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Research study
We are seeking participants for our research study that investigates the ways practicing designers use Generative AI (GenAI) tools in their creative design process and how use changes over two months.
We are seeking participants for our research study that investigates the ways practicing designers use Generative AI (GenAI) tools in their creative design process and how use changes over two months.
What is this study about?
What is this study about?
This study aims to contribute to the understanding of how the creative design process changes with the adoption of new technology, such as GenAI. The use of GenAI to assist human creativity in the realm of design has the potential to directly affect the design process due to the synergies and tensions emerging through the shared objective of designer and tool to create.
The quality of design solutions may be impacted positively or negatively as these tools are applied to design tasks in practice. While positive impacts, such as time efficiency or ideation expansion, may enhance innovation; negative impacts, such as hollow outputs or bias amplification, may hinder innovation.
The rate of GenAI adoption means these impacts may not be understood before GenAI is embedded in design methods, thereby altering the design process in ways that are not necessarily intentional or optimal. This study seeks to contribute to the intentional integration of these powerful new tools so design practitioners might harness GenAI's capabilities in ways that align with their goals and values. It also aims to advance the crucial role the design research community can play in supporting this effort by contributing a novel study that explores the impact of GenAI on the design process in practice. In turn, this will help inform future directions for the professional development and learning of designers to support such change. Thus, through collaboration, the design community can ensure the potential impact of GenAI may be considered thoughtfully, benefiting both practitioners, researchers, and the broader design field.
Why participate?
Why participate?
Your assistance in completing the study will help contribute to the collective design practitioner and design research communities' understanding of the impact of GenAI on the design process of designers in practice. The rapid adoption of Generative AI (GenAI) suggests that changes to the design process might become entrenched before they are fully understood, potentially leading to unintentional shifts in how designers work. This study aims to provide insights into these potential shifts, to empower the design practitioner to make informed, deliberate choices about how to incorporate GenAI and enable the design research community to support this.
The insights gained from research on the ways GenAI tools are changing the design process can help inform educational resources and guidelines to help designers adopt GenAI in ways that enhance their work while maintaining control over the creative process. If you are using GenAI, this may be valuable to you, so we encourage you to participate. But please note that participation is completely voluntary. Declining to participate, or stopping participation once you have started will in no way impact your relationship with The University of Sydney.
To show our appreciation for completing the interview and survey, you will go into a draw to win an AUD$100 gift card.
What are the study's core concepts?
What are the study's core concepts?
GenAI tools
GenAI is a broad term that is used for any AI system whose primary function is to generate content (e.g., text and images). In this study, we consider GenAI tools that are publicly available and used for design. This includes standalone (e.g., ChatGPT or Midjourney) and integrated AI tools such as those in design software (e.g., Autodesk Fusion 360) or in design platforms (e.g., Adobe Firefly). Consideration of these allows us to comprehensively examine GenAI application in creative design tasks.
Creative design
Design tasks range from routine, which are repetitive and predictable (e.g., data entry or file organisation) to creative, which are original and diverse (e.g., product conceptualisation or visual storytelling) [1]. While routine tasks are well-defined, making them suitable for machine execution [2], creative tasks typically demand innovative thought and involve the development of distinctive solutions [3], which results in ideas or products that are novel and useful [4]. The engagement of creativity is thought to be a distinctly human capability, which AI-powered tools have some potential to alter [5],[6].
Design process
The Design Council's Double Diamond is a widely recognised design process model [5],[7],[8],[9]. It consists of four phases: Discover (problem exploration), Define (problem definition), Develop (solution exploration), and Deliver (solution delivery). This model conceptualises the design process as iterative and dynamic, moving between divergent (broad exploration of possibilities) and convergent (specific focus on objectives) modes of thinking, which are engaged during the creative response to a design challenge.
Project summary and research questions
Project summary and research questions
This research project investigates how designers practising in Australia utilise general-use Generative AI (GenAI) tools (e.g., Midjourney, ChatGPT, Autodesk Fusion 360) in their design process for creative design tasks. A mixed-method case study will be conducted with practicing designers who currently utilise GenAI tools for creative design work. In-depth interviews and longitudinal experience sampling will be used to explore how these designers utilise GenAI tools in their design process for creating design solutions. Through thematic analysis of empirical data using a design process framework derived from synthesised research, the study aims to: (1) provide valuable insights for practitioners and researchers by capturing evolving GenAI usage patterns for design tasks, (2) refine a design process framework that highlights GenAI use in methods that enhance design outcomes, and (3) suggest implications for design practitioners' professional development and learning, based on real-time experiences and behavioural trends.
