The Role of New-Age AI in Website Accessibility

The Role of New-Age AI in Website Accessibility

There is a growing need to incorporate website accessibility in the designing and development process. The increasing numbers of ADA lawsuits for inaccessible websites should be enough warning for American businesses to take action.

However, there is an evident reluctance in business owners to take the necessary measures for website accessibility. We have noticed that ignorance is the prime reason behind American business websites that are often left inaccessible to people with disabilities.

But the second most widespread reason is the exorbitant cost of redesigning or recoding a website entirely for accessibility. There are cheaper overlays and plug-ins available in the market, but they have a bad reputation for not meeting most of the requirements for web accessibility.

That is where AI and machine learning makes a difference. But can AI unlock the way to complete and absolute accessibility compliance? That is what we are here to discuss.

AI-Enhanced Accessibility Audits

Accessibility testers and scanners have been around for some time now. However, recently AI has drastically improved their efficiency and accuracy. The auditing tools can now scan through a lot of web pages and content to detect any accessibility shortcomings without the need for manual testing.

Needless to say, one needs automated tools to execute AI tests and audits because it needs to compare the actual results with the expected standards. Those who have used AI technology to scan accessibility problems describe it as an easy, fast, and accurate way to detect any problem early on.

These audits generate a report once the scan is complete to flag the inaccessible shortcomings based on the current WCAG 2.1 standards. The tools usually correspond with the current WCAG standards to identify and compare the web accessibility issues present on a website.

The technology is also used to design tools that deduce accessible documents, such as Microsoft Accessibility Checker or Adobe Accessibility Checker. These tools can automatically detect and rectify any accessibility problems before publishing or sending a document.

Some people also use Adobe InDesign to create accessible files for cross-media publications. For example, a company may need to produce an end of year report with several graphs and images.

They can use InDesign to optimize the accessibility of all the elements present in the report before generating a PDF or an HTML document. Some tools also use AI and machine learning technology to create accessible texts, videos. Braille, and other documents.

AI-Powered Accessibility Tools

The latest use of AI technology for web accessibility is to create customized JavaScript overlay tools that can work without disturbing the underlying source code. accessiBe is one of the market leaders for AI-based accessibility tools and has more than 100,000 satisfied customers.

Their technology can identify and add missing accessibility elements like alternative texts for images or missing HTML attributes. It can also detect and fix issues related to icons, buttons, navigation roles, and landmarks for any website. The remediation makes the website compliant with ADA and WCAG criteria.

These tools are excellent for business owners and developers to understand the impact brought by web accessibility. The technology is ideal for organizations under pressure to fix existing accessibility problems on their website due to an ADA lawsuit or a demand letter.

The software can make any website accessible within a short time for organizations without a dedicated web development team. These tools also work in tandem with the current WCAG 2.1 standards and use an API to correspond with the guideline data.

Using Machine Learning for Visual Accessibility

AI technology is used for people who are blind or visually impaired and need screen reader support. It uses machine learning to identify the visual elements present in an image and then corresponds with a larger database to make sense of what is present in the picture.

The database has segregation for several categories, which helps the technology deduce the details in the picture. Once the image has been tagged appropriately, the screen reader software can read the alternative text to a blind or visually impaired user.

The machine learning technology used for image recognition has helped several businesses with large visual databases to execute and scale their operations. For example, the social media giant Facebook has been using object recognition to generate automated alt-text since 2016. However, the technology is still under development, so businesses should crosscheck the results before publication.

The idea of using automated software to scan and check a lot of webpages or content is appealing for business owners and developers. We can expect to see further advancements soon owing to several reasons.

For instance, the WCAG standards are due for changes in 2021, and the technology will have to adjust to WCAG 2.2 or 3.0 guidelines in the near future. However, the solutions developed by accessibility start-ups are adequate to achieve compliance for now. We are sure that these start-ups will develop their technology to keep up with the release of new standards.