The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Technological solutionism: disability, higher education and generative artificial intelligence
Open accessAbstract
Generative AI is rapidly emerging as a mainstream or general purpose technology that non-specialists may use with the aim of enhancing accessibility although many will not have the lived experience or expertise to evaluate whether this sufficiently meets the diverse needs of others. This is particularly critical for educators, as disabled students already report inconsistencies with existing technological and institutional supports. To date, there have been relatively few efforts to engage disabled students in discussions around Generative AI. Some details are specific to a UK and Higher Education context, but many general principles are expected to be transferable. As the author is based in the UK, this paper adopts an identity-first model of language.
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Cites
To Save Everything, Click Here: The Folly of Technological Solutionism
Cramer, B. W. (2014) · Journal of Information Policy · doi:10.5325/jinfopoli.4.2014.0173 · Cited by 873
Post-Covid-19 Education and Education Technology ‘Solutionism’: a Seller’s Market
Teräs, M., Suoranta, J., Teräs, H., & Curcher, M. (2020) · Postdigital Science and Education · doi:10.1007/s42438-020-00164-x · Cited by 594
"I wouldn't say offensive but...": Disability-Centered Perspectives on Large Language Models
Gadiraju, V., Kane, S., Dev, S., Taylor, A., Wang, D., Denton, R., & Brewer, R. (2023) · 2023 ACM Conference on Fairness Accountability and Transparency · doi:10.1145/3593013.3593989 · Cited by 155
(2020) · doi:10.1145/3386296.3386301 · Cited by 107
An Autoethnographic Case Study of Generative Artificial Intelligence's Utility for Accessibility
Glazko, K. S., Yamagami, M., Desai, A., Mack, K. A., Potluri, V., Xu, X., & Mankoff, J. (2023) · The 25th International ACM SIGACCESS Conference on Computers and Accessibility · doi:10.1145/3597638.3614548 · Cited by 80
Rice, M. F., & Dunn, S. D. (2023) · Computers in the Schools · doi:10.1080/07380569.2023.2244935 · Cited by 66
Disabled student experiences of Higher Education
Brewer, G., Urwin, E., & Witham, B. (2025) · Disability & Society · doi:10.1080/09687599.2023.2263633 · Cited by 53
Prevalence of bias against neurodivergence‐related terms in artificial intelligence language models
Brandsen, S., Chandrasekhar, T., Franz, L., Grapel, J., Dawson, G., & Carlson, D. (2024) · Autism Research · doi:10.1002/aur.3094 · Cited by 47
Evaluating the effectiveness of automatic image captioning for web accessibility
Leotta, M., Mori, F., & Ribaudo, M. (2022) · Universal Access in the Information Society · doi:10.1007/s10209-022-00906-7 · Cited by 37
Ortegón, C., Decuypere, M., & Williamson, B. (2024) · Research in Education · doi:10.1177/00345237241242990 · Cited by 33
Research works printed but not linked: 3
- Bailey, John, and John Warner. 2024. “AI Tutors: Hype or Hope for Education?” Education Next 25 (1): 62–71. https://www.educationnext.org/ai-tutors-hype-or-hope-for-education-forum/.
- Holt, Laurence. 2024. “The 5 Percent Problem.” Education Next 24 (4): 26–31 https://www.educationnext.org/5-percent-problem-online-mathematics-programs-may-benefit-most-kids-who-need-it-least/.
- 10.15131/shef.data.25669323.v1 · doi:10.15131/shef.data.25669323.v1
Cited by
Morgan, D. (2026) · Disability & Society · doi:10.1080/09687599.2026.2667528 · Cited by 4
Castellano-Beltrán, A. (2025) · International Journal of Information and Learning Technology · doi:10.1108/ijilt-11-2024-0260 · Cited by 2
Almulla, A. A., Alduais, A. M. S., & Almulla, M. O. (2026) · Journal of Disability Research · doi:10.57197/jdr-2026-0937
A sociotechnical approach to ethical AI in disability services: insights from stakeholders
Ždanovič, N., & Bezzina, L. (2026) · Disability & Society · doi:10.1080/09687599.2026.2733300
Metadata
- Authors
- Fletcher, R.
- Affiliations
- Nottingham Trent University (GB)
- Corresponding author
- Fletcher, Richard
- ORCID
- Fletcher, Richard
- Venue
- Disability & Society
- Publisher
- Informa UK Limited
- Published
- 2025-08-18
- Volume
- 41
- Issue
- 4
- Pages
- 1154-1159
- ISSN
- 0267-4645 (ISSN-L)
- 0968-7599
- 1360-0508
- OpenAlex
- W4413273736
- Cited by
- 4
- References
- 18
- Citations by year
- 2026: 3 · 2025: 1
- FWCI
- 4.19
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Disability & Society (publishedVersion, cc-by)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Human Factors and Ergonomics › Digital Accessibility for Disabilities
- Social Sciences › Education › Disability Education and Employment
- Keywords
- generative AI, disability, higher education, accessibility, students with disabilities, solutionism, student engagement, identity-first language, educational technology
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- Fletcher, R. (2026). Technological solutionism: disability, higher education and generative artificial intelligence. Disability & Society. https://doi.org/10.1080/09687599.2025.2548461
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
