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• Disability-First AI Dataset Annotation: Co-designing Stuttered Speech Annotation Guidelines with People Who Stutter

  Xinru Tang, Jingjin Li, Shaomei Wu · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  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 (FluencyBank, UCLASS, KSoF,…

  AI dataset annotation · stuttering · speech recognition · disability-first design · embodied knowledge

• Surveilling Suitability: How AI Hiring Interviews Impact Job Seekers with Disabilities

  Vaishnav Kameswaran, Valentina Hong, Jazmin Clark, Yu Hou, Hal Daumé III, Katie Shilton · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  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 and experienced by job seekers…

  disability · AI hiring · surveillance · algorithmic bias · employment

• Toward a taxonomy of negative outcomes from the use of AI-driven systems for people with disabilities

  Krishna Venkatasubramanian, Haven Hardie, Tina-Marie Ranalli · 2025 · ASSETS 2025: 27th International ACM SIGACCESS Conference on Computers and Accessibility

  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 Incident Monitor, and the Database…

  AI fairness · algorithmic bias · disability rights · AI harm · AI incident databases

• Examining and Mitigating Ability-bias in LLMs via Self-Reflection

  Neel Iyer, Akshita Jha, Alisha Pradhan · 2025 · Proceedings of the 22nd International Web for All Conference (W4A)

  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, the authors administered…

  ability bias · ableism · LLM bias · debiasing · AI fairness

• Data Representativeness in Accessibility Datasets: A Meta-Analysis

  Rie Kamikubo, Lining Wang, Crystal Marte, Amnah Mahmood, Hernisa Kacorri · 2022 · Proceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '22)

  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 race and ethnicity are…

  AI fairness · datasets · representation · diversity · inclusion

• Regulating Personal Cameras for Disabled People and People with Deafblindness: Implications for HCI and Accessible Computing

  Sarah L. Woodin, Arthur Theil · 2021 · Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '21)

  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), the authors — a disability…

  deafblindness · wearable cameras · face recognition · privacy · data protection

• How Could Equality and Data Protection Law Shape AI Fairness for People with Disabilities?

  Reuben Binns, Reuben Kirkham · 2021 · ACM Transactions on Accessible Computing

  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 other protected…

  AI fairness · disability discrimination · data protection · GDPR · equality law

• Fairness of AI for People with Disabilities: Problem Analysis and Interdisciplinary Collaboration

  Jason J. G. White · 2020 · SIGACCESS Accessibility and Computing

  This paper provides a philosophical analysis of the fairness challenges that machine learning-based AI poses for people with disabilities, arguing that these challenges demand unprecedented interdisciplinary collaboration across applied ethics, human rights law, disability…

  AI fairness · algorithmic bias · disability · social justice · ethics

• Fairness Issues in AI Systems that Augment Sensory Abilities

  Leah Findlater, Steven Goodman, Yuhang Zhao, Shiri Azenkot, Margot Hanley · 2020 · SIGACCESS Accessibility and Computing

  This paper examines the unique fairness challenges that arise when AI systems are used to augment sensory abilities for people with disabilities — a context distinct from other AI applications because these systems provide information that is already available to non-disabled…

  AI fairness · sensory augmentation · visual impairment · deaf and hard of hearing · privacy

• Artificial Intelligence and the Dignity of Risk

  Emily Shea Tanis, Clayton Lewis · 2020 · SIGACCESS Accessibility and Computing

  This paper examines the dual risks and opportunities that AI-based systems pose for people with cognitive disabilities, framed around the concept of the "dignity of risk" — the right to make self-directed choices about tradeoffs between risks and benefits, including the freedom…

  AI fairness · cognitive disability · dignity of risk · privacy · algorithmic bias

• Toward Fairness in AI for People with Disabilities: A Research Roadmap

  Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna Wallach, Meredith Ringel Morris · 2020 · SIGACCESS Accessibility and Computing

  This position paper from Microsoft Research presents a systematic risk assessment of how major categories of AI systems may fail or discriminate against people with disabilities, proposing a four-point research roadmap for increasing AI fairness. The authors organize their…

  AI fairness · algorithmic bias · disability · computer vision · speech recognition

• What Is the Point of Fairness? Disability, AI and the Complexity of Justice

  Cynthia L. Bennett, Os Keyes · 2020 · SIGACCESS Accessibility and Computing

  This paper offers a critical disability studies challenge to the dominant "fairness" framing of AI ethics, arguing that fairness is insufficient and potentially harmful when applied to disability, and that justice must be centred instead. Drawing on Anna Lauren Hoffmann's…

  AI fairness · disability justice · critical disability studies · computer vision · autism diagnosis

• Artificial Intelligence Fairness in the Context of Accessibility Research on Intelligent Systems for People Who Are Deaf or Hard of Hearing

  Sushant Kafle, Abraham Glasser, Sedeeq Al-khazraji, Larwan Berke, Matthew Seita, Matt Huenerfauth · 2020 · SIGACCESS Accessibility and Computing

  This paper from RIT's Center for Accessibility and Inclusion Research discusses AI fairness issues specifically through the lens of the authors' extensive research on intelligent systems for people who are Deaf or Hard of Hearing (DHH). The authors identify five interconnected…

  AI fairness · deaf and hard of hearing · automatic speech recognition · captioning · evaluation metrics

• Sense and Accessibility: Understanding People with Physical Disabilities' Experiences with Sensing Systems

  Shaun K. Kane, Anhong Guo, Meredith Ringel Morris · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020)

  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 adults with physical…

  physical disability · AI bias · AI fairness · sensors · ubiquitous computing

• Privacy Considerations of the Visually Impaired with Camera Based Assistive Technologies: Misrepresentation, Impropriety, and Fairness

  Taslima Akter, Tousif Ahmed, Apu Kapadia, Swami Manohar Swaminathan · 2020 · Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2020)

  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 behavioral information about…

  visual accessibility · blindness and low vision · privacy · AI bias · AI fairness

• Exploring the Performance of Facial Expression Recognition Technologies on Deaf Adults and Their Children

  Irene Rogan Shaffer · 2018 · Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2018)

  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 problem: in ASL and other sign…

  deaf and hard of hearing · sign language · facial expression recognition · emotion recognition · AI fairness

16 results.