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인공지능을 활용한 정책의사결정에 관한 탐색적 연구: 문제구조화 유형으로 살펴 본 성공과 실패 사례 분석
An Exploratory Study on Policy Decision Making with Artificial Intelligence: Applying Problem Structuring Typology on Success and Failure Cases 원문보기

정보화 정책 = Informatization policy, v.27 no.4, 2020년, pp.47 - 66  

은종환 (Public Policy Center of Intelligent Society and Policy) ,  황성수 (Department of Public Administration, Yeungnam University)

초록
AI-Helper 아이콘AI-Helper

머신러닝딥러닝인공지능 기술의 급속한 발전은 행정-정책 분야에도 영향을 확대하고 있다. 이 논문은 데이터분석과 알고리즘의 발전으로 자동화된 구성과 운용을 설계하는 인공지능 시대의 정책의사결정에 관한 탐색적 연구이다. 이 연구의 의의는 정책의사결정에서의 주요 연구 중 하나인 정책 문제의 문제구조화를 기반으로 하여, 문제정의가 잘 구조화된 정도에 따른 유형으로 이론적 틀을 구성하여 성공과 실패 사례를 구분하고 분석해서 시사점을 도출하였다. 즉 문제구조화가 어려운 유형일수록 인공지능을 활용한 의사결정의 실패 혹은 부작용의 우려가 크다는 것이다. 또한 알고리즘의 중립성여부에 대한 우려도 제시하였다. 정책적 제언으로는 우리나라 인공지능 추진체계구축 시 기술적 측면과 사회적 측면의 전문가들이 전문적으로 역할을 하는 소위원회를 병렬적으로 두고 이 소위원회들이 종합적, 융합적으로도 작동할 수 있는 운영의 묘를 발휘하는 거버넌스 추진체계 구축이 필요함을 제시하고 있다.

Abstract AI-Helper 아이콘AI-Helper

The rapid development of artificial intelligence technologies such as machine learning and deep learning is expanding its impact in the public administrative and public policy sphere. This paper is an exploratory study on policy decision-making in the age of artificial intelligence to design automat...

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