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May 9, 2026International Journal of Human-Computer Interaction0 citations

Conversational AI for Digital Accessibility: An Experimental Study Involving Blind and Low Vision Users

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AEAndrea EspositoRLRosa LanzilottiMMMaristella Matera

Key Points

  • This study aims to evaluate how conversational AI can enhance digital accessibility for blind and low vision users compared to traditional screen readers.
  • Experimental study involving 30 blind and low vision participants.
  • Comparison of user experience with conversational AI versus screen reader technology.
  • Focus on user needs and trust in AI-designed systems.
  • Conversational AI improved the browsing experience of participants compared to using screen readers.
  • Participants reported increased satisfaction and usability with the AI-based interaction.
  • The study highlights the importance of user-centered design in developing assistive technologies.

Abstract

Digital inclusion is a fundamental right and a “must-have” for access to knowledge, education, and work. Many individuals living with disabilities or limited digital skills face digital barriers that determine inequalities and discrimination. Accessible digital services are therefore essential to guarantee everyone’s right to information and full societal inclusion. Nevertheless, the Web remains largely a visual experience, inadequate for many users. Assistive technologies, such as screen readers, can help, but not without problems. Conversational Artificial Intelligence and Large Language Models have emerged as technologies for inclusive interaction with digital services. This article presents an experimental study involving 30 BLV participants to explore the benefits a new AI-based paradigm would bring to the browsing experience of BLV people compared to screen readers. This aligns with a human-centered view of AI, which prioritizes users’ needs and trust over the powerful, autonomous tools that the users do not perceive as safe.

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Cite This Study

Esposito et al. (2026) studied this question.

synapsesocial.com/papers/69fece83b9154b0b82875f1dhttps://doi.org/10.1080/10447318.2026.2659951
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