Artificial Intelligence and Digital Accessibility

Artificial Intelligence (AI) has the potential to play a crucial role in enhancing digital accessibility for people with disabilities. It has the potential to transform the way we live, work, and interact with technology. By leveraging AI, we can unlock new possibilities and address complex challenges.  

However, there is a lack of awareness and understanding of how AI actually works and how to make it accessible for everyone. We thought a series of blog posts might be useful. So here is the first one explaining some of the basics of AI. 

Artificial Intelligence (AI) refers to computer systems that can perform tasks that would typically require human intelligence. These tasks can include learning, problem-solving, understanding language, and making decisions. AI systems are designed to analyse vast amounts of data, identify patterns, and make predictions or recommendations based on that information. 

Data Sets 

Artificial Intelligence needs large amounts of data to ‘train’ the systems. This data comes from a variety of places, depending on the system. The data may come from the Internet, business and customer data, social media and AI can now create synthetic data. Unfortunately, because disabled people are not often represented in mainstream media content, there is a potential that some data sets are biased. 

Machine Learning 

Machine learning uses this existing data to make predictions and draw conclusions based on what has happened previously. Predictive text, for example, works on the basis of how sentences are structured and predicts the words most likely to come next. Machine Learning models can learn from user interactions and preferences to personalise web experiences, making websites more intuitive and tailored to the specific needs of individuals with disabilities. By adapting to individual requirements, AI-powered systems can enhance usability and ensure a more accessible interface for all users. 

Natural Language Processing (NLP) 

Using machine learning, NLP interprets written or spoken language and responds back. This is how Alexa or Siri can ‘hear’ what you say, interpret your request and provide the answer. NLP makes it easier for individuals with disabilities to interact with websites using speech recognition, voice commands, or alternative input methods. This enables seamless communication and improves the accessibility of web content for individuals with diverse needs. 

Generative AI 

Generative AI systems create original content like words, images and code. Generative AI uses existing data reworking it into something original. For example, when ChatGPT is asked a question it uses data it already has to put together a unique response. Generative AI can be used by people who are blind or low vision to create unique images that meet their criteria. 

Computer Vision 

Computer vision is required for AI to interpret the world visually and checks with the data and rule sets to decide what it is ‘seeing.’  Automated captions and apps that support Blind people use Computer Vision. AI algorithms can analyse images, videos and the real world to recognise and describe visual content, providing text descriptions or alternative formats for individuals with visual impairments. This allows them to access and understand the visual elements of web pages, ensuring a more inclusive browsing experience. 

Speech Recognition 

Speech recognition is the technology that recognises human speech and can turn it into text. Speech recognition is needed for NLP systems like Alexa or Siri to take the words and process them. AI speech recognition can automate the process of transcribing and captioning audio and video content, benefiting individuals with hearing impairments and those who prefer to consume content in a text-based format. This improves access to multimedia content, making it accessible to individuals who rely on captions or transcripts. 

Ensuring that these AI systems are designed in an accessible way for people with disabilities is essential for promoting inclusivity and equal access. If you’d like to know more about making your AI systems inclusive, reach out or read our next blog Design inclusive artificial intelligence systems.