Na
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	digital light industry fourth Industrial Revolution artificial intelligence human resource development work index architecture Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/8552ae56d67b4187ad20d6e74836a987
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id	oai:doaj.org-article:8552ae56d67b4187ad20d6e74836a987
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spelling	oai:doaj.org-article:8552ae56d67b4187ad20d6e74836a9872021-11-25T16:40:53ZChallenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry10.3390/app1122109192076-3417https://doaj.org/article/8552ae56d67b4187ad20d6e74836a9872021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10919https://doaj.org/toc/2076-3417The paper examines that many human resources are needed on the research and development (R&D) process of artificial intelligence (AI) and discusses factors to consider on the current method of development. Labor division of a few managers and numerous ordinary workers as a form of light industry appears to be a plausible method of enhancing the efficiency of AI R&D projects. Thus, the research team regards the development process of AI, which maximizes production efficiency by handling digital resources named ‘data’ with mechanical equipment called ‘computers’, as the digital light industry of the fourth industrial era. As experienced during the previous Industrial Revolution, if human resources are efficiently distributed and utilized, no less progress than that observed in the second Industrial Revolution can be expected in the digital light industry, and human resource development for this is considered urgent. Based on current AI R&D projects, this study conducted a detailed analysis of necessary tasks for each AI learning step and investigated the urgency of R&D human resource training. If human resources are educated and trained, this could lead to specialized development, and new value creation in the AI era can be expected.Seokjae HeoSehee HanYoonsoo ShinSeunguk NaMDPI AGarticledigital light industryfourth Industrial Revolutionartificial intelligencehuman resource developmentwork indexarchitectureTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10919, p 10919 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	digital light industry fourth Industrial Revolution artificial intelligence human resource development work index architecture Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	digital light industry fourth Industrial Revolution artificial intelligence human resource development work index architecture Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Seokjae Heo Sehee Han Yoonsoo Shin Seunguk Na Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry
description	The paper examines that many human resources are needed on the research and development (R&D) process of artificial intelligence (AI) and discusses factors to consider on the current method of development. Labor division of a few managers and numerous ordinary workers as a form of light industry appears to be a plausible method of enhancing the efficiency of AI R&D projects. Thus, the research team regards the development process of AI, which maximizes production efficiency by handling digital resources named ‘data’ with mechanical equipment called ‘computers’, as the digital light industry of the fourth industrial era. As experienced during the previous Industrial Revolution, if human resources are efficiently distributed and utilized, no less progress than that observed in the second Industrial Revolution can be expected in the digital light industry, and human resource development for this is considered urgent. Based on current AI R&D projects, this study conducted a detailed analysis of necessary tasks for each AI learning step and investigated the urgency of R&D human resource training. If human resources are educated and trained, this could lead to specialized development, and new value creation in the AI era can be expected.
format	article
author	Seokjae Heo Sehee Han Yoonsoo Shin Seunguk Na
author_facet	Seokjae Heo Sehee Han Yoonsoo Shin Seunguk Na
author_sort	Seokjae Heo
title	Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry
title_short	Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry
title_full	Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry
title_fullStr	Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry
title_full_unstemmed	Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry
title_sort	challenges of data refining process during the artificial intelligence development projects in the architecture, engineering and construction industry
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/8552ae56d67b4187ad20d6e74836a987
work_keys_str_mv	AT seokjaeheo challengesofdatarefiningprocessduringtheartificialintelligencedevelopmentprojectsinthearchitectureengineeringandconstructionindustry AT seheehan challengesofdatarefiningprocessduringtheartificialintelligencedevelopmentprojectsinthearchitectureengineeringandconstructionindustry AT yoonsooshin challengesofdatarefiningprocessduringtheartificialintelligencedevelopmentprojectsinthearchitectureengineeringandconstructionindustry AT seungukna challengesofdatarefiningprocessduringtheartificialintelligencedevelopmentprojectsinthearchitectureengineeringandconstructionindustry
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Challenges of Data Refining Process during the Artificial Intelligence Development Projects in the Architecture, Engineering and Construction Industry

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