A Study on Human-AI Collaboration Process to Support Evidence-Based National Innovation Monitoring: Case Study on Ministry of Oceans and Fisheries
(주)코리아스칼라
- 최초 등록일
- 2023.07.31
- 최종 저작일
- 2023.06
- 10페이지/ 어도비 PDF
- 가격 4,000원
* 본 문서는 배포용으로 복사 및 편집이 불가합니다.
서지정보
ㆍ발행기관 : 한국산업경영시스템학회
ㆍ수록지정보 : 산업경영시스템학회지 / 46권 / 2호
ㆍ저자명 : Jung Sun Lim, Seoung Hun Bae, Kil-Ho Ryu, Sang-Gook Kim
목차
1. 서 론
2. 선행연구
3. 연구방법
3.1 분석 데이터
3.2 LDA 토픽모델링
3.3 기계학습 및 해석 방법론
3.4 동시출현 네트워크
4. 분석 및 결과
5. 결 론
cknowledgement
References
영어 초록
Governments around the world are enacting laws mandating explainable traceability when using AI(Artificial Intelligence) to solve real-world problems. HAI(Human-Centric Artificial Intelligence) is an approach that induces human decision-making through Human-AI collaboration. This research presents a case study that implements the Human-AI collaboration to achieve explainable traceability in governmental data analysis. The Human-AI collaboration explored in this study performs AI inferences for generating labels, followed by AI interpretation to make results more explainable and traceable. The study utilized an example dataset from the Ministry of Oceans and Fisheries to reproduce the Human-AI collaboration process used in actual policy-making, in which the Ministry of Science and ICT utilized R&D PIE(R&D Platform for Investment and Evaluation) to build a government investment portfolio.
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