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

TL;DR

WorldSmith introduces an iterative, multi-modal system that helps users create and modify fictional worlds through layered visualizations and prompts, enhancing expressiveness and user control in world-building with AI.

Contribution

The paper presents a novel multi-modal interface enabling iterative, layered world-building with generative AI, surpassing traditional prompt-based methods.

Findings

Users found WorldSmith more expressive and flexible.

Participants could quickly visualize complex worlds.

The system supports hierarchical and layered edits.

Abstract

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.