Authors’ Values and Attitudes Towards AI-bridged Scalable Personalization of Creative Language Arts
Taewook Kim, Hyomin Han, Eytan Adar, Matthew Kay, John Joon Young Chung
ACM Human Factors in Computing Systems (CHI) 2024 | 
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(A) Author-audience dynamics without AI. (B) Author-audience dynamics with AI-bridged CLA. Authors can find values from the process of creating the artifact (red). Authors infuse certain values into the artifacts in the hope that audiences would find these values from artifacts (blue). Lastly, authors might receive values from the audience (green).
Abstract
Generative AI has the potential to create a new form of interactive media: AI-bridged creative language arts (CLA), which bridge the author and audience by personalizing the author’s vision to the audience’s context and taste at scale. However, it is unclear what the authors’ values and attitudes would be regarding AI-bridged CLA. To identify these values and attitudes, we conducted an interview study with 18 authors across eight genres (e.g., poetry, comics) by presenting speculative but realistic AI-bridged CLA scenarios. We identified three benefits derived from the dynamics between author, artifact, and audience: those that 1) authors get from the process, 2) audiences get from the artifact, and 3) authors get from the audience. We found how AI-bridged CLA would either promote or reduce these benefits, along with authors’ concerns. We hope our investigation hints at how AI can provide intriguing experiences to CLA audiences while promoting authors’ values.