Hostname: page-component-54dcc4c588-2ptsp Total loading time: 0 Render date: 2025-09-23T12:25:35.593Z Has data issue: false hasContentIssue false
  • English
  • Français

Stimulating design ideation with artificial intelligence: present and (short-term) future

Published online by Cambridge University Press:  16 May 2024

Aurora Berni ,
Yuri Borgianni ,
Federico Rotini ,
Milene Gonçalves  and
Katja Thoring
Aurora Berni
Affiliation:
Free University of Bozen|Bolzano, Italy
Yuri Borgianni*
Affiliation:
Free University of Bozen|Bolzano, Italy
Federico Rotini
Affiliation:
University of Florence, Italy
Milene Gonçalves
Affiliation:
Delft University of Technology, The Netherlands
Katja Thoring
Affiliation:
Technical University of Munich, Germany
*
yuri.borgianni@unibz.it

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The role of Artificial Intelligence (AI) in design is clearly growing. One of the tenets of the paper is that stimulation could be among the design processes mostly benefitting from the introduction of AI. Available contributions have been reviewed to understand the current support AI can give in design inspiration and ideation. We also reflected on what AI should and ahould not do in the future: a framework is proposed. Based on the reviewed contributions, in no case, AI is seen as a substitute of designers. Most contributions originate from the IT domain and have a demonstrative purpose.

Keywords

design processartificial intelligence (AI)human behaviourinspirationreview

Information

Type
Artificial Intelligence and Data-Driven Design
Information
Proceedings of the Design Society , Volume 4: DESIGN 2024 , May 2024 , pp. 1939 - 1948
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2024.

