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• Shiny Stories, Hidden Struggles: Investigating the Representation of Disability Through the Lens of LLMs

  Marco Bombieri, Simone Paolo Ponzetto, Marco Rospocher · 2026 · ACM Transactions on Intelligent Systems and Technology

  This paper investigates how Large Language Models (LLMs) represent disability by comparing AI-generated social media posts with self-descriptions from real people with disabilities on Reddit. The study addresses a critical gap in bias research: while prior work has focused on…

  AI bias · large language models · disability representation · inspiration porn · toxic positivity

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

  Shuo Niu, Dylan Clements, Hyungsin Kim · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Niu, Clements, and Kim worked with nine people with disabilities (PwDs) from a Massachusetts disability advocacy group (pseudonymized as 'Campaign') to study how novice users adopt generative AI for creating first-person disability storytelling videos. Participants had…

  generative AI · disability storytelling · video accessibility · disability advocacy · LLM

• Interface Support for Evaluating Disability Bias in AI-Generated Images

  Kelly Avery Mack, Lucy Jiang, Lotus Zhang, Leah Findlater · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Mack and colleagues investigate whether interface-level interventions can help users of generative text-to-image (T2I) tools recognise and avoid disability stereotypes in AI-generated images. The authors frame the work around a gap in AI safety: while model-side debiasing is an…

  AI bias · generative AI · text-to-image · disability representation · disability stereotypes

3 results.