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• The Perceptual Gap: Why We Need Accessible XAI for Assistive Technologies

  Shadab H. Choudhury · 2026 · Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (CHI EA '26)

  Choudhury (University of Maryland, Baltimore County) presents a position paper and targeted literature review arguing that explainable AI (XAI) — the body of methods that help users understand why a black-box model produced a particular output — is fundamentally inaccessible to…

  explainable AI · XAI · artificial intelligence · blind and low vision · deaf and hard of hearing

• Human-Centered Explainable AI for Brain-Computer Interface-driven Rehabilitation

  Param Rajpura · 2026 · Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (CHI EA ’26)

  This CHI Extended Abstract presents a doctoral research agenda developing human-centered explainable AI (HCXAI) frameworks for brain-computer interfaces (BCIs) used in stroke rehabilitation. Rajpura argues that current BCI systems prioritize technical performance, such as…

  brain-computer interface · explainable AI · stroke rehabilitation · aphasia · human-centered AI

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