AI for Accessibility: A Case Study of Enhancing Library Services for Users With Disabilities

AI for Accessibility: A Case Study of Enhancing Library Services for Users With Disabilities

Henry S. Kishore, D. Solomon Paul Raj, K. R. Senthilkumar
Copyright: © 2024 |Pages: 12
DOI: 10.4018/979-8-3693-5593-0.ch015
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Abstract

This chapter examines integrating artificial intelligence (AI) technologies to enhance library services for users with disabilities, aiming to contribute to the accessibility and inclusivity of library resources. The study adopts a mixed-methods approach, combining quantitative user experience surveys with qualitative interviews to assess the impact of AI-driven tools—such as voice recognition, text-to-speech, and AI-powered search and recommendation systems—on the accessibility of library services for individuals with visual, auditory, and mobility impairments.
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Introduction

Integrating artificial intelligence (AI) into various sectors has been a transformative force, reshaping how services are delivered and experienced. Among the many areas benefiting from AI's potential, library services stand out, especially in enhancing accessibility for users with disabilities. The significance of libraries extends beyond their role as repositories of knowledge; they are vibrant community hubs that offer access to information, technology, and spaces for public discourse. However, for individuals with disabilities, libraries can pose unintended barriers to access and participation. This paper explores AI's pivotal role in enhancing library services for users with disabilities, focusing on the intersection of technology and accessibility to foster an inclusive library experience.

Regarding enhancing library services for users with disabilities, AI technology can be pivotal in ensuring accessibility and inclusivity. By leveraging AI tools, libraries can provide personalised services and accommodations for individuals with disabilities, ultimately creating a more welcoming and supportive environment. In this case study, we will explore the implementation of AI-powered solutions to improve the accessibility of library services, highlighting the impact and benefits of integrating advanced technologies to meet the diverse needs of all library patrons.

Background and Significance

Libraries have long advocated for inclusivity and accessibility, ensuring that all individuals, regardless of their abilities, have equal access to information and services. Digital technology has provided libraries new tools to enhance accessibility, yet challenges persist. Users with disabilities often encounter physical, sensory, and digital barriers that hinder their full participation in the library's offerings. The significance of addressing these challenges cannot be overstated; enhancing accessibility in libraries aligns with legal and ethical mandates and enriches the library experience for all users, promoting diversity, equity, and inclusion within the community.

Accessibility, in the context of library services, encompasses a broad spectrum of considerations designed to remove barriers and enable all users to access information and services effectively. This includes physical access to library buildings and resources, sensory access to materials in various formats, and digital access through adaptive technologies and user-friendly interfaces. The importance of accessibility within libraries lies not only in compliance with legislation such as the Americans with Disabilities Act (ADA) but also in the fundamental library principle of providing equitable access to information for all community members.

AI Technologies and Accessibility Enhancement

Recent advancements in AI technology offer promising solutions to accessibility challenges in libraries. AI can be leveraged to develop and implement tools and services that adapt to the needs of users with disabilities, thereby personalising the library experience and ensuring equitable access. Among the AI technologies with the potential to enhance accessibility are:

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    Natural Language Processing (NLP): Enables the development of voice-activated assistants and real-time transcription services, aiding users with visual impairments or learning disabilities.

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    Computer Vision: Powers applications that can interpret visual information, such as text and images, into accessible formats, assisting users with visual impairments.

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    Machine Learning (ML): Facilitates the creation of adaptive interfaces and personalised recommendation systems that cater to each user's unique preferences and needs, including those with cognitive disabilities.

These technologies aim to mitigate existing barriers and envision a future where library services are inherently designed with accessibility in mind.

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