Using Text-to-Image Generation for Architectural Design Ideation
This addresses how architects and designers can leverage AI for ideation, though it is incremental as it applies existing methods to a new domain.
The study investigated using text-to-image generators like Midjourney, Stable Diffusion, and DALL-E to support creativity in early architectural design, finding through a lab with 17 students that these tools enable serendipitous idea discovery and enrich the process when constraints are considered.
The recent progress of text-to-image generation has been recognized in architectural design. Our study is the first to investigate the potential of text-to-image generators in supporting creativity during the early stages of the architectural design process. We conducted a laboratory study with 17 architecture students, who developed a concept for a culture center using three popular text-to-image generators: Midjourney, Stable Diffusion, and DALL-E. Through standardized questionnaires and group interviews, we found that image generation could be a meaningful part of the design process when design constraints are carefully considered. Generative tools support serendipitous discovery of ideas and an imaginative mindset, enriching the design process. We identified several challenges of image generators and provided considerations for software development and educators to support creativity and emphasize designers' imaginative mindset. By understanding the limitations and potential of text-to-image generators, architects and designers can leverage this technology in their design process and education, facilitating innovation and effective communication of concepts.