Cognitive determinants and technological adoption: examining behavioral intention mechanisms in Chinese artisanal design practices mediated by AI-generated content

Engineering notes

Key topics: autonomous driving. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Artificial Intelligence-Generated Content (AIGC) is a rapidly evolving technology with significant computational and creative potential, offering new possibilities in design, aesthetics, and process innovation. However, traditional artisans view AIGC as a potential threat to the authenticity and value of their work. Research on artisans’ acceptance of AIGC is limited. This study aims to identify the key factors influencing Chinese artisans’ willingness to adopt AIGC-assisted design and develop a context-specific measurement scale and evaluation model. A mixed-methods approach combining qualitative and quantitative research was used, including Craftsman interviews and literature review. Exploratory factor analysis and structural equation model analysis identified six key factors affecting adoption: serendipity for design, artisanal epistemology, performance expectancy, and perceived ease of use. Simulated craft authenticity and epistemic openness did not show direct effects. The study highlights the need for technology integration that respects artisans’ cognitive frameworks and creative traditions, advocating for a shift from technological neutrality to cultural adaptation and collaborative co-creation.

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