References

Blandino, G., Montagna, F., Cantamessa, M., & Colombo, S. (2023), "A comparative review on the role of stimuli in idea generation", AI EDAM, Vol. 37, e19. https://doi.org/10.1017/S0890060423000124Google Scholar
Borgianni, Y., & Maccioni, L. (2020), "Review of the use of neurophysiological and biometric measures in experimental design research", AI EDAM, Vol. 34, No. 2, pp. 248-285. https://doi.org/10.1017/S0890060420000062Google Scholar
Borgianni, Y., Maccioni, L., Fiorineschi, L., & Rotini, F. (2020), "Forms of stimuli and their effects on idea generation in terms of creativity metrics and non-obviousness" International Journal of Design Creativity and Innovation, Vol. 8 No. 3, pp. 147-164. https://doi.org/10.1080/21650349.2020.1766379CrossRefGoogle Scholar
Chen, L., Wang, P., Dong, H., Shi, F., Han, J., Guo, Y., & Wu, …, C. (2019), "An artificial intelligence based data-driven approach for design ideation", Journal of Visual Communication and Image Representation, Vol. 61, pp. 10-22. https://doi.org/10.1016/j.jvcir.2019.02.009CrossRefGoogle Scholar
Crilly, N., & Cardoso, C. (2017), "Where next for research on fixation, inspiration and creativity in design?", Design Studies, Vol., 50, pp. 1-38. https://doi.org/10.1016/j.destud.2017.02.001CrossRefGoogle Scholar
Csikszentmihalyi, M. (1997), "Low and the psychology of discovery and invention", Harper Perennial, New York, Vol. 39.Google Scholar
Debowski, N., Tavanapour, N., & Bittner, E. A. (2022), "Prototyping a Conversational Agent for AI-Supported Ideation in Organizational Creativity Processes", In HICSS, pp. 1-10Google Scholar
Dorta, T., Kinayoglu, G., & Boudhraâ, S. (2016), "A new representational ecosystem for design teaching in the studio", Design Studies, Vol. 47, pp. 164-186. https://doi.org/10.1016/j.destud.2016.09.003CrossRefGoogle Scholar
Duan, Y., & Zhang, J. (2022), "A Novel AI-Based Visual Stimuli Generation Approach for Environment Concept Design", Computational Intelligence and Neuroscience, Vol. 2022, pp. 8015492. https://doi.org/10.1155/2022/8015492CrossRefGoogle ScholarPubMed
Fink, A., Grabner, R. H., Gebauer, D., Reishofer, G., Koschutnig, K., & Ebner, F. (2010), "Enhancing creativity by means of cognitive stimulation: Evidence from an fMRI study", NeuroImage, Vol. 52 No. 4, pp. 1687-1695. https://doi.org/10.1016/j.neuroimage.2010.05.072CrossRefGoogle ScholarPubMed
Gonçalves, M., Cardoso, C., & Badke-Schaub, P. (2013), "Inspiration peak: Exploring the semantic distance between design problem and textual inspirational stimuli", International Journal of Design Creativity and Innovation, Vol. 1 No. 4, pp. 215-232. https://doi.org/10.1080/21650349.2013.799309CrossRefGoogle Scholar
Gonçalves, M., Cardoso, C., & Badke-Schaub, P. (2014), "What inspires designers? Preferences on inspirational approaches during idea generation", Design Studies, Vol. 35 No. 1, pp. 29-53. https://doi.org/10.1155/2022/8015492CrossRefGoogle Scholar
Gonçalves, M., Cardoso, C., & Badke-Schaub, P. (2016), "Inspiration choices that matter: the selection of external stimuli during ideation", Design Science, Vol. 2, pp. e10. https://doi.org/10.1017/dsj.2016.10CrossRefGoogle Scholar
Gonçalves, M. & Cash, P. (2021), "The life cycle of creative ideas: towards a dual-process theory of ideation", Design Studies, Vol. 72, No. 100988. https://doi.org/10.1016/j.destud.2020.100988CrossRefGoogle Scholar
Jin, X., Evans, M., Dong, H., & Yao, A. (2021), "Design heuristics for artificial intelligence: inspirational design stimuli for supporting UX designers in generating AI-powered ideas", In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, pp. 1-8. https://doi.org/10.1145/3411763.3451727CrossRefGoogle Scholar
Kim, J., & Maher, M. L. (2023), "The effect of AI-based inspiration on human design ideation", International Journal of Design Creativity and Innovation, Vol. 11 No. 2, pp. 81-98. https://doi.org/10.1080/21650349.2023.2167124CrossRefGoogle Scholar
