Disability, Accessibility, and Civil Rights
Accommodation Repricing: Disability, Generative AI Subscriptions, and the Accessibility Tax as a Variable the Vendor Controls
- Travis Gilly, Real Safety AI Foundation
Publisher: Real Safety AI Foundation
Working paper. Not peer reviewed.
- Written
- August 2026
- Version
- v0.7
- Pages
- 20
Abstract
Disabled people increasingly meet access needs with general purpose generative artificial intelligence sold as a commercial subscription rather than with prescribed assistive technology. Three findings are established in the accessible computing literature: the use is widespread across disability communities, it is frequently necessary rather than discretionary, and pricing tiers determine the quality of access a disabled user can obtain. This paper extends the third finding from level to change. Prior work describes what a disabled user can afford at a moment in time. This paper describes what happens when the price, the metered quantity, or the capability itself moves after the user has already reorganized around it, and it names that event accommodation repricing. The argument is that two literatures each hold half of the mechanism and neither holds the join. The accessibility tax literature describes the standing cost of inaccessibility and treats that cost as a level. The assistive technology abandonment literature explains why access tools fall out of use but locates the cause in the device, in the match between device and user, or in the user’s own changing needs; a complete reading of the two most cited taxonomies in that literature finds no category at all for a cost the supplier moves after adoption. The paper identifies three positions a disabled user can occupy with respect to an access capability, and argues the third is the most exposed: prescribed assistive technology, where obligations attach; a consumer subscription, where the user is a weak party to a contract they cannot negotiate; and a platform procured by an institution, where the capability can be metered or withdrawn in a transaction the disabled user is not a party to at all. The paper distinguishes accommodation repricing from technoableism, which explains how the accommodation came to be a commercial product but does no work on what happens afterward, and it takes up the strongest existing objection, that recent power aware work in accessible computing has already displaced the adoption-as-fit account. It declines to coin a new category of ableism on the ground that the mechanism is already named at both ends by existing literatures. It then builds and runs the instrument capable of measuring the phenomenon without asking disabled people to narrate a cost increase they cannot escape: a longitudinal documentary audit of published vendor pricing artifacts, coded from dated public archive captures. A first pass across 16 vendor surfaces, with one consumer surface coded in full across 12 consecutive quarters, finds the predicted behavior in a form stronger than a price increase. The posted price of the paid tier did not change across three years. The quantity behind it was metered, then re-expressed in a unit not commensurable with the one it replaced, leaving the user without the comparison required to detect that anything had been reduced.
Keywords
- accommodation repricing
- accessibility tax
- disability tax
- generative artificial intelligence
- assistive technology abandonment
- subscription pricing
- switching costs
- technoableism
- crip technoscience
- educational technology procurement
- accessible computing
- documentary audit
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Gilly, Travis. "Accommodation Repricing: Disability, Generative AI Subscriptions, and the Accessibility Tax as a Variable the Vendor Controls." Real Safety AI Foundation Working Paper, August 2026. https://realsafetyai.org/research/4fz3q7/
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References (33)
- Çakır, M. (2021). Retail pass-through of package downsizing. Agribusiness, 38(2), 259–278. https://doi.org/10.1002/agr.21724
- Farrell, J., & Klemperer, P. (2007). Coordination and lock-in: Competition with switching costs and network effects. In M. Armstrong & R. Porter (Eds.), Handbook of Industrial Organization (Vol. 3, pp. 1967–2072). Elsevier.
- Foley, A., & Ferri, B. A. (2012). Technology for people, not disabilities: Ensuring access and inclusion. Journal of Research in Special Educational Needs, 12(4), 192–200. https://doi.org/10.1111/j.1471-3802.2011.01230.x
- Foley, A., & Ferri, B. A. (2026). DISCO-Tech: A framework for resisting ableism in emerging technologies. Teachers College Record, 128(3), 166–194. https://doi.org/10.1177/01614681261444567
- Foley, A., & Melese, F. (2025). Disabling AI: Power, exclusion, and disability. British Journal of Sociology of Education. https://doi.org/10.1080/01425692.2025.2519482
- Glazko, K., Lewis, A., Kosa, B., et al. (2025). Autoethnographic insights from neurodivergent GAI “power users.” In Proceedings of the CHI Conference on Human Factors in Computing Systems. ACM. https://doi.org/10.1145/3706598.3713670
- Gourville, J. T., & Koehler, J. J. (2004). Downsizing price increases: A greater sensitivity to price than quantity in consumer markets (Working Paper). Harvard Business School. https://doi.org/10.2139/ssrn.559482
- Kim, I. K. (2023). Consumers’ preference for downsizing over package price increases. Journal of Economics & Management Strategy, 33(1), 25–52. https://doi.org/10.1111/jems.12548
- Gilly, T. (2026). Accommodation repricing audit [Data set and code]. Real Safety AI Foundation. https://github.com/princesshobbes/accommodation-repricing-audit
- Hamraie, A., & Fritsch, K. (2019). Crip technoscience manifesto. Catalyst: Feminism, Theory, Technoscience, 5(1), 1–33. https://doi.org/10.28968/cftt.v5i1.29607
- Ho, K., Hogan, J., & Scott Morton, F. (2017). The impact of consumer inattention on insurer pricing in the Medicare Part D program. RAND Journal of Economics, 48(4), 877–905.
