Literature Reviews
Reviewed research papers, articles, and publications relevant to digital accessibility.
10 results found tagged disability representation.
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Interface Support for Evaluating Disability Bias in AI-Generated Images
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: whil…
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Shiny Stories, Hidden Struggles: Investigating the Representation of Disability Through the Lens of LLMs
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…
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Rhetoric vs Responsibility: How Tech Companies Shape AI for Accessibility
Marathe, Zhou, Mishra, and Piper conduct a critical discourse analysis (CDA) of 126 public-facing blog posts and news articles published between 2016 and 2025 by 11 leading U.S.-based AI companies — Adobe, Amazon, Apple, Eleven Labs, Google, Meta, Mi…
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How the Alt Text Gets Made: What Roles and Processes of Alt Text Creation Can Teach Us About Inclusive Imagery
This paper investigates how alternative text is created in industry settings through a collaboration between UC Irvine researchers and Google's Avatar Project, an initiative to create inclusive stickers depicting people with disabilities. The researc…
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A Return to Community: Flintstones or Jetsons?
This keynote-style paper uses the cultural lens of two iconic 1960s cartoons — The Flintstones and The Jetsons — to reflect on how automation and technology are shaping the lives of people with disabilities. Dr. Conway, writing from Western Australia…
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"That's in the eye of the beholder": Layers of Interpretation in Image Descriptions for Fictional Representations of People with Disabilities
This paper investigates how to create accurate and sensitive image descriptions for fictional representations of people with disabilities — a challenge that arises when real subjects cannot be consulted about their preferred identity terminology. The…
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Examining and Mitigating Ability-bias in LLMs via Self-Reflection
This short paper investigates ability bias in large language models — the tendency of LLMs to encode and perpetuate stereotypical or discriminatory associations about people with disabilities. Using the Bias Benchmarking Questionnaire (BBQ) dataset, …
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"I'm treating it kind of like a diary": Characterizing How Users with Disabilities Use AI Chatbots
This study investigates how people with disabilities actually use LLM-based chatbots like ChatGPT, Gemini, Claude, and Perplexity in their daily lives. While previous research has focused primarily on identifying harms that LLMs impose on the disabil…
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The Fears, The Hopes, The Oscillations: A Critical Analysis of Tech Startups Targeting Autism
This paper employs thematic and critical discourse analysis to examine the websites of 38 autism tech startups founded in the U.S. since 2012, investigating how these companies construct problems, users, and technological legitimacy through their mar…
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Unintended Machine Learning Biases as Social Barriers for Persons with Disabilities
This paper from Google's Ethical AI team provides concrete empirical evidence that widely deployed NLP models encode measurable biases against people with disabilities, creating social barriers through technology. The authors examine three layers of …