Literature Reviews
Reviewed research papers, articles, and publications relevant to digital accessibility.
16 results found tagged AI fairness.
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Surveilling Suitability: How AI Hiring Interviews Impact Job Seekers with Disabilities
This CHI 2026 paper reports a qualitative study of how AI-driven hiring interview platforms — asynchronous video interview tools (e.g., HireVue) that use AI to score candidates on facial expressions, vocal cues, and behavioural data — are perceived a…
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Disability-First AI Dataset Annotation: Co-designing Stuttered Speech Annotation Guidelines with People Who Stutter
Tang, Li, and Wu present the first study to push the 'disability-first' principle beyond dataset collection and into the dataset annotation stage of the AI pipeline. Their case is stuttered speech: despite a growing number of stuttering datasets (Flu…
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How Could Equality and Data Protection Law Shape AI Fairness for People with Disabilities?
This interdisciplinary paper examines how UK equality law and EU data protection law (GDPR) intersect with AI fairness for people with disabilities (PWD). The authors argue that AI fairness for PWD requires a fundamentally different approach than for…
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Exploring the Performance of Facial Expression Recognition Technologies on Deaf Adults and Their Children
This Boston University student research paper investigates how commercial facial expression recognition services perform on Deaf ASL signers and Children of Deaf Adults (CODAs) compared to hearing non-signers. The study is motivated by a critical pro…
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Privacy Considerations of the Visually Impaired with Camera Based Assistive Technologies: Misrepresentation, Impropriety, and Fairness
This paper investigates the privacy concerns of both visually impaired people (PVIs) and sighted bystanders regarding camera-based assistive technologies like smart glasses (Orcam, Aira, eSight) that can identify people and provide demographic and be…
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Sense and Accessibility: Understanding People with Physical Disabilities' Experiences with Sensing Systems
This paper examines how sensing systems — the increasingly pervasive technologies that mediate our interactions with the digital and physical world — create accessibility barriers for people with physical disabilities. Through an online survey of 40 …
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Regulating Personal Cameras for Disabled People and People with Deafblindness: Implications for HCI and Accessible Computing
This experience paper examines the intersection of social policy, privacy regulation, and assistive technology design, focusing on the case of personal cameras for people with deafblindness. Drawing from the EU-funded SUITCEYES project (2018-2021), t…
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Data Representativeness in Accessibility Datasets: A Meta-Analysis
This paper conducts a systematic meta-analysis of demographic representativeness in 190 accessibility datasets — datasets sourced from people with disabilities and older adults — spanning from 1984 to 2021. The authors examine how age, gender, and ra…
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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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Toward a taxonomy of negative outcomes from the use of AI-driven systems for people with disabilities
This paper presents the first systematic taxonomy of how AI-driven systems create negative outcomes specifically for people with disabilities. The authors searched eight publicly available AI incident databases — including AIAAIC, AIID, OECD AI Incid…