Chemnad Khansa, Othman Achraf
Mada Qatar Assistive Technology Center, Doha, Qatar.
Front Artif Intell. 2024 Feb 16;7:1349668. doi: 10.3389/frai.2024.1349668. eCollection 2024.
Digital accessibility involves designing digital systems and services to enable access for individuals, including those with disabilities, including visual, auditory, motor, or cognitive impairments. Artificial intelligence (AI) has the potential to enhance accessibility for people with disabilities and improve their overall quality of life.
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-ACM Digital Library, IEEE Xplore, ScienceDirect, Scopus, and Springer.
The analysis narrowed down to 43 articles, presenting a classification framework based on applications, challenges, AI methodologies, and accessibility standards.
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.
数字无障碍涉及设计数字系统和服务,以使包括残疾人(包括视觉、听觉、运动或认知障碍者)在内的所有人都能使用。人工智能(AI)有潜力增强残疾人的无障碍使用体验并改善他们的整体生活质量。
本系统综述涵盖2018年至2023年的学术文章,重点关注人工智能在数字无障碍方面的应用。最初,从五个学术数据库——美国计算机协会数字图书馆(ACM Digital Library)、电气和电子工程师协会(IEEE)Xplore、科学Direct、Scopus和施普林格(Springer)中筛选出3706篇文章。
分析后缩小至43篇文章,提出了一个基于应用、挑战、人工智能方法和无障碍标准的分类框架。
本研究强调了主要侧重于人工智能驱动的视觉障碍数字无障碍,揭示了在解决言语和听力障碍、自闭症谱系障碍、神经障碍和运动障碍方面的关键差距。这凸显了需要更均衡的研究分布,以确保为所有残疾群体提供公平支持。该研究还指出现有系统缺乏对无障碍标准的遵守,强调了在为残疾人设计解决方案时进行根本性转变的紧迫性。总体而言,本研究强调了无障碍人工智能在防止排斥和歧视方面的重要作用,敦促采取全面的数字无障碍方法以满足不同的残疾需求。