Computer Science

Document Type

Conference Paper

Abstract

Generative AI (GenAI) is both promising and challenging in supporting people with disabilities (PwDs) in creating stories about disability. GenAI can reduce barriers to media production and inspire the creativity of PwDs, but it may also introduce biases and imperfections that hinder its adoption for personal expression. In this research, we examine how nine PwD from a disability advocacy group used GenAI to create videos sharing their disability experiences. Grounded in digital storytelling theory, we explore the motivations, expression, and sharing of PwD-created GenAI story videos. We conclude with a framework of momentous depiction, which highlights four core affordances of GenAI that either facilitate or require improvements to better support disability storytelling: non-capturable depiction, identity concealment and representation, contextual realism and consistency, and emotional articulation. Based on this framework, we further discuss design implications for GenAI in relation to story completion, media formats, and corrective mechanisms. © 2026 Copyright held by the owner/author(s).

Publication Title

Conference on Human Factors in Computing Systems - Proceedings

Publication Date

4-13-2026

ISBN

9798400722783

DOI

10.1145/3772318.3791495

Keywords

disability, Generative AI, LLM, storytelling, video

APA Citation

Niu, S., Clements, D., & Kim, H. (2026, April). Creating Disability Story Videos with Generative AI: Motivation, Expression, and Sharing. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1-16).

Cross Post Location

Student Publications

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