Multi-PDAI: integrating multimodal GenAI models for participatory design

Participatory Design is one of the traditional human-centred approaches commonly used during the early stages of the design process. Currently, Large Language Models and Generative Artificial Intelligence (GenAI) are increasingly being adopted in the early stage of design, particularly for requirements analysis and conceptual design. To harness the respective strengths of Participatory Design and GenAI, it is essential to approach the problem through the lens of multimodal human–machine perception. In this paper, we propose a new multimodal GenAI-Driven Participatory Design approach and develop the Multi-PDAI platform, which is validated in the context of wheeled humanoid robot design. A crossover experiment (N designers = 8, N users = 16) was conducted with evaluation data on the generated images from design industry experts (N = 10). Platform usability was assessed using the SUS scale. In addition, users’ UEQ data and designers’ IMI data were analyzed, with systematic comparisons of initial and final prompt templates, design completion criteria, and time–process metrics. The results show that the images generated by the Multi-PDAI platform are more innovative and aesthetically appealing, and the platform demonstrates better usability compared to Stable Diffusion (M = 72.5, Sig. = 0.043). These findings further support the hypothesis that participatory design and GenAI are mutually beneficial, and that multimodality in GenAI is essential.