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AI and Accessibility: A Discussion of Ethical Considerations

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arxiv 1908.08939 v3 pith:L6UAK6EF submitted 2019-08-21 cs.CY cs.AIcs.HC

classification cs.CYcs.AIcs.HC
keywords peopleaccessibilitymightbarrierschallengesdisabilitiesdisabilityethical
verification ladder T0 review T1 audit T2 compute T3 formal
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According to the World Health Organization, more than one billion people worldwide have disabilities. The field of disability studies defines disability through a social lens; people are disabled to the extent that society creates accessibility barriers. AI technologies offer the possibility of removing many accessibility barriers; for example, computer vision might help people who are blind better sense the visual world, speech recognition and translation technologies might offer real time captioning for people who are hard of hearing, and new robotic systems might augment the capabilities of people with limited mobility. Considering the needs of users with disabilities can help technologists identify high-impact challenges whose solutions can advance the state of AI for all users; however, ethical challenges such as inclusivity, bias, privacy, error, expectation setting, simulated data, and social acceptability must be considered.

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Cited by 1 Pith paper

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

  1. Surfacing Variations to Calibrate Perceived Reliability of MLLM-generated Image Descriptions

    cs.HC 2025-07 conditional novelty 6.0 of 10

    Surfacing variations across multiple MLLM image descriptions increases blind and low vision users' detection of unreliable claims and reduces their over-trust in a single AI description.

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