| id |
caadria2025_204 |
| authors |
Jayachandran, Surendar, McMeel, Dermott and Walker, Charles |
| year |
2025 |
| title |
Steal like an AI: AI and data privacy in architectural practice |
| source |
Dagmar Reinhardt, Christiane M. Herr, Anastasia Globa, Jielin Chen, Taro ?Narahara, Nicolas Rogeau (eds.), ARCHITECTURAL INFORMATICS - Proceedings of the 30th CAADRIA Conference, Tokyo, 22-29 March 2025, Volume 1, pp. 511–520 |
| summary |
Through a confluence of diverse disciplinary interests and trajectories, questions surrounding the materiality and implications of artificial intelligence (AI) for architecture have recently come into focus. This broad domain encompasses several overlapping areas of inquiry, necessitating careful differentiation of concerns. Historically, architectural visualisations serve to communicate or encode disciplinary expertise gained by humans through education and practical experience. However, in the age of AI this is no longer the case. Contemporary neural networks typically may be trained to extract data and visual images irrespective of any motivating ideas that underpin the particular architectonic or stylistic design decisions made by their original creators. This paper identifies and describes four distinct themes for conceptualizing AI, aiming to provide a typology for mapping current research streams and a shared language for analysis. By clarifying these frameworks, the paper contributes to a deeper understanding of how AI systems intersect with historical, organizational, ethical and ecological contexts of architectural practice. |
| keywords |
AI in Architectural Design, Data Privacy, Ethical Integration, AI & Style, Creativity |
| series |
CAADRIA |
| full text |
 file.pdf (335,479 bytes) |
| references |
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