The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Toward fairness in AI for people with disabilities SBG@a research roadmap
Abstract
AI technologies have the potential to dramatically impact the lives of people with disabilities (PWD). Indeed, improving the lives of PWD is a motivator for many state-of-the-art AI systems, such as automated speech recognition tools that can caption videos for people who are deaf and hard of hearing, or language prediction algorithms that can augment communication for people with speech or cognitive disabilities. However, widely deployed AI systems may not work properly for PWD, or worse, may actively discriminate against them. These considerations regarding fairness in AI for PWD have thus far received little attention. In this position paper, we identify potential areas of concern regarding how several AI technology categories may impact particular disability constituencies if care is not taken in their design, development, and testing. We intend for this risk assessment of how various classes of AI might interact with various classes of disability to provide a roadmap for future research that is needed to gather data, test these hypotheses, and build more inclusive algorithms.
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“More generally, the literature on AI and accessibility also suggests specific concerns regarding the use of AI and people with disabilities (Guo et al., 2020;Morris, 2020;Trewin, 2018).”
From Exploring the role of generative AI in higher education: Semi-structured interviews with students with disabilities (2025) · cites this paper as Guo et al., 2020
In the citing paper
“For instance, speech-to-text recognition may not function properly for people with unusual speech patterns (Guo et al., 2020).”
From Exploring the role of generative AI in higher education: Semi-structured interviews with students with disabilities (2025) · cites this paper as Guo et al., 2020
In the citing paper
“Guo et al. (2020) presented a research roadmap arguing that computer vision, speech systems, text processing, integrative AI, and other AI techniques may not work for people with disabilities as it does for those without.”
From Exploring the role of generative AI in higher education: Semi-structured interviews with students with disabilities (2025) · cites this paper as Guo et al., 2020
In the citing paper
“Interestingly, Guo et al. (2020) highlighted that conversational agents might be ineffective for dyslexic individuals if the system has not been trained to interpret texts with atypical spelling or phrasing.”
From Exploring the role of generative AI in higher education: Semi-structured interviews with students with disabilities (2025) · cites this paper as Guo et al., 2020
In the citing paper
“and thus partially disproves the risk identified by Guo et al. (2020).”
From Exploring the role of generative AI in higher education: Semi-structured interviews with students with disabilities (2025) · cites this paper as Guo et al. (2020)
In the citing paper
“One student reported that ChatGPT could be talking about autism in a harmful and biased manner, concurring with concerns about bias in research on AI ethics and disability (Guo et al., 2020;Morris, 2020;Trewin, 2018).”
From Exploring the role of generative AI in higher education: Semi-structured interviews with students with disabilities (2025) · cites this paper as Guo et al., 2020
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Metadata
- Authors
- Guo, A., Kamar, E., Vaughan, J. W., Wallach, H., & Morris, M. R.
- Affiliations
- Microsoft (United States) (US)
- Venue
- ACM SIGACCESS Accessibility and Computing
- Published
- 2020-03-02
- Issue
- 125
- Pages
- 1-1
- ISSN
- 1558-1187 (ISSN-L)
- 1558-2337
- OpenAlex
- W3009306974
- Cited by
- 128
- References
- 36
- Citations by year
- 2026: 7 · 2025: 23 · 2024: 26 · 2023: 34 · 2022: 19 · 2021: 15 · 2020: 3
- FWCI
- 24.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM SIGACCESS Accessibility and Computing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Human Factors and Ergonomics › Digital Accessibility for Disabilities
- Health Sciences › Health Professions › Occupational Therapy › Assistive Technology in Communication and Mobility
- Keywords
- algorithmic fairness, people with disabilities, algorithmic discrimination, accessibility, speech recognition, deaf and hard of hearing, assistive technology, research roadmap
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