Literature Reviews
Reviewed research papers, articles, and publications relevant to digital accessibility.
61 results found tagged accessibility.
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Demonstrating Consent Rings: Explicit Non-Verbal Consent Through Haptic Wearables as a Solution to Unwanted Sex Between Neurodivergent Partners
Consent Rings is a pair of symmetric haptic Bluetooth ring wearables developed by three neurodivergent researchers as an accessibility-oriented alternative to verbal 'yes means yes' affirmative consent. The authors situate the work in evidence that n…
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Look Here, Click Me: Improving Older Adults’ Perception of Manipulable User Interface Components through AI-Based Perceptual Guidance
This CHI 2026 Extended Abstracts paper from Sookmyung Women’s University (Seoul) tackles a concrete gap in older-adult digital literacy: existing programs teach step-by-step procedures ("tap here, then here, then here") that collapse the moment an ap…
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Reassurance Robots: OCD in the Age of Generative AI
This CHI 2026 Extended Abstracts paper by Grace Barkhuff (Georgia Tech) is an exploratory qualitative study of how generative AI tools, particularly ChatGPT, are reshaping the lived experience of Obsessive-Compulsive Disorder (OCD). OCD is a mental h…
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Towards Inclusive External Human-Machine Interface: Exploring the Effects of Visual and Auditory eHMI for Deaf and Hard-of-Hearing People
This CHI 2026 paper is a companion to Xu et al. 2026 (10.1145/3772318.3791557) but with a broader, two-stage inclusive-design focus: selecting appropriate visual eHMI concepts for Deaf and Hard-of-Hearing (DHH) pedestrians and then evaluating how vis…
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Exploring the Impacts of Background Noise on Auditory Stimuli of Audio-Visual eHMIs for Hearing, Deaf, and Hard-of-Hearing People
This CHI 2026 paper investigates a critical but overlooked accessibility question in the design of external Human-Machine Interfaces (eHMIs) for automated vehicles (AVs): how do Deaf and Hard-of-Hearing (DHH) pedestrians experience audio-visual eHMIs…
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Exploring AI Opportunities in Deaf Education: Understanding Design Needs Through Teacher and Parent Perspectives in Bangladesh
This CHI 2026 qualitative study investigates how AI-powered educational tools should be designed for Deaf learners in Bangladesh — a low-resource context where Bangla Sign Language (BdSL) is still evolving, datasets are small, and infrastructure (int…
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"I Don't Trust it, but I Use it": Navigating Trust, Privacy, and Identity in Disabled People's Use of Generative AI
This CHI 2026 paper reports a qualitative focus-group study of how disabled people navigate generative AI (GenAI) tools in everyday life, with particular attention to how trust, privacy, and intersecting identities (race, gender, language, sexuality,…
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How Multimodal Large Language Models Support Access to Visual Information: A Diary Study With Blind and Low Vision People
This CHI 2026 paper reports a two-week diary study with 20 Blind and Low Vision (BLV) participants (ages 19–75, 11 female/9 male, 13 blind/7 low vision) investigating how multimodal large language models (MLLMs) support real-world access to visual in…
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The ORBIT India Dataset: Understanding the Challenges of Collecting a Disability-First AI Dataset in Low-Resource Environments
This paper introduces ORBIT-India, the first teachable object recognition dataset contributed entirely by people who are blind or have low vision in India. It extends the UK/Canada-collected ORBIT dataset (Massiceti et al., 2021) to the Indian contex…
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Beyond Accuracy: Auditing Allocative Harms in Facial-Gesture Recognition for People with Motor Impairments
This paper challenges the conventional framing of facial-gesture recognition accuracy as a purely technical property, and reframes it as a sensorimotor alignment problem between user intention and algorithmic interpretation. The authors conducted a m…