Design talks
Variation, control, and operational reintegration in artificial intelligence workflows
Keywords:
Generative artificial intelligence, Architectural design process, Back talk, Design agency, Operational reintegration
Abstract
In architectural design, the response of a tool is never neutral: it interferes with the formulation of the problem, guides decision-making, and redefines the course of action. With generative artificial intelligence, this relationship takes on an unprecedented form. Drawing on Schön’s concept of back talk, this contribution analyses six documented workflows to investigate the threshold at which an output ceases to be a visual suggestion and acquires operational relevance. The aim is to clarify how variation, control, and reintegration redefine the role of the designer in AI-mediated processes.
References
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- Chaillou, S. (2022). Artificial intelligence and architecture: From research to practice. Birkhäuser.
- Cross, N. (2006). Designerly ways of knowing. Springer. https://doi.org/10.1007/1-84628-301-9
- del Campo, M. (2021). Architecture, language and AI: Language, attentional generative adversarial networks (AttnGAN) and architecture design. In A. Globa, J. van Ameijde, A. Fingrut, N. Kim, & T. T. S. Lo (Eds.), Projections: Proceedings of the 26th CAADRIA Conference (Vol. 1, pp. 211–220). The Association for Computer-Aided Architectural Design Research in Asia. https://doi.org/10.52842/conf.caadria.2021.1.211
- Goldschmidt, G. (1991). The dialectics of sketching. Creativity Research Journal, 4(2), 123–143. https://doi.org/10.1080/10400419109534381
- Koh, I. (2022). Architectural plasticity: The aesthetics of neural sampling. Architectural Design, 92(3), 86–93. https://doi.org/10.1002/ad.2818
- Lawson, B. (2006). How designers think: The design process demystified (4th ed.). Architectural Press. https://doi.org/10.4324/9780080454979
- Li, C., Zhang, T., Du, X., Zhang, Y., & Xie, H. (2025). Generative AI models for different steps in architectural design: A literature review. Frontiers of Architectural Research, 14(3), 759–783. https://doi.org/10.1016/j.foar.2024.10.001
- Li, P., Li, B., & Li, Z. (2023). Sketch-to-architecture: Generative AI-aided architectural design. In R. Chaine, Z. Deng, & M. H. Kim (Eds.), Pacific Graphics Short Papers and Posters (pp. 99–102). The Eurographics Association. https://doi.org/10.2312/pg.20231276
- Prix, W., Schmidbaur, K., Bolojan, D., & Baseta, E. (2022). The legacy sketch machine: From artificial to architectural intelligence. Architectural Design, 92(3), 14–21. https://doi.org/10.1002/ad.2808
- Schön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books.
- SPAN. (2020). Peaches & Plums. https://span-arch.org/peaches-plums/.
- Suárez, V. E. (2023, June 30). Controlled creativity: Empowering architectural design with AI diffusion. IAAC Blog. https://blog.iaac.net/controlled-creativity/
Published
2026-06-30
How to Cite
Berardi, V., Colapinto, D., & Parisi, N. (2026). Design talks: Variation, control, and operational reintegration in artificial intelligence workflows. AND Journal of Architecture, Cities and Architects, 49(1), 24-29. Retrieved from https://www.and-architettura.it/index.php/and/article/view/706
Section
Articles
Copyright (c) 2026 Author(s)
This work is licensed under a Creative Commons Attribution 4.0 International License.
