DesignGPT para diseño industrial: Co-creación de productos en la era de la inteligencia artificial
Resumen
El presente estudio elaboró una reflexión crítica y argumentativa sobre este fenómeno recientemente emergente, DesignGPT, definido como la inclusión en la actividad del diseño industrial de inteligencia artificial generativa. Se elaboró una cartografía conceptual que exploraba cómo la IA había transformado el proceso creativo, la identidad del diseñador y propuesto nuevos enfoques de cocreación sostenidos entre humanos y algoritmos, con base en el análisis documental realizado mediante artículos científicos publicados entre 2016 y 2024. Se adopta un enfoque cualitativo, interpretativo y crítico, centrado en la documentación y el diálogo entre diferentes puntos de vista teóricos, dejando a un lado la forma de las metodologías empíricas o el análisis estadístico. Los resultados mostraron que la IA ayudó a ampliar el pensamiento divergente, a evitar la fijación creativa y a permitir una colaboración fluida que desafiaba los límites tradicionales de la autoría. Aparecieron tensiones éticas en forma de sesgo cultural, dispone incluso la necesidad de un marco inclusivo para el entrenamiento de los algoritmos. Estos resultados contienen ejemplos prácticos para ayudar a mejoras en la práctica del ideación por IA, particularmente en entornos del diseño profesional. Este estudio muestra una interpretación conceptual original que ayuda a reforzar la comprensión teórica del diseño algorítmico, como una práctica situada y simétrica.
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Referencias
Adeleye, I. O. (2024). The Impact of Artificial Intelligence on Design: Enhancing Creativity and Efficiency. Journal of Engineering and Applied Sciences, 3(1), 1. https://doi.org/10.70560/vvsfej12
Ahmadabadi, S. N., Haghifam, M., Shah‐Mansouri, V., & Ershadmanesh, S. (2024). Design and evaluation of crowdsourcing platforms based on users’ confidence judgments. Scientific Reports, 14(1). https://doi.org/10.1038/s41598-024-65892-7
Ai, J. (2025). The Integration Path of Innovative Design Thinking and Rural Development of Non- Heritage Cultural Creations in the Era of Artificial Intelligence.
Berni, A., Borgianni, Y., Rotini, F., Gonçalves, M., & Thoring, K. (2024). Stimulating design ideation with artificial intelligence: present and (short-term) future. Proceedings of the Design Society, 4, 1939. https://doi.org/10.1017/pds.2024.196
Boden, M. A. (2005). Aesthetics and interactive art. https://doi.org/10.1145/1056224.1056225
Burg, V. van der. (2022). Ceci n’est pas une chaise: Emerging practices in designer-AI collaboration. Proceedings of DRS. https://doi.org/10.21606/drs.2022.653
Camburn, B., He, Y., Raviselvam, S., Luo, J., & Wood, K. (2019). Evaluating Crowdsourced Design Concepts With Machine Learning.pdf.
Cautela, C., Mortati, M., Dell’Era, C., & Gastaldi, L. (2019). The impact of Artificial Intelligence on Design Thinking practice: Insights from the Ecosystem of Startups. Strategic Design Research Journal, 12(1). https://doi.org/10.4013/sdrj.2019.121.08
Chen, J.-F., Ni, C.-C., Lin, P.-H., & Lin, R. (2024). Designing the Future: A Case Study on Human-AI Co-Innovation. Creative Education, 15(3), 474. https://doi.org/10.4236/ce.2024.153028
Chen, L., Song, Y., Zheng, C., Jing, Q., Hansen, P., & Sun, L. (2025). Understanding Design Fixation in Generative AI. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2502.05870
Choi, D., Hong, S., Park, J., Chung, J. J. Y., & Kim, J. (2024). CreativeConnect: Supporting Reference Recombination for Graphic Design Ideation with Generative AI. 1. https://doi.org/10.1145/3613904.3642794
Chong, H., Ma, Q.-H., Lai, J. S., & Liao, X. X. (2025). Achieving Sustainable Construction Safety Management: The Shift from Compliance to Intelligence via BIM–AI Convergence. Sustainability, 17(10), 4454. https://doi.org/10.3390/su17104454
Cross, N. (2011). Design Thinking: Understanding How Designers Think and Work. http://ci.nii.ac.jp/ncid/BB06060968
Fang, Y.-M. (2024). The role of generative AI in industrial design: enhancing the design process and education. IET Conference Proceedings., 2023(45), 135. https://doi.org/10.1049/icp.2024.0303
Gong, Z., Paananen, S., Nurmela, P., Gonçalves, M., Georgiev, G. V., & Häkkilä, J. (2024). AI ROLE IN IDEATION FOR DESIGN CREATIVITY ENHANCEMENT.
