Creating Disability Story Videos with Generative AI: Motivation, Expression, and Sharing

TL;DR

This paper investigates how people with disabilities use generative AI to create and share personal stories, highlighting opportunities and challenges in supporting authentic disability storytelling through AI tools.

Contribution

It introduces a framework of core affordances for GenAI in disability storytelling and discusses design implications to improve AI support for personal expression.

Findings

GenAI enables PwDs to create expressive disability stories.

Four core affordances influence the effectiveness of GenAI in storytelling.

Design improvements can enhance authenticity and emotional articulation in generated videos.

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.