Kim, J., Maher, M. L., & Siddiqui, S. (2021), "Collaborative Ideation Partner: Design Ideation in Human-AI Co-creativity", In CHIRA, pp. 123-130. https://doi.org/10.5220/0010640800003060CrossRefGoogle Scholar
Knops, R., Şerban, B., & Houben, S. (2023), "Human-human collaboration enhanced with emerging technologies of AI", In CHI'23: Workshop on Integrating AI in Human-Human Collaborative Ideation.Google Scholar
Koch, J., Taffin, N., Beaudouin-Lafon, M., Laine, M., Lucero, A., & Mackay, W. E. (2020), "Imagesense: An intelligent collaborative ideation tool to support diverse human-computer partnerships", Proceedings of the ACM on human-computer interaction, Vol. 45, pp. 1-27. https://doi.org/10.1145/3392850CrossRefGoogle Scholar
Kronqvist, A., & Rousi, R. (2023), "A quick review of ethics, design thinking, gender, and AI development", International Journal of Design Creativity and Innovation, Vol. 11 No.1, pp. 62-79. https://doi.org/10.1080/21650349.2022.2136762CrossRefGoogle Scholar
Kwon, E., Rao, V., & Goucher-Lambert, K. (2023), "Understanding inspiration: Insights into how designers discover inspirational stimuli using an AI-enabled platform", Design Studies, Vol. 88, pp. 101202. https://doi.org/10.1016/j.destud.2023.101202.CrossRefGoogle Scholar
Lee, YH., Chiu, CY. (2023), "The Impact of AI Text-to-Image Generator on Product Styling Design", In: Mori, H., Asahi, Y. (eds) Human Interface and the Management of Information. HCII 2023. Lecture Notes in Computer Science, Vol. 14015. Springer, Cham. https://doi.org/10.1007/978-3-031-35132-7_38Google Scholar
Li, X., Su, J., Zhang, Z., & Bai, R. (2021), "Product innovation concept generation based on deep learning and Kansei engineering", Journal of Engineering Design, Vol. 32 No. 10, pp. 559-589. https://doi.org/10.1080/09544828.2021.1928023CrossRefGoogle Scholar
Liao, J., Hansen, P., & Chai, C. (2020), "A framework of artificial intelligence augmented design support", Human–Computer Interaction, Vol. 35 No. 5-6, pp. 511-544. https://doi.org/10.1080/07370024.2020.1733576CrossRefGoogle Scholar
Loi, D., Wolf, C., Blomberg, J., Arar, R., & Brereton, M. (2019), "Co-designing AI Futures: Integrating AI ethics, social computing and design", In Companion Publication of the 2019 on Designing Interactive Systems Conference 2019 Companion (DIS '19 Companion). Association for Computing Machinery, New York, NY, USA, pp. 381–384. https://doi.org/10.1145/3301019.3320000CrossRefGoogle Scholar
Maier, T., Soria Zurita, N. F., Starkey, E., Spillane, D., Menold, J., & McComb, C. (2020), "Analyzing the characteristics of cognitive-assistant-facilitated ideation groups", In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Vol. 83976, pp. V008T08A046. American Society of Mechanical Engineers. https://doi.org/10.1115/DETC2020-22555CrossRefGoogle Scholar
O'Halloran, B. M., Hoyle, C., Tumer, I. Y., & Stone, R. B. (2019), "The Early Design Reliability Prediction Method", Proceedings of the ASME 2012 International Mechanical Engineering Congress and Exposition. Vol. 3: Design, Materials and Manufacturing, Parts A, B, and C. Houston, Texas, USA. November 9–15, 2012. pp. 1765-1776. ASME. https://doi.org/10.1115/IMECE2012-89592CrossRefGoogle Scholar
Paananen, V., Oppenlaender, J., & Visuri, A. (2023), "Using Text-to-Image Generation for Architectural Design Ideation", arXiv preprint arXiv:2304.10182. https://doi.org/10.48550/arXiv.2304.10182CrossRefGoogle Scholar
Pena, M. L. C., Carballal, A., Rodríguez-Fernández, N., Santos, I., & Romero, J. (2021), "Artificial intelligence applied to conceptual design. A review of its use in architecture", Automation in Construction, Vol. 124, pp. 103550. https://doi.org/10.1016/j.autcon.2021.103550.CrossRefGoogle Scholar
Popescu, A., and Schut, A. (2023), "Generative AI in creative design processes: a dive into possible cognitive biases", in De Sainz Molestina, D., Galluzzo, L., Rizzo, F., Spallazzo, D. (eds.), IASDR 2023: Life-Changing Design, pp. 9-13 October, Milan, Italy. https://doi.org/10.21606/iasdr.2023.784Google Scholar
