Similarly, natural language processing algorithms can identify and correct language that may be difficult for people with cognitive impairments to understand (Le Glaz et al., 2021). By creating machine-learning algorithms that specifically address the issues of digital accessibility, we can create technology that benefits all users, regardless of their abilities. However, it is crucial that these algorithms are developed with inputs from people with disabilities to ensure that they are effective and meet their needs.<\/p>\n
Akter et al. (2022) examined shared ethical and privacy considerations relevant to people with visual impairments, making a significant contribution to the ethical development of assistive technologies. To our knowledge, no systematic review has comprehensively outlined these research findings, while providing a profound analysis of the research and practice related to the topic of digital accessibility, with a specific focus on AI applications for people with disabilities. However, despite these valuable efforts, no comprehensive systematic review has yet extensively examined the intersection of digital accessibility and AI applications within the existing literature. This study seeks to address this gap by providing an extensive analysis of this field, revealing potential benefits, challenges, and opportunities. The utilization of deep-learning methodologies has been prevalent in several studies, including Royal et al. (2023), which facilitated real-time object recognition and text extraction using deep-learning algorithms.<\/p>\n
Additionally, addressing the adaptability and accessibility of Open Educational Resources (OER), the need for new metadata aligned with Universal Design for Learning guidelines is highlighted (Ingavelez-Guerra et al., 2022). Cimolino et al. (2021) explored the improvement in game accessibility by utilizing multiple frameworks, including universal design, player balancing, and interface adaptation. Within this context, universal design focuses on the creation of products and environments that cater to a broad spectrum of individuals irrespective of their abilities. The analysis narrowed down to 43 articles, presenting a classification framework based on applications, challenges, AI methodologies, and accessibility standards. This systematic review, covering academic articles from 2018 to 2023, focuses on AI applications for digital accessibility. Initially, 3,706 articles were screened from five scholarly databases\u2014ACM Digital Library, IEEE Xplore, ScienceDirect, Scopus, and Springer.<\/p>\n
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Regular reviews and updates of content are therefore vital to ensure that it meets current requirements. Examples of Edge Protection and Handrail Extensions.Four types of edge protection and handrail design are shown. The first ramp (top) labeled „Curb” shows a handrail horizontal projection of 12 inches (305 mm) minimum at the top and bottom of the ramp. Edge protection on both sides of the ramp is a raised surface at least 2 inches (50 mm) high.<\/p>\n
This research emphasizes the predominant focus on AI-driven digital accessibility for visual impairments, revealing a critical gap in addressing speech and hearing impairments, autism spectrum disorder, neurological disorders, and motor impairments. This highlights the need for a more balanced research distribution to ensure equitable support for all communities with disabilities. The study also pointed out a lack of adherence to accessibility standards in existing systems, stressing the urgency for a fundamental shift in designing solutions for people with disabilities. Overall, this research underscores the vital role of accessible AI in preventing exclusion and discrimination, urging a comprehensive approach to digital accessibility to cater to diverse disability needs. Advancements in AI have created new opportunities to enhance digital accessibility for people with disabilities (Hapsari et al., 2017). However, as AI technology progresses, it is crucial to closely examine its impact on accessibility and to ensure that these technologies are developed in an equitable and inclusive manner.<\/p>\n
With the increasing use of AI in all spheres of life, it is crucial to ensure that these technologies are accessible to all individuals. This review presents the current state of the application of AI in the digital accessibility sector and proposes a classification system for identifying accessibility standards and frameworks, challenges, AI methodologies, and functionalities of AI in digital accessibility. A key aspect of creating accessible digital content in today\u2019s era is web design and development. These design templates are already designed to meet many accessibility requirements and provide a solid foundation for an optimal result. Using such templates makes it easier for companies to design accessible digital offerings from the outset.<\/p>\n