# Exploring Designer Trust in Artificial Intelligence-Generated Content: TAM/TPB Model Study
## 1 Introduction  
The widespread adoption of Artificial Intelligence-Generated Content (AIGC) technology has become a hallmark of our era, acting as a double-edged sword for the design industry. Some designers worry that AIGC will lower industry standards, thereby affecting their income and career development. Conversely, others are eager to use AIGC to enhance work efficiency and broaden the scope of applications. As academic researchers, we are more concerned with the impact of AIGC technology on the design ecosystem: from design education and training at the front end, to design research and innovation and commercial practice in the mid-stage, and finally to design generation and evaluation at the back end. Therefore, this paper uses designers' basic drawing skills as a starting point to explore their acceptance of AIGC. This study employs a combination of expert interviews and questionnaires. Independent sample \(T\)-tests and variance analysis were used for data analysis. Theresults indicate that designers with high professional recognition and relevant experience with AIGC exhibit a more positive attitude towards the technology. In contrast, those without relevant experience demonstrate a relatively negative attitude. Designers' acceptance of AIGC is somewhat influenced by their existing drawing skills. These findings can provide valuable references for design education, design services, and other researchers. AIGC has been widely applied in various aspects of the art and design field, accelerating design visualization and expanding design possibilities, thus fostering the flourishing development of the art and design industry [1]. Its impact on the field of art and design is mainly reflected in three areas: the internal working methods of the industry, the external social influence, and human-machine collaborative innovation. Specifically, it encompasses the following: (1) It has transformed the work content, processes, and design thinking of designers. It reduces the workload in the ideation phase, allowing designers to focus more on refining design definitions and deepening design thinking [2]. (2) It has lowered the industry threshold for design, enabling cross-disciplinary knowledge integration. By diminishing the skill barriers in the art and design industry, it has popularized innovation awareness across society, allowing innovators from various fields to leverage the efficiency of AIGC to collectively advance the art and design industry [3]. (3) Designers will achieve specialization and personalization of AI assistants through model training. Mastery of AIGC will become a fundamental skill for future designers, who will actively seek the optimal convergence of technology and human creativity, thereby attaining an efficient human-machine collaborative innovation working model [4]. In conclusion, AIGC, driven by data-driven innovation, has inspired an industrial revolution in the art and design field, optimizing design processes, methods, and quality, and thereby propelling the rapid development of the art and design industry. Current academic research predominantly focuses on technology research and applications, with limited studies addressing users' attitudes and behavioral changes towards artificial intelligence technology, especially in the field of art and design. This study aims to analyze designers' acceptance and trust in AI-generated content (AIGC), exploring how designers' intrinsic characteristics influence perceived risk (both functional and emotional) and trust. Additionally, it examines the impact of perceived characteristics, perceived risk, and trust on designers' behavioral intentions. By enhancing the transparency and credibility of AIGC and safeguarding designers' legitimate rights, this study aims to reduce perceived risk and increase trust, thereby promoting designers' behavioral intentions towards AIGC.