Abstract
The summer of 2022 marked the advent of accessible text-to-image tools, revolutionizing image rendering with distinctive styles swiftly. This generated a creative shift among designers, generally addressed as “prompt design”, although this expression scarcely captures the profound interaction between design and digital tools. This paper elucidates the potential synergy between designers and AI through two pragmatic exercises engaged by university students. Our approaches were polarized: in one exercise we fostered a rich imaginative process before the text-to-image creation; secondly we asked students to elaborate a possible user interface over an artifact drawn by AI, following a very simple textual description. The result is a framework that combines both the relevance of structured imaginative process and the capabilities of generative AI technologies, supporting an enriched dialogic interaction between design and dataset-based imagery.
Keywords
scenario design; imagery production; generative ai; designing futures
DOI
https://doi.org/10.21606/drs.2024.822
Citation
Ciaramitaro, M., and Costa, P. (2024) Imagination meets algorithm: redefining design practices in the coming AI age, 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.2024.822
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Research Paper
Included in
Imagination meets algorithm: redefining design practices in the coming AI age
The summer of 2022 marked the advent of accessible text-to-image tools, revolutionizing image rendering with distinctive styles swiftly. This generated a creative shift among designers, generally addressed as “prompt design”, although this expression scarcely captures the profound interaction between design and digital tools. This paper elucidates the potential synergy between designers and AI through two pragmatic exercises engaged by university students. Our approaches were polarized: in one exercise we fostered a rich imaginative process before the text-to-image creation; secondly we asked students to elaborate a possible user interface over an artifact drawn by AI, following a very simple textual description. The result is a framework that combines both the relevance of structured imaginative process and the capabilities of generative AI technologies, supporting an enriched dialogic interaction between design and dataset-based imagery.