Artificial intelligence in digital accessibility - and how we already use it

The digital world is evolving rapidly, and so are the demands for accessibility. It is vital that all people - regardless of their individual needs - have access to digital content. People with disabilities are particularly dependent on accessible digital infrastructure. Artificial Intelligence (AI) offers promising opportunities to overcome barriers and promote digital inclusion. But what exactly does this mean for digital accessibility and how can AI be used in practice?

Automated accessibility testing: efficiency through AI

An important application of AI in digital accessibility is the automation of testing. AI-powered tools such as Google Lighthouse (also available in the Eye-Able® Report Tool) and WAVE help to test websites for accessibility. These tools are based on the Web Content Accessibility Guidelines (WCAG). The WCAG are international standards that define how websites should be designed to be accessible to people with different disabilities. The tools analyse alternative text, contrast ratios and page structure, among other things, to identify barriers. However, it is important to emphasise that automated solutions, such as Google Lighthouse, can only cover part of the accessibility picture and manual testing is still essential to ensure full accessibility.

Eye-Able® also uses AI as part of automated accessibility testing. For example, in the Eye-Able® Audit Tool - which allows website operators to quickly identify the barriers that exist on their site. This uses the Ally AI. This Eye-Able® AI assistant analyses the website and offers individual, actionable solutions that are tailored to the specific barriers. In this way, websites can be efficiently checked for WCAG compliance and improved.

Personalised user experience through machine learning

Another exciting area where AI is playing a key role is in personalising the user experience. People with visual, hearing or motor impairments often have very different and individual needs from digital content. AI can help websites dynamically adapt to these needs by analysing behaviour patterns and automatically optimising user settings. Typically, this is done by training models on user behaviour data to analyse and adjust interactions - for example, text size, contrast or navigation.

However, this area also raises privacy issues. The collection and analysis of usage data for these personalised adjustments must be done in a transparent and responsible way to protect users' privacy. AI-based systems should be designed so that users remain in control of their own data and can give their consent to the collection and use of data.

Speech processing and AI-assisted accessibility

Technologies such as natural language processing (NLP) and voice recognition systems (such as Siri and Alexa) offer new opportunities for people with motor impairments. NLP is a branch of artificial intelligence that aims to understand, analyse and respond to human speech. NLP enables machines to recognise and respond to spoken or written language, making it easier for people with motor impairments to access digital content. They can easily control devices and systems without a mouse or keyboard.

Another area where NLP is important is automatic text generation and adaptation. In some accessibility systems, NLP is used to convert spoken language to text, which can enable the creation of captions or the automatic adaptation of text content. This also makes digital content more accessible for many people, especially those who have difficulty using traditional input devices such as keyboards or mice.

Automated translation and natural language AI

AI can also be used to automatically translate websites. We already have a tool for this in Eye-Able®: AI Website Translation. Websites can be translated into different languages to ensure accessibility for people from different language areas. The AI can not only translate the text, but also assess its readability and comprehension. Users can also manually edit translations to optimise the quality of the text.

Another highlight is the Eye-Able Plain language AI. It makes complex content easier to understand by avoiding difficult words and complex sentence structures.

Challenges and ethical considerations

Despite the many benefits that AI offers in terms of accessibility, there are also challenges that should not go unnoticed. AI systems require large amounts of good quality data to operate reliably. The diversity and representativeness of this data is particularly important, as it determines how accurately and fairly the AI performs its tasks. For example, if data from certain user groups is under-represented, the AI may produce biased results or fail to recognise certain needs. These biases could lead to people with certain disabilities being disadvantaged. Therefore, AI models need to be regularly reviewed and adapted to ensure that they are truly helpful to all user groups.

Another important aspect is ethical responsibility in the development and use of AI. It is crucial that AI models not only meet the needs of the majority, but also take into account the needs of minorities and disadvantaged groups. Companies and developers need to ensure that their AI applications do not discriminate or create barriers for certain groups. This also includes the transparency of algorithms and a continuous evaluation of how AI decisions are made and whether they are ethically justifiable.

The future of accessibility through AI

The future of accessibility is increasingly being shaped by artificial intelligence. AI can not only help to overcome barriers more efficiently, but also offer an individual and personalized user experience. The AI-supported solutions from Eye-Able® are just some of the practical applications. We are already on the way to making the digital world more accessible and inclusive for everyone.

It will be exciting to see how these technologies evolve over the coming years and how they contribute to creating a truly inclusive digital future.