| id |
ecaade2023_137 |
| authors |
Blaas, Quintin, Pelosi, Antony and Brown, Andre |
| year |
2023 |
| title |
Reconsidering Artificial Intelligence as Co-Designer |
| doi |
https://doi.org/10.52842/conf.ecaade.2023.2.559
|
| source |
Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 559–566 |
| summary |
The research in this paper is presented from the perspective of a designer interested in investigating using artificial intelligence, specifically machine learning, to act as a co-pilot during architectural design phases. Significant recent interest has been evident in, for instance, rapidly developing text-to-image and intelligent chat AI areas. However, we have a particular focus and have undertaken a series of feasibility experiments to explore the potential for enabling a designer's exploitation of machine learning, and consequently in effect, using machine learning as a co-designer. We conclude that the industry would need to develop certain protocols to take advantage of the opportunities available through such an AI-assisted approach. |
| keywords |
Artificial Intelligence, Design Data, Algorithmic Design, Design Process, Co-Designing |
| series |
eCAADe |
| email |
antony.pelosi@vuw.ac.nz |
| full text |
 file.pdf (544,841 bytes) |
| references |
Content-type: text/plain
|
| last changed |
2023/12/10 10:49 |
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