인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
개인구독
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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
Objective: This paper aims to analyze the human factors in artificial intelligence and discuss the Human-AI collaboration based on previous researches in three major fields such as healthcare, teaching and automated driving. Background: Despite the fact that artificial intelligence is one of the largest and most important inventions of the present, the researches have shown that there are several challenges of using artificial intelligence in the cooperation with human teammates. AI-Infused systems may perform certain operations or tasks faster and more precisely than a person, play chess, drive a car and perform many functions. But, depending on the different type of human factors, users may interact differently with artificial intelligence, and those factors make some challenges in the relationship between human and artificial intelligence. Method: This paper was conducted in three steps: (1) Reviewing previous researches on human factors in three areas; (2) Categorizing human factors in to the table to analyze their importance in adoption to AI infused systems; (3) Identifying the most critical human factors of individuals in three fields in collaboration with artificial intelligence devices to deal with the challenges of AI acceptance to improve teamwork and work efficiency as well as reducing errors mostly caused by human factors for each field. Results: Gender, age and trust in technology are found the most critical factors for each fields, while technology expertise and social influence factors plays important role in adoption AI-Infused systems in Education and Healthcare. Conclusion: It is found that, autonomous driving is most discussed field in terms of use human factors in the interaction with artificial intelligence, while there is still lack of researches about the adoption to AI technologies in education and healthcare based on some differences of human factors such as health, cognitive, work and , physical capabilities. Application: Findings of this study can help for the further studies focusing on identifying the cause of human errors that can be occurred in takeover or handover scenarios in terms of use AI-Infused Systems in healthcare, autonomous driving, and education.
본문·목차
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