Goucher-Lambert, K., & Cagan, J. (2019). Crowdsourcing inspiration: Using crowd generated inspirational stimuli to support designer ideation. Design Studies, 61, 1. https://doi.org/10.1016/j.destud.2019.01.001
Grant, M. J., & Booth, A. (2009). A typology of reviews: an analysis of 14 review types and associated methodologies [Review of A typology of reviews: an analysis of 14 review types and associated methodologies]. Health Information & Libraries Journal, 26(2), 91. Wiley. https://doi.org/10.1111/j.1471-1842.2009.00848.x
Han, J., Forbes, H., Shi, F., Hao, J. L., & Schaefer, D. (2020). A DATA-DRIVEN APPROACH FOR CREATIVE CONCEPT GENERATION AND EVALUATION. Proceedings of the Design Society DESIGN Conference, 1, 167. https://doi.org/10.1017/dsd.2020.5
HOLZNER, N., MAIER, S., & FEUERRIEGEL, S. (2025). Generative AI and Creativity: A Systematic Literature Review and Meta-Analysis.
Jordanous, A. (2012). A Standardised Procedure for Evaluating Creative Systems: Computational Creativity Evaluation Based on What it is to be Creative. Cognitive Computation, 4(3), 246. https://doi.org/10.1007/s12559-012-9156-1
Jordanous, A. (2013). Evaluating computational creativity: a standardised procedure for evaluating creative systems and its application. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.574929
Kim, J., & Maher, M. L. (2023). The effect of AI-based inspiration on human design ideation. International Journal of Design Creativity and Innovation, 11(2), 81. https://doi.org/10.1080/21650349.2023.2167124
Kotnik, T. (2010). Digital Architectural Design as Exploration of Computable Functions. International Journal of Architectural Computing, 8(1), 1. https://doi.org/10.1260/1478-0771.8.1.1
Kwon, J., Jung, E.-C., & Kim, J. (2024). Designer-Generative AI Ideation Process: Generating Images Aligned with Designer Intent in Early-Stage Concept Exploration in Product Design. Archives of Design Research, 37(3), 7. https://doi.org/10.15187/adr.2024.07.37.3.7
Liao, J., Hansen, P., & Chai, C. (2020). A framework of artificial intelligence augmented design support. Human-Computer Interaction, 35, 511. https://doi.org/10.1080/07370024.2020.1733576
Poleac, D. (2024). Design Thinking with AI. Proceedings of the ... International Conference on Business Excellence, 18(1), 2891. https://doi.org/10.2478/picbe-2024-0240
Ramesh, A., Kambhampati, C., Monson, J., & Drew, P. (2004). Artificial intelligence in medicine [Review of Artificial intelligence in medicine]. Annals of The Royal College of Surgeons of England, 86(5), 334. Royal College of Surgeons of England. https://doi.org/10.1308/147870804290
Reyes, C. E. G., & Cruz, E. C. (2021). Modelo TIC-PD: Descriptores de competencias digitales para la práctica docente. Transdigital, 2(4). https://doi.org/10.56162/transdigital78
Rezwana, J., & Maher, M. L. (2022). Designing Creative AI Partners with COFI: A Framework for Modeling Interaction in Human-AI Co-Creative Systems. ACM Transactions on Computer-Human Interaction, 30(5), 1. https://doi.org/10.1145/3519026
Saeki, N., & Papalambros, P. Y. (2014). Human-Computer Interaction for Part Selection in Product Design. 106. https://doi.org/10.3850/978-981-09-1348-9_021
Shi, Y., Gao, T., Jiao, X., & Cao, N. (2023). Understanding Design Collaboration Between Designers and Artificial Intelligence: A Systematic Literature Review. Proceedings of the ACM on Human-Computer Interaction, 7, 1. https://doi.org/10.1145/3610217
Shinde, N. K., Gulve, O. M., & Magar, R. S. (2025). Revolutionizing Design: The Role of Generative AI in the Creative Process. https://philarchive.org/rec/OMKRDT
Song, B., Zhu, Q., & Luo, J. (2024). Human-AI collaboration by design. Proceedings of the Design Society, 4, 2247. https://doi.org/10.1017/pds.2024.227
Tang, X., Windham, J., & Bush, B. (2024). Pre-AI and post-AI design: balancing human Creativity and AI Tools in the Industrial Design Process. 100. https://doi.org/10.1145/3708394.3708413
Wadinambiarachchi, S., Kelly, R., Pareek, S., Zhou, Q., & Velloso, E. (2024). The Effects of Generative AI on Design Fixation and Divergent Thinking. 1. https://doi.org/10.1145/3613904.3642919
Wang, W.-F., Lu, C.-T., Campanyà, N. P. i, Chen, B., & Chen, M. Y. (2025). AIdeation: Designing a Human-AI Collaborative Ideation System for Concept Designers. 1. https://doi.org/10.1145/3706598.3714148
Weller, A. J. (2019). Design Thinking for a User-Centered Approach to Artificial Intelligence. She Ji, 5(4), 394. https://doi.org/10.1016/j.sheji.2019.11.015
Yu, W. F. (2025). AI as a co-creator and a design material: Transforming the design process. Design Studies, 97, 101303. https://doi.org/10.1016/j.destud.2025.101303
DOI: https://doi.org/10.23857/pc.v10i6.9851
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