Authors' Values and Attitudes Towards AI-bridged Scalable Personalization of Creative Language Arts

TL;DR

This investigation hints at how AI can provide intriguing experiences to CLA audiences while promoting authors’ values, and found how AI-bridged CLA would either promote or reduce these benefits, along with authors’ concerns.

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.

Figures (6)

• Figure 1: The landscape of creative language arts media powered by different technologies, along dimensions of 1) personalization, 2) audience scale, and 3) authorial control. The dimension values of AI-bridged creative language arts are based on recent advances in AI but assume idealistic technology within the direction of advances.
• Figure 2: Overview of our scenario design process. Trans and Gen indicate transfer and generation, respectively. We first identified 12 types of AI-bridged CLA along author dimensions (LLM task, control) and audience dimensions (context, interactivity). We narrowed these into five types, gradually adding changes to the author's current practice ($P$). Then, we instantiated five types in genres of lyrics and novels while focusing AI transformations on content, form, or both.
• Figure 3: We used Cinderella story to create AI-bridged CLA examples in novels. This is a translation from Korean to English.
• Figure 4: $A_3$-type ([transfer, high, N, Y]) derivative of Cinderella. In this example, we explain to authors that audiences are allowed to interactively choose and switch narrative perspectives. Note that this is a translated version from Korean to English.
• Figure 5: Benefit dynamics from the authors' perspective.