Research aims and questions
This research project aims to address the gap in understanding how GenAI tools are applied in the design process of practicing designers. It will investigate GenAI use through the lens of divergent and convergent thinking that occurs during the design process and the activities and methods that facilitate this. It will concentrate on the examination of primary data and triangulate this using mixed methods to address three research questions:
(RQ1) How is GenAI used in the creative design process of practicing designers?
(RQ2) How is the way practicing designers use GenAI in the creative design process changing over time?
(RQ3) Considering the integration of Generative AI (GenAI) in the creative design process, what implications do this study's findings have for designer professional development and learning?
[1] Howard, T. J., Culley, S. J., & Dekoninck, E. (2008). Describing the creative design process by the integration of engineering design and cognitive psychology literature. Design Studies, 29(2), 160–180. https://doi.org/10.1016/j.destud.2008.01.001
[2] Anantrasirichai, N., & Bull, D. (2022). Artificial intelligence in the creative industries: A review. Artificial Intelligence Review, 55(1), 589–656. https://doi.org/10.1007/s10462-021-10039-7[3] Dorst, K., & Cross, N. (2001). Creativity in the design process: Co-evolution of problem–solution. Design Studies, 22(5), 425–437. https://doi.org/10.1016/S0142-694X(01)00009-6[4] Sarkar, P., & Chakrabarti, A. (2011). Assessing design creativity. Design Studies, 32(4), 348–383. https://doi.org/10.1016/j.destud.2011.01.002[5] Bouschery, S. G., Blazevic, V., & Piller, F. T. (2023). Augmenting human innovation teams with artificial intelligence: Exploring transformer-based language models. Journal of Product Innovation Management, 40(2), 139–153. https://doi.org/10.1111/jpim.12656[6] Verganti, R., Vendraminelli, L., & Iansiti, M. (2020). Innovation and design in the age of artificial intelligence. Journal of Product Innovation Management, 37(3), 212–227. https://doi.org/10.1111/jpim.12523[7] Green, S., Southee, D., & Boult, J. (2014). Towards a design process ontology. The Design Journal, 17(4), 515–537. https://doi.org/10.2752/175630614X14056185480032[8] Hughes, R. T., Zhu, L., & Bednarz, T. (2021). Generative adversarial networks–enabled human–artificial intelligence collaborative applications for creative and design industries: A systematic review of current approaches and trends. Frontiers in Artificial Intelligence, 4. https://www.frontiersin.org/articles/10.3389/frai.2021.604234[9] Isgrò, F., Ferraris, S. D., & Colombo, S. (2022). AI-enabled design tools: Current trends and future possibilities. In G. Bruyns & H. Wei (Eds.), [ ] With Design: Reinventing Design Modes (pp. 2836–2847). Springer. https://doi.org/10.1007/978-981-19-4472-7_183
[2] Anantrasirichai, N., & Bull, D. (2022). Artificial intelligence in the creative industries: A review. Artificial Intelligence Review, 55(1), 589–656. https://doi.org/10.1007/s10462-021-10039-7[3] Dorst, K., & Cross, N. (2001). Creativity in the design process: Co-evolution of problem–solution. Design Studies, 22(5), 425–437. https://doi.org/10.1016/S0142-694X(01)00009-6[4] Sarkar, P., & Chakrabarti, A. (2011). Assessing design creativity. Design Studies, 32(4), 348–383. https://doi.org/10.1016/j.destud.2011.01.002[5] Bouschery, S. G., Blazevic, V., & Piller, F. T. (2023). Augmenting human innovation teams with artificial intelligence: Exploring transformer-based language models. Journal of Product Innovation Management, 40(2), 139–153. https://doi.org/10.1111/jpim.12656[6] Verganti, R., Vendraminelli, L., & Iansiti, M. (2020). Innovation and design in the age of artificial intelligence. Journal of Product Innovation Management, 37(3), 212–227. https://doi.org/10.1111/jpim.12523[7] Green, S., Southee, D., & Boult, J. (2014). Towards a design process ontology. The Design Journal, 17(4), 515–537. https://doi.org/10.2752/175630614X14056185480032[8] Hughes, R. T., Zhu, L., & Bednarz, T. (2021). Generative adversarial networks–enabled human–artificial intelligence collaborative applications for creative and design industries: A systematic review of current approaches and trends. Frontiers in Artificial Intelligence, 4. https://www.frontiersin.org/articles/10.3389/frai.2021.604234[9] Isgrò, F., Ferraris, S. D., & Colombo, S. (2022). AI-enabled design tools: Current trends and future possibilities. In G. Bruyns & H. Wei (Eds.), [ ] With Design: Reinventing Design Modes (pp. 2836–2847). Springer. https://doi.org/10.1007/978-981-19-4472-7_183
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