Researchers have argued that large language models (LLMs) exhibit high-quality writing capabilities from blogs to stories. However, evaluating objectively the creativity of a piece of writing is challenging. Inspired by the Torrance Test of Creative Thinking (TTCT), which measures creativity as a process, we use the Consensual Assessment Technique and propose Torrance Test of Creative Writing (TTCW) to evaluate creativity as product. TTCW consists of 14 binary tests organized into the original dimensions of Fluency, Flexibility, Originality, and Elaboration. We recruit 10 creative writers and implement a human assessment of 48 stories written either by professional authors or LLMs using TTCW. Our analysis shows that LLM-generated stories pass 3-10X less TTCW tests than stories written by professionals. In addition, we explore the use of LLMs as assessors to automate the TTCW evaluation, revealing that none of the LLMs positively correlate with the expert assessments.
doi.org/10.1145/3613904.3642731
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.
doi.org/10.1145/3613904.3642529
Understanding how communities experience algorithms is necessary to mitigate potential harmful impacts. This paper presents folk theories of text-to-image (T2I) models to enrich understanding of how artist communities experience creative machine learning systems. This research draws on data collected from a workshop with 15 artists from 10 countries who incorporate T2I models in their creative practice. Through reflexive thematic analysis of workshop data, we highlight artist folk theories of T2I use, harm, and harm reduction. Folk theories of use envision T2I models as an artistic medium, a mundane tool, and locate true creativity as rising above model affordances. Theories of harm articulate T2I models as harmed by engineering efforts to eliminate glitches and product policy efforts to limit functionality. Theories of harm-reduction orient towards protecting T2I models for creative practice through transparency and distributed governance. We examine how these theories relate, and conclude by discussing how folk theorization informs responsible AI efforts.
doi.org/10.1145/3613904.3642461
This paper discusses the findings from a cross-sector research project investigating how a digital score created using AI and robot-ics might stimulate new creative opportunities and relationships within the practices of an inclusive music ensemble. Through the concept of a digital score [65], AI and a robotic arm were introduced into an ensemble’s musical practice to evaluate the impact and ben-efits of using autonomous systems to challenge barriers around a disabled musician's access to creative music-making. Throughout the development process we placed an emphasis on involvement and togetherness of not only the AI and robots' contribution to shared creativity amongst the ensemble, but also to the social as-pects of the creative process across the team of musicians, develop-ers, researchers and supporting organisations. The findings were surprising with many aspects of the project exceeding the expecta-tions of the original aims. In short, all the musicians benefited from the introduction of these unfamiliar technologies with practices enhanced and relationships transformed.
doi.org/10.1145/3613904.3642548