Using text-to-image generation for architectural design ideation

• Published in: International journal of architectural computing Vol. 22; no. 3; pp. 458 - 474
• Main Authors: Paananen, Ville, Oppenlaender, Jonas, Visuri, Aku
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.09.2024
• Subjects: text-to-image generation; Architecture; design creativity; generative artificial intelligence
• ISSN: 1478-0771; 2048-3988
• DOI: 10.1177/14780771231222783

Text-to-image generation has become very popular in various domains requiring creativity. This article investigates 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.