In today's digital age, accessibility is not just a nice-to-have feature – it's a fundamental requirement for creating products that can be enjoyed by everyone, regardless of their abilities. When it comes to designing products utilising Artificial Intelligence, ensuring accessibility for users with hearing and sight loss is paramount. In this blog, we'll explore the essential features, considerations and best practices for designing AI products that are inclusive and empowering for all.
Accessibility for Sight Loss: Screen Reader Compatibility
Ensuring compatibility with screen reader software is crucial for users with sight loss who rely on assistive technologies to navigate digital interfaces. AI products should be designed with semantic markup and proper accessibility attributes to ensure that screen readers can accurately interpret and convey the content to users. It is much more expensive and slower to add this later; the best teams build these in as they go and include testing for these attributes in the QA process.
Text-to-Speech (TTS) and Speech-to-Text (STT) Capabilities
Incorporating robust text-to-speech and speech-to-text capabilities is essential for making Artificial Intelligence products accessible to people with sight loss, it is also a huge benefit for those less familiar with Digital interaction. TTS functionality