Exploring human-machine collaboration paths in the context of AI- generation content creation: a case study in product styling design
Wei Li, Weidi Zhang, Weilu Wu, Jie Xu
Abstract
The advent of generative AI has profoundly influenced contemporary design, offering a cost-effective method for creating a wide array of digital elements through Artificial Intelligence Generated Content (AIGC). This innovation signifies a pivotal change in how humans collaborate with machines in the design process, necessitating new adaptations in product styling workflows. Unfortunately, a clear and practical design process has not yet been established, despite the pioneering efforts of several leaders in the product design domain who have begun to incorporate AIGC technology. This study aims to integrate AIGC with product styling design to enhance workflow efficiency and explore new dimensions of human-machine collaboration. Leveraging an ethnographic research methodology, we comprehensively analyzed the AIGC and product design communities. Building upon this foundation, we propose an AIGC-enabled product design methodology. Based on our findings, we developed an AIGC-enabled product design technique, which we then tested in practical scenarios through specific design cases. Our results demonstrate the methodology’s effectiveness in improving the product styling design workflow. Additionally, this study points toward new pathways for human-machine collaboration within the context of AI creation, shedding light on potential avenues for integrating AIGC more broadly in the product design field.