| id |
ecaade2024_35 |
| authors |
Agkathidis, Asterios; Song, Yang; Symeonidou, Ioanna |
| year |
2024 |
| title |
AI-Assisted Design: Utilising artificial intelligence as a generative form-finding tool in architectural design studio teaching |
| source |
Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 619–628 |
| doi |
https://doi.org/10.52842/conf.ecaade.2024.2.619
|
| summary |
Artificial Intelligence (AI) tools are currently making a dynamic appearance in the architectural realm. Social media are being bombarded by word-to-image/image-to-image generated illustrations of fictive buildings generated by tools such as ‘Midjourney’, ‘DALL-E’, ‘Stable Diffusion’ and others. Architects appear to be fascinated by the rapidly generated and inspiring ‘designs’ while others criticise them as superficial and formalistic. In continuation to previous research on Generative Design, (Agkathidis, 2015), this paper aims to investigate whether there is an appropriate way to integrate these new technologies as a generative tool in the educational architectural design process. To answer this question, we developed a design workflow consisting of four phases and tested it for two semesters in an architectural design studio in parallel to other studio units using conventional design methods but working on the same site. The studio outputs were evaluated by guest critics, moderators and external examiners. Furthermore, the design framework was evaluated by the students through an anonymous survey. Our findings highlight the advantages and challenges of the utilisation of AI image synthesis tools in the educational design process of an architectural design approach. |
| keywords |
AI, GAI, Generative Design, Design Education |
| series |
eCAADe |
| email |
|
| full text |
 file.pdf (758,118 bytes) |
| references |
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