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ML Applications for Web Accessibility: Automated Testing for Interactive Content Elements, Images and Text

AIThority – by Roman Pavlov

Web accessibility is the practice of making digital products, such as websites, more accessible and navigable for all users, including those with disabilities and impairments. Much like designated parking and service ramps, European and U.S. governments have included the internet as a “place of public accommodation,” which must meet accessibility guidelines. Web accessibility covers a broad range of limitations – whether someone is blind or has a broken arm – and accessibility features seek to ensure the same user experience regardless of disability, injury, or impairment.

The genuine necessity of web accessibility cannot be understated because it allows users with diverse disabilities to effectively navigate, understand and use platforms, content, and tools without compromising user experience – which is everything in our modern world. Proper disability accommodation encompasses all digital products, including websites, mobile device applications and educational resources.

Nevertheless, making any digital product accessible is a meticulous process, and that is why experts are looking towards machine learning (ML) as a potential solution. 

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