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A Study on the Work Type of Machine Learning Administrative Service in Metropolitan Government
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광역자치단체의 기계학습 행정서비스 업무유형에 관한 연구-서울시를 중심으로-

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Type
Academic journal
Author
Chung-Yeol Ha (한성대학교 공공컨설팅학과) Jung Jin-Taek (한성대학교)
Journal
The Korea Society of Digital Policy & Management 디지털융복합연구 디지털융복합연구 제18권 제12호 KCI Accredited Journals
Published
2020.1
Pages
29 - 36 (8page)

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A Study on the Work Type of Machine Learning Administrative Service in Metropolitan Government
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Abstract· Keywords

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The background of this study is that machine learning administrative services are recently attracting attention as a major policy tool for non-face-to-face administrative services in the post-corona era. This study investigated the types of work expected to be effective when introducing machine learning administrative services for Seoul Metropolitan Government officials who are piloting machine learning administrative services. The research method is a machine that can be introduced by organizational unit by distributing and collecting questionnaires for Seoul administrative organizations that have performed machine learning-based administrative services for one month in July 2020 targeting Seoul public officials using machine learning-based administrative services. By analyzing the learning administration service and application service, the business characteristics of each machine learning administration service type such as supervised learning work type, unsupervised learning work type, and reinforced learning work type were analyzed. As a result of the research analysis, it was found that there were significant differences in the characteristics of administrative tasks by supervised and unsupervised learning areas. In particular, it was found that the reinforcement learning domain contains the most appropriate business characteristics for machine learning administrative services. Implications were drawn. The results of this study can be provided as a reference material to practitioners who want to introduce machine learning administration services, and can be used as basic data for research to researchers who want to study machine learning administration services in the future.
#재택근무 #원격근무 #모바일근무 #유연근무제 #비대면 행정서비스

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Accenture / 2016 / Digital government: Your digital citizens are ready, willing… and wait google schola R. Ayachi, I. / 2016 / Proactive and reactive e-government services recommendation / Universal Access in the Information Society 15(4):681~697 google schola J. Bosse / 2015 / European Public Sector Award 2015: The public sector as partner for a better society European Institute of Public Administration google schola European Commission / 2016 / Government benchmark 2016: A turning point for eGovernment development in Europe? google schola Hendrik Scholta / 2019 / From one-stop shop to no-stop shop : An e-government stage model / Government Information Quarterly 36(1):11~26 google schola

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