Earticle

초록

영어

While generative artificial intelligence (GAI) has shown promise in various domains, it faces challenges such as knowledge deficits and hallucination issues. To tackle these problems, we propose a multi-AI collaboration system. Our research employs a mixed-methods approach, combining Design Science Research (DSR) with quantitative and qualitative methods. We investigate the design principles for efficient multi-AI collaboration systems and their impact on team trust compared to single AI collaboration. The results indicate that multi-AI collaboration systems significantly enhance users' trust in AI, particularly in the perception of capability. Furthermore, a number of key design principles for multi-AI collaboration systems were identified. These findings contribute to the development of more effective and trustworthy AI collaboration systems, paving the way for improved human-AI teamwork.

목차

Abstract
Introduction
Methods
Findings and Future Directions
Acknowledgments
References

키워드

저자

• Ang Zeng [ School of Information, Renmin University of China ]
• Xusen Cheng [ School of Information, Renmin University of China ] Corresponding Author
• Kanliang Wang [ School of business, Renmin University of China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국경영정보학회 정기 학술대회 [KMIS Conference]

• 간기

  반년간

• 수록기간

  1990~2025

• 십진분류

  KDC 325 DDC 658