Project Title: 

Streamlining Designer-Client Inter(Ai)Ction

Project Summary: 

Traditionally, architects switch between the role of designer and client to better understand their client’s needs and preferences for a design (Hettithanthri et al., 2022; Vartiainen & Tedre, 2024). However, such approaches to the architectural design process have limited design ideas to the designer’s own understanding of their clients from a single meeting. Leaving clients dissatisfied with design outcomes. Image Generative Artificial Intelligence (Image GenAI), where the instant translation of text into image have been enabled, presents a new opportunity to extend such design activities beyond the design practitioner and towards non-designer stakeholders through an unsupervised learning environment (Alhabeeb & Al-Shargabi, 2024; Goodfellow et al., 2020). Ultimately, the advent of Image GenAI have and will undoubtedly continue to influence and transform the ways in stakeholder interactions are approached in architecture. However, there remains to be a limited understanding, balance, and exploration on the nature of designer-client interactions in the architectural design processes (Verheijden & Funk, 2023; Pouliou et al., 2024). Even more so in the new age of Image GenAI.  

This study aims to gain a greater understanding on how Image GenAI have and will continue to support design practitioners and engage non-design stakeholders in public space design projects, through the creation of a model and toolkit for best practice use of an Image GenAI-supported architectural design process. Following the Design Research Methodology adopted (Blessing and Chakrabarti, 2009), the main objectives of this research project are to develop an understanding and support to change current approaches towards designer-client interactions in architecture to desired ones in the new age of Image GenAI. Early findings from a review of literature and autoethnographic study conducted revealed that there is a significant relationship that can already be observed between traditional approaches to architectural design and Image GenAI’s current capabilities for supporting the design practice. Such relationships identified have then been developed into a preliminary Image GenAI-supported architectural design process model above, for later testing and exploration with designer and non-designer individuals. 

References: 

Alhabeeb, S. K., & Al-Shargabi, A. A. (2024). Text-to-Image Synthesis With Generative Models: Methods, Datasets, Performance Metrics, Challenges, and Future Direction. IEEE access, 12, 24412-24427. https://doi.org/10.1109/access.2024.3365043  

Blessing, L. T. M., & Chakrabarti, A. (2009). DRM, a Design Research Methodology (1. Aufl. ed.). Springer Verlag London Limited. https://doi.org/10.1007/978-1-84882-587-1 

Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2020). Generative adversarial networks. Communications of the ACM, 63(11), 139-144. https://doi.org/10.1145/3422622 

Hettithanthri, U., Hansen, P., & Munasinghe, H. (2022). Exploring the architectural design process assisted in conventional design studio: a systematic literature review. International Journal of Technology and Design Education, 33(5), 1835-1859. https://doi.org/10.1007/s10798-022-09792-9  

Pouliou, P., Palamas, G., & Horvath, A. S. (2024). Decisions We Should Put in the Algorithm: Mapping architect’s attitudes towards computational and AI-powered tools for practice. Conference: 29th Annual Conference for Computer-Aided Architectural Design Research in Asia (CAADRIA), Singapore. 

Vartiainen, H., & Tedre, M. (2024). How Text-to-Image Generative AI is Transforming Mediated Action. IEEE computer graphics and applications, PP, 1-12. https://doi.org/10.1109/MCG.2024.3355808 

Verheijden, M. P., & Funk, M. (2023). Collaborative Diffusion: Boosting Designerly Co-Creation with Generative AI Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems,  https://dl.acm.org/doi/pdf/10.1145/3544549.3585680