Recent advances in Machine-Learning have led to the development of models that generate images based on a text description.Such large prompt-based text to image models (TTIs), trained on a considerable amount of data, allow the creation of high-quality images by users with no graphics or design training. This paper examines the role such TTI models can playin collaborative, goal-oriented design. Through a within-subjects study with 14 non-professional designers, we find that such models can help participants explore a design space rapidly and allow for fluid collaboration. We also find that text inputs to such models ("prompts") act as reflective design material, facilitating exploration, iteration, and reflection in pair design. This work contributes to the future of collaborative design supported by generative AI by providing an account of how text-to-image models influence the design process and the social dynamics around design and suggesting implications for tool design
@article{arxiv.2303.12647,
title = {A Word is Worth a Thousand Pictures: Prompts as AI Design Material},
author = {Chinmay Kulkarni and Stefania Druga and Minsuk Chang and Alex Fiannaca and Carrie Cai and Michael Terry},
journal= {arXiv preprint arXiv:2303.12647},
year = {2023}
}