Think AI-side the Box! Exploring the Usability of Text-to-Image Generators for Architecture Students

Jonathan Dortheimer, Gerhard Schubert, Agata Dalach, Lielle Brenner, Nikolas Martelaro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

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.

Original languageEnglish
Title of host publicationeCAADe 2023 - Digital Design Reconsidered
EditorsWolfgang Dokonal, Urs Hirschberg, Gabriel Wurzer, Gabriel Wurzer
PublisherEducation and research in Computer Aided Architectural Design in Europe
Pages567-576
Number of pages10
ISBN (Print)9789491207358
StatePublished - 2023
Event41st Conference on Education and Research in Computer Aided Architectural Design in Europe, eCAADe 2023 - Graz, Austria
Duration: 20 Sep 202322 Sep 2023

Publication series

NameProceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe
Volume2
ISSN (Print)2684-1843

Conference

Conference41st Conference on Education and Research in Computer Aided Architectural Design in Europe, eCAADe 2023
Country/TerritoryAustria
CityGraz
Period20/09/2322/09/23

Keywords

  • Computational Creativity
  • Design Process
  • Diffusion Models
  • Machine Learning

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