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AI Fairness for People with Disabilities: Point of View

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arxiv 1811.10670 v1 pith:XTY64MAY submitted 2018-11-26 cs.AI cs.CY

classification cs.AIcs.CY
keywords disabilitiesfairnesspeopledisabilitywaysadaptalwaysapplications
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We consider how fair treatment in society for people with disabilities might be impacted by the rise in the use of artificial intelligence, and especially machine learning methods. We argue that fairness for people with disabilities is different to fairness for other protected attributes such as age, gender or race. One major difference is the extreme diversity of ways disabilities manifest, and people adapt. Secondly, disability information is highly sensitive and not always shared, precisely because of the potential for discrimination. Given these differences, we explore definitions of fairness and how well they work in the disability space. Finally, we suggest ways of approaching fairness for people with disabilities in AI applications.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Beyond wheelchairs and blindfolds: Investigating disability stereotypes in T2I models with INCLUDE-BENCH

    cs.CV 2026-07 conditional novelty 7.0 of 10

    T2I models systematically depict disability via wheelchair and blindfold tropes with reduced diversity and SCM scores that mirror real-world high-warmth/low-competence stereotypes.

  2. AI and Accessibility: A Discussion of Ethical Considerations

    cs.CY 2019-08 unverdicted novelty 2.0 of 10

    A viewpoint article that outlines the ethical challenges of AI for people with disabilities and urges responsible development.

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