Abstract
Artificial Intelligence Generated Content (AIGC) introduces a new collaborative design paradigm where words, sentences, and images circulate within the team as new design knowledge. However, due to the limited controllability and inter-pretability of current AIGC models, collaboration between designers and AI de-mands continuous iterations and experimentation. How to establish a reusable representation for the knowledge of the collaborative process is an open prob-lem. Our comprehensive approach, including focused interviews, case studies, and workshops, revealed transmission patterns of design concepts during both divergent and convergent phases. To represent the interaction between design-ers, we propose a novel node-based design strategy, where each node is an AI operation with its prompts and outputs and each link denotes the data flow to the next node. Implementing this strategy, we crafted a design system that en-hances synergy between the design team and AIGC.
Keywords
design progress; human-ai collaboration; generative ai
DOI
https://doi.org/10.21606/drs.2024.985
Citation
Yu, K., Xiao, Y., Li, M., Yu, S., Yang, Y., Guo, X., Zhang, W., and Yuan, X. (2024) Design for AI-Integrated Design Team Collaboration：A Strategy and Exploration Using Node Flow in Establishing a Reusable Representation of Knowledge in the Collaborative Process, in Gray, C., Ciliotta Chehade, E., Hekkert, P., Forlano, L., Ciuccarelli, P., Lloyd, P. (eds.), DRS2024: Boston, 23–28 June, Boston, USA. https://doi.org/10.21606/drs.2024.985
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Research Paper
Included in
Design for AI-Integrated Design Team Collaboration：A Strategy and Exploration Using Node Flow in Establishing a Reusable Representation of Knowledge in the Collaborative Process
Artificial Intelligence Generated Content (AIGC) introduces a new collaborative design paradigm where words, sentences, and images circulate within the team as new design knowledge. However, due to the limited controllability and inter-pretability of current AIGC models, collaboration between designers and AI de-mands continuous iterations and experimentation. How to establish a reusable representation for the knowledge of the collaborative process is an open prob-lem. Our comprehensive approach, including focused interviews, case studies, and workshops, revealed transmission patterns of design concepts during both divergent and convergent phases. To represent the interaction between design-ers, we propose a novel node-based design strategy, where each node is an AI operation with its prompts and outputs and each link denotes the data flow to the next node. Implementing this strategy, we crafted a design system that en-hances synergy between the design team and AIGC.