Materia sensibile
Colore, materiali e finiture nell’era dell’AI: dalla generazione visiva alla sensibilità progettuale
Parole chiave:
Intelligenza Artificiale generativa, CMF, Sensibilità progettuale aumentata, Cultura materiale, Co-progettazione uomo–AI
Abstract
L’articolo indaga come l’Intelligenza Artificiale generativa trasformi la progettazione di colore, materiali e finiture (CMF). Attraverso un approccio qualitativo-esplorativo, analizza le possibilità della generazione visiva e lo scarto tra la plausibilità dell’immagine e la realtà materica. Emerge uno spostamento del valore progettuale dalla produzione di alternative alla loro selezione e verifica critica. La ricerca propone il concetto di sensibilità progettuale aumentata, in cui l’esplorazione algoritmica si integra con le competenze percettive, tecniche e culturali del designer.
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- Chen, L., Song, Y., Guo, J., Sun, L., Childs, P., & Yin, Y. (2025). How generative AI supports human in conceptual design. Design Science, 11, e9.
- Di Dio, S., Inzerillo, B., Monterosso, F., Morvillo, S., & Russo, D. (2024). Artificial intelligence and design: Innovation, practical applications, and future creative horizons. Human Factors in Design, Engineering, and Computing, 159, 44–52. DOI: 10.54941/ahfe1005566.
- Doshi, A. R., & Hauser, O. P. (2024). Generative AI enhances individual creativity but reduces the collective diversity of novel content. Science Advances, 10(28), eadn5290. DOI: 10.1126/sciadv.adn5290.
- Ge, W., & Hou, G. (2025). The effects of generative AI model type and visual stimuli type on design creativity. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 39, e17. DOI: 10.1017/S0890060425100061.
- Li, B., Hu, Z., Liu, Y., & Wang, Z. (2025). Integrating Kansei engineering and AI-generated image for commercial vehicle body morphology design. Symmetry, 17(11), 1971. DOI: 10.3390/sym17111971.
- Rapp, A., Di Lodovico, C., Torrielli, F., & Di Caro, L. (2025). How do people experience the images created by generative artificial intelligence? An exploration of people’s perceptions, appraisals, and emotions related to a Gen-AI text-to-image model and its creations. International Journal of Human-Computer Studies, 193, 103375. DOI: 10.1016/j.ijhcs.2024.103375.
- Rizzi, G., & Bertola, P. (2025). Exploring the generative AI potential in the fashion design process: An experimental experience on the collaboration between fashion design practitioners and generative AI tools. European Journal of Cultural Management and Policy, 15, 13875. DOI: 10.3389/ejcmp.2025.13875.
- Sattele, V. (2025a). Creative dialogue: Evolving intent in designer-AI workflows. In Creativity and Cognition (C&C ’25) (pp. 39–44). Association for Computing Machinery. DOI: 10.1145/3698061.3734419.
- Sattele, V., & Ortiz, J. C. (2025b). AI as an element to overcome creative fixation in design teams. Proceedings of the Design Society, 5, 409–418. DOI: 10.1017/pds.2025.10055.
- Singh, S., Hindriks, K., Heylen, D., & Baraka, K. (2025). A systematic review of human-AI co-creativity. arXiv. DOI: 10.48550/arXiv.2506.21333.
- Su, J., Zhang, Y., & Zhu, J. (2025). Generative CMF design of wood grain decorative paper for custom furniture. In Proceedings of the 2025 International Conference on Artificial Intelligence and Product Design (AIPD 2025). Association for Computing Machinery. DOI: 10.1145/3765416.3765443.
- Torricelli, M., Martino, M., Baronchelli, A., & Aiello, L. M. (2024). The role of interface design on prompt-mediated creativity in generative AI. In Proceedings of the ACM Web Science Conference 2024. Association for Computing Machinery. DOI: 10.1145/3614419.3644000.
- Vo, K. H. T. (2025). “Who” designs better? A competition among human, artificial intelligence and human–AI collaboration. Design Science, 11, e29. DOI: 10.1017/dsj.2025.10029.
- Wang, N., Kim, H., Peng, J., & Wang, J. (2025). Exploring creativity in human–AI co-creation: A comparative study across design experience. Frontiers in Computer Science, 7, 1672735. DOI: 10.3389/fcomp.2025.1672735.
- Wang, P., Khinvasara, Y., Creijghton, G. J., Scholing, T., Wang, Y., Zhou, Z., Childs, P. R. N., & Yin, Y. (2025). Enhancing designer creativity through human–AI co-ideation: A co-creation framework for design ideation with custom GPT. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 39, e22. DOI: 10.1017/S0890060425100127.
- Ye, R., Varona, M., Huang, O., Lee, P. Y. K., Liut, M., & Nobre, C. (2025). The design space of recent AI-assisted research tools for ideation, sensemaking, and scientific creativity. arXiv. DOI: 10.48550/arXiv.2502.16291.
- Zhou, E., & Lee, D. (2024). Generative artificial intelligence, human creativity, and art. PNAS Nexus, 3(3), pgae052. DOI: 10.1093/pnasnexus/pgae052.
- Zhu, Q., & Luo, J. (2025). Artificial creativity in design: A theory-based framework for implementation. Proceedings of the Design Society, 5, 621–630. DOI: 10.1017/pds.2025.100765.
Pubblicato
2026-06-30
Come citare
Alfarano, G. (2026). Materia sensibile: Colore, materiali e finiture nell’era dell’AI: dalla generazione visiva alla sensibilità progettuale. AND Rivista Di Architetture, Città E Architetti, 49(1), 10-23. Recuperato da https://and-architettura.it/index.php/and/article/view/705
Sezione
Articoli
Copyright (c) 2026 Autore/i
TQuesto lavoro è fornito con la licenza Creative Commons Attribuzione 4.0 Internazionale.
