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Inspiration or indication? Evaluating the qualities of design inspiration boards created using text to image generative AI

Published online by Cambridge University Press:  16 May 2024

Charlie Ranscombe ,
Linus Tan ,
Mark Goudswaard  and
Chris Snider
Charlie Ranscombe*
Affiliation:
Swinburne University of Technology, Australia
Linus Tan
Affiliation:
Swinburne University of Technology, Australia
Mark Goudswaard
Affiliation:
University of Bristol, United Kingdom
Chris Snider
Affiliation:
University of Bristol, United Kingdom
*
cranscombe@swin.edu.au

Abstract

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This study explores the application of image generative AI to support design process by creating inspiration boards. Through an evaluative study, we compare the diversity, quantity, fidelity, and ambiguity of boards generated by image generative AI and traditional methods. The results highlight how generative AI produces a quantity of images, it exhibits limited diversity compared to traditional methods. This suggests a tendency for supporting interpolation rather than extrapolation of ideas, in turn providing insights on best practice and into the optimal stage for its application.

Keywords

inspiration boardsartificial intelligence (AI)design creativityindustrial designvisualisation

Information

Type
Artificial Intelligence and Data-Driven Design
Information
Proceedings of the Design Society , Volume 4: DESIGN 2024 , May 2024 , pp. 2207 - 2216
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

Bresciani, S. (2019) “Visual design thinking: A collaborative dimensions framework to profile visualisations”, Design Studies, 63, 92–124. https://doi.org/10.1016/j.destud.2019.04.001.CrossRefGoogle Scholar
Brisco, R., Hay, L. and Dhami, S. (2023) “Exploring the role of text-to-image AI in concept generation”, Proceedings of the Design Society, 3, 1835–1844. https://doi.org/10.1017/pds.2023.184.CrossRefGoogle Scholar
Brown, Z. and Tiggemann, M. (2016) “Attractive celebrity and peer images on Instagram: Effect on women's mood and body image”, Body image, 19, 37–43. https://doi.org/10.1016/j.bodyim.2016.08.007.CrossRefGoogle ScholarPubMed
Cardoso, C. and Badke-Schaub, P. (2011) “The influence of different pictorial representations during idea generation”, The Journal of Creative Behavior, 45(2), 130–146. https://doi.org/10.1002/j.2162-6057.2011.tb01092.x.Google Scholar
Cheng, P., Mugge, R. and Schoormans, J.P. (2014) “A new strategy to reduce design fixation: Presenting partial photographs to designers”, Design Studies, 35(4), 374–391. https://doi.org/10.1016/j.destud.2014.02.004.CrossRefGoogle Scholar
Fu, K., Chan, J., Cagan, J., Kotovsky, K., Schunn, C. and Wood, K. (2013) “The meaning of “near” and “far”: the impact of structuring design databases and the effect of distance of analogy on design output”, Journal of Mechanical Design, 135(2), 7–21. https://doi.org/10.1115/1.4023158.CrossRefGoogle Scholar
Goldschmidt, G. and Smolkov, M. (2006) “Variances in the impact of visual stimuli on design problem solving performance”, Design Studies, 27(5), 549–569. https://doi.org/10.1016/j.destud.2006.01.002.Google Scholar
Gonçalves, M., Cardoso, C. and Badke-Schaub, P. (2012) “Find your inspiration: exploring different levels of abstraction in textual stimuli”, in DS 73-1 Proceedings of the 2nd International Conference on Design Creativity Volume 1.Google Scholar
Koch, J. (2017) “Design implications for Designing with a Collaborative AI”, in 2017 AAAI Spring symposium series.Google Scholar
Kuys, B., Ranscombe, C. and Zhang, W. (2023) “Visualising product concepts to engage manufacturers with little or no industrial design capability”, Design Studies, 87, 101–188. https://doi.org/10.1016/j.destud.2023.Google Scholar
McComb, C., Boatwright, P. and Cagan, J. (2023) “Focus and Modality: Defining a Roadmap to Future AI-Human Teaming in Design”, Proceedings of the Design Society, 3, 1905–1914. https://doi.org/10.1017/pds.2023.191.CrossRefGoogle Scholar
Mikkonen, J. (2023) “Advent of GAN—How does a generative AI create a moodboard?”. https://doi.org/10.21606/nordes.2023.114.CrossRefGoogle Scholar
Ranscombe, C., Bissett-Johnson, K., Mathias, D., Eisenbart, B. and Hicks, B. (2020) “Designing with LEGO: exploring low fidelity visualization as a trigger for student behavior change toward idea fluency”, International Journal of Technology and Design Education, 30(2), 367–388. https://doi.org/10.1007/s10798-019-09502-y.CrossRefGoogle Scholar
Self, J.A. (2019) “Communication through design sketches: Implications for stakeholder interpretation during concept design”, Design Studies, 63, 1–36. https://doi.org/10.1016/j.destud.2019.02.003.CrossRefGoogle Scholar
Thoring, K., Huettemann, S. and Mueller, R.M. (2023) “The Augmented Designer: A Research Agenda for Generative AI-Enabled Design”, Proceedings of the Design Society, 3, 3345–3354. https://doi.org/10.1017/pds.2023.335.CrossRefGoogle Scholar
Vasconcelos, L.A. and Crilly, N. (2016) “Inspiration and fixation: Questions, methods, findings, and challenges”, Design Studies, 42, 1–32. https://doi.org/10.1016/j.destud.2015.11.001.CrossRefGoogle Scholar
Velasquez-Posada, A.M. (2019) “How to be Systematic with Mood Boards?”, in 2019 IEEE Frontiers in Education Conference (FIE), IEEE, 1–4. https://doi.org/10.1109/FIE43999.2019.9028383.CrossRefGoogle Scholar
Viswanathan, V., Atilola, O., Esposito, N. and Linsey, J. (2014) “A study on the role of physical models in the mitigation of design fixation”, Journal of Engineering Design, 25(1-3), 25–43. https://doi.org/10.1080/09544828.2014.885934.CrossRefGoogle Scholar