- Hsueh, S., Van Dusen, D., & Caspi, A. (2025). Minor resistance: The everyday politics and power dynamics of assistive technology adoption. In Proceedings of the International ACM SIGACCESS Conference on Computers and Accessibility. ACM. https://doi.org/10.1145/3663547.3746465
- Jang, J., Moharana, S., & Carrington, P. (2024). “It’s the only thing I can trust”: Envisioning large language model use by autistic workers for communication assistance. In Proceedings of the CHI Conference on Human Factors in Computing Systems. ACM. https://doi.org/10.1145/3613904.3642894
- Johnson, J., Lewis, A., Mankoff, J., & Banner, O. (2026). “I don’t trust it, but I use it”: Navigating trust, privacy, and identity in disabled people’s use of generative AI. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1–17). ACM. https://doi.org/10.1145/3772318.3790652
- Jones, C. T., Rice, C., & Lam, M. (2021). Toward TechnoAccess: A narrative review of disabled and aging experiences of using technology to access the arts. Technology in Society, 65, 101537. https://doi.org/10.1016/j.techsoc.2021.101537
- Judge, S., & Townend, G. (2013). Perceptions of the design of voice output communication aids. International Journal of Language and Communication Disorders, 48(4), 366–381.
- Klemperer, P. (1987). Markets with consumer switching costs. Quarterly Journal of Economics, 102(2), 375–394.
- Klemperer, P. (1995). Competition when consumers have switching costs. Review of Economic Studies, 62(4), 515–539.
- Mullen, K., Xue, W., & Kudumu, M. (2024). “I’m treating it kind of like a diary”: Characterizing how users with disabilities use AI chatbots. In Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility (Article 133, 7 pp.). ACM. https://doi.org/10.1145/3663548.3688549
- Lewis, T., & Yildirim, H. (2005). Managing switching costs in multiperiod procurements with strategic buyers. International Economic Review, 46(4), 1233–1269.
- Mack, K., Martinez, J. J., & Lewis, A. (2025). Modeling accessibility: Characterizing what we mean by “accessible.” In Proceedings of the International ACM SIGACCESS Conference on Computers and Accessibility. ACM. https://doi.org/10.1145/3663547.3746344
- Mack, K., McDonnell, E. J., & Findlater, L. (2022). Chronically under-addressed: Considerations for HCI accessibility practice with chronically ill people. In Proceedings of the International ACM SIGACCESS Conference on Computers and Accessibility. ACM. https://doi.org/10.1145/3517428.3544803
- McNally, K., Wright, K., & Goldkind, L. (2024). Disability expertise and large language models: A qualitative study of autistic TikTok creators’ use of ChatGPT. Social Media + Society, 10(3). https://doi.org/10.1177/20563051241279549
- Ni, W., & Li, J. C. (2026). Mapping the impact of generative AI in higher education: A scoping review of psychological and equity dimensions. Frontiers in Psychology, 17. https://doi.org/10.3389/fpsyg.2026.1856854
- Olsen, S. H., Cork, S. J., & Anders, P. (2022). The disability tax and the accessibility tax. Including Disability, (1), 51–86. https://doi.org/10.51357/id.vi1.170
- Orellano-Colón, E. M., Mann, W. C., & Rivero-Méndez, M. (2015). Hispanic older adults’ perceptions of personal, contextual and technology-related barriers for using assistive technology devices. Journal of Racial and Ethnic Health Disparities, 3(4), 676–686.
- Phillips, B., & Zhao, H. (1993). Predictors of assistive technology abandonment. Assistive Technology, 5(1), 36–45. https://doi.org/10.1080/10400435.1993.10132205
- Rauchberg, J. S. (2022). Imagining a neuroqueer technoscience. Studies in Social Justice, 16(2), 370–388. https://doi.org/10.26522/ssj.v16i2.3415
- Shew, A. (2023). Against technoableism: Rethinking who needs improvement. W. W. Norton.
- Steel, E., Buchanan, R., & Layton, N. (2017). Currency and competence of occupational therapists and consumers with rapidly changing technology. Occupational Therapy International, 2017, 1–5. https://doi.org/10.1155/2017/5612843
- Tang, X., Lin, T., & Li, J. (2026). Cripping AI: Reimagining AI through lived disability experiences. ACM. https://doi.org/10.1145/3805689.3806744
- Xue, W., Kudumu, M., Sriram, S., Mullen, K., Boyd, A., & Gadiraju, V. (2025). Characterizing uses and prompting strategies of LLM-based chatbots among neurodivergent individuals. In Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility. ACM. https://doi.org/10.1145/3663547.3759721
- Waller, A. (2019). Telling tales: Unlocking the potential of AAC technologies. International Journal of Language and Communication Disorders, 54(2), 159–169. https://doi.org/10.1111/1460-6984.12449