Sarica, S., Song, B., Luo, J., & Wood, K. L. (2021), "Idea generation with technology semantic network" AI EDAM, Vol. 35 No. 3, pp. 265-283. https://doi.org/10.1017/S0890060421000020Google Scholar
Shneiderman, B. (2020), "Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy", International Journal of Human-Computer Interaction, Vol 36 No. 6, pp. 495-504. https://doi.org/10.1080/10447318.2020.1741118CrossRefGoogle Scholar
Singh, D., Rajcic, N., Colton, S., & McCormack, J. (2019), "Camera obscurer: generative art for design inspiration", In Computational Intelligence in Music, Sound, Art and Design: 8th International Conference, EvoMUSART 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019, Vol. 8, pp. 51-68. Springer International Publishing. https://doi.org/10.1007/978-3-030-16667-0_4CrossRefGoogle Scholar
Sun, Y, & Münster, S. (2018), "A look at the research on design idea generation in industrial design: Literature review from 2003 to 2017", Proceedings of the Fifth International Conference on Design Creativity, Bath, UK, 31 January - 2 February 2018, pp. 31-38Google Scholar
Tang, Y. C., Huang, J. J., Yao, M. T., Wei, J., Li, W., He, Y. X., & Li, Z. J. (2019), "A review of design intelligence: progress, problems, and challenges", Frontiers of Information Technology & Electronic Engineering, Vol. 20 No.12, pp. 1595-1617. https://doi.org/10.1631/FITEE.1900398CrossRefGoogle Scholar
Thoring, K., Huettemann, S., & Mueller, R. M. (2023), "The augmented designer: a research agenda for generative AI-enabled design", Proceedings of the Design Society, Vol. 3, pp. 3345-3354. https://doi.org/10.1017/pds.2023.335CrossRefGoogle Scholar
Verganti, R., Vendraminelli, L., & Iansiti, M. (2020), "Innovation and design in the age of artificial intelligence", Journal of Product Innovation Management, Vol. 37 No. 3, pp. 212-227. https://doi.org/10.1111/jpim.12523CrossRefGoogle Scholar
Wahl, J., Hutter, K., & Füller, J. (2022), "How AI-supported searches through other perspectives affect ideation outcomes" International Journal of Innovation Management, Vol. 26 No. 09, pp. 2240028. https://doi.org/10.1142/S136391962240028XCrossRefGoogle Scholar
Wan, Q., & Lu, Z. (2023), "GANCollage: A GAN-Driven Digital Mood Board to Facilitate Ideation in Creativity Support", In Proceedings of the 2023 ACM Designing Interactive Systems Conference, pp. 136-146. https://doi.org/10.1145/3563657.3596072CrossRefGoogle Scholar
Wang, D., & Han, J. (2023), "Exploring the impact of generative stimuli on the creativity of designers in combinational design", Proceedings of the Design Society, Vol. 3, pp. 1805-1814. https://doi.org/10.1017/pds.2023.181CrossRefGoogle Scholar
Yüksel, N., Börklü, H. R., Sezer, H. K., & Canyurt, O. E. (2023), "Review of artificial intelligence applications in engineering design perspective", Engineering Applications of Artificial Intelligence, Vol. 118, pp. 105697. https://doi.org/10.1016/j.engappai.2022.105697CrossRefGoogle Scholar
Yun, G., Cho, K., Jeong, Y., and Nam, T. (2022), "Ideasquares: Utilizing generative text as a source of design inspiration", in Lockton, D., Lenzi, S., Hekkert, P., Oak, A., Sádaba, J., Lloyd, P. (eds.), DRS2022 Bilbao, 25 June - 3 July, Bilbao, Spain. https://doi.org/10.1016/j.engappai.2022.105697CrossRefGoogle Scholar
Zhao, T., Yang, J., Zhang, H., & Siu, K. W. M. (2021), "Creative idea generation method based on deep learning technology", International Journal of Technology and Design Education, Vol. 31, pp. 421-440. https://doi.org/10.1007/s10798-019-09556-yCrossRefGoogle Scholar
Zhou, C., Chai, C., Liao, J., Chen, Z., & Shi, J. (2020), "Artificial intelligence augmented design iteration support", In 2020 13th International Symposium on Computational Intelligence and Design (ISCID), pp. 354-358. IEEE. https://doi.org/10.1109/ISCID51228.2020.00086CrossRefGoogle Scholar
Zhu, Q., & Luo, J. (2022), "Generative design ideation: a natural language generation approach", In International Conference on-Design Computing and Cognition, Cham: Springer International Publishing, pp. 39-50. https://doi.org/10.1007/978-3-031-20418-0_3CrossRefGoogle Scholar