Artificial Intelligence (AI) can be used to bridge the gap between web accessibility and design. It can provide insights on design aspects, automate accessibility testing, and reduce costs. However, several challenges must be addressed before implementing AI for web accessibility.
It provides insight into design aspects
While people without disabilities may frame the problems and solutions for web accessibility, the perspective of people with cognitive disabilities may be more valuable to researchers and designers. People with cognitive impairments have specific knowledge about the challenges that can hinder accessibility but are often left out of the design process. That is why engaging people with mental disabilities in design and research is vital.
AI is already bringing new ways to create more accessible web experiences are already available. For instance, it can automatically develop descriptive titles for content structures, detect form errors, and translate sign language into text. However, AI will not be able to provide the same level of accessibility as humans. This means that human intelligence is still necessary for most web content.
While research such as that done by accessibe has identified some common accessibility problems, the need for greater accessibility is not likely to diminish with age. For example, while most web accessibility concerns relate to text, many people with cognitive disabilities benefit from audio and video sharing. Also, direct navigation pathways are helpful for people with memory problems.
It can automate testing
Several problems with using automated accessibility testing tools may affect accessibe reviews. Firstly, they often fail to identify all types of accessibility errors. For example, we cannot locate images’ alt text or accurately identify form labels using automated means. This can lead to confusion for screen readers. Additionally, automated accessibility testing tools cannot simulate complex web experiences like a checkout. In contrast, manual testers can replicate the entire process.
In addition, web content is constantly changing, and website page layout and structure are not standardized. Developers often use different frameworks and design styles, resulting in inconsistent results. It’s essential to ensure that your accessibility testing automation can support all possible types of web content.
It can reduce costs
With the recent introduction of AI-powered accessibility remediation tools, companies can reduce the cost of accessibility improvements while at the same time increasing the usability of their websites. AI-powered solutions can also reduce the time and cost of web authoring, which is already becoming more accessible to people with disabilities. In addition, with well-annotated data, AI-powered solutions can also create entirely new types of algorithms.
Another way AI is reducing costs for web accessibility is in the field of speech and text-based interaction. For example, the technology can understand and respond to addresses, significantly improving the user experience. Additionally, AI-driven technology can be applied to chatbots, which are increasingly popular among web users. However, chatbots should be designed to provide both voice and keyboard access. Additionally, they should consider color contrast, orientation, and screen magnification. For example, an AI-based solution uses a rules-based method to determine the accuracy of an image’s alt attribute. When this algorithm is not specific, it is called a separate image recognition algorithm.