关键词: 人机知识共创, 矛盾态度, 人智交互, 情境式问卷法, 系统性决策

Abstract: [Purpose/Significance] Knowledge acquisition through AIGC platform has gradually become a catalyst for cognitive breakthrough and a source of innovation for knowledge users. Human-computer knowledge co-creation is a new type form of human-computer interaction in the era of human-AI collaboration. Exploring the impact of users' ambivalent attitudes on their experience of human-computer knowledge co-creation can help restore the interactive context and promote the sustainable development of the AIGC platform. [Design/Methodology] In this study, through a contextual questionnaire method and by introducing cognitive load theory, we construct a research model of the relationship between different degrees of ambivalence and human-computer knowledge co-creation experiences, and explore the mediating role of systematic decision-making and the moderating role of algorithmic involvement. [Findings/Conclusion] There is an inverted "U"-shaped relationship between ambivalence and the experience of human-computer knowledge co-creation. As the degree of ambivalence deepened, the human-computer knowledge co-creation experience shows a tendency of initially increasing and subsequently decreasing. Systematic decision-making mediates the relationship between ambivalence and human-computer knowledge co-creation experience. Furthermore, the extent of algorithmic involvement regulates the mediating effect, at different levels of algorithmic involvement, the inverted "U"-shaped relationship between ambivalence and systematic decision-making exists, and the combination of medium ambivalence and high algorithmic involvement performs optimally. [Originality/Value] The study enriches the application of cognitive load theory, helps to dialectically understand the ambivalence of users, and offers references for the improvement of users' knowledge co-creation experience during human-AI interaction.

Keywords: Human-computer knowledge co-creation, Ambivalence, Human-AI interaction, Contextual questionnaire method, Systematic decision-making