WorldSmith : Iterative and Expressive Prompting for World Building with a Generative AI

Title data

Dang, Hai ; Brudy, Frederik ; Fitzmaurice, George ; Anderson, Fraser:
WorldSmith : Iterative and Expressive Prompting for World Building with a Generative AI.
In: Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology : UIST '23. - New York, NY, USA : Association for Computing Machinery , 2023 . - 36
ISBN 979-8-4007-0132-0
DOI: https://doi.org/10.1145/3586183.3606772

Official URL:

Abstract in another language

Crafting a rich and unique environment is crucial for fictional world-building, but can be difficult to achieve since illustrating a world from scratch requires time and significant skill. We investigate the use of recent multi-modal image generation systems to enable users iteratively visualize and modify elements of their fictional world using a combination of text input, sketching, and region-based filling. WorldSmith enables novice world builders to quickly visualize a fictional world with layered edits and hierarchical compositions. Through a formative study (4 participants) and first-use study (13 participants) we demonstrate that WorldSmith offers more expressive interactions with prompt-based models. With this work, we explore how creatives can be empowered to leverage prompt-based generative AI as a tool in their creative process, beyond current "click-once" prompting UI paradigms.

Further data

Item Type:	Article in a book
Refereed:	Yes
Keywords:	Multi-modal image generation; Fictional world-building; AI-assisted creativity
Institutions of the University:	Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IX > Chair Applied Computer Science - Univ.-Prof. Dr. Daniel Buschek
Result of work at the UBT:	Yes
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science
Date Deposited:	18 Jan 2024 09:44
Last Modified:	18 Jan 2024 09:44
URI:	https://eref.uni-bayreuth.de/id/eprint/88270