Think AI-side the Box! Exploring the Usability of text-to-image generators for architecture students
Jonathan Dortheimer, Gerhard Schubert, Agata Dalach, Lielle Joy Brenner, Nikolas Martelaro
Abstract
This study examines how architecture students use generative AI image generating models for architectural design. A workshop was conducted with 25 participants to create designs using three state-of-the-art generative diffusion models and BIM or 3D modeling software. Results showed that the participants found the image-generating models useful for the preliminary design stages but had difficulty when the design advanced because the models did not perform as they expected. Finally, the study shows areas for improvement that merit further research. The paper provides empirical evidence on how generative diffusion models are used in an architectural context and contributes to the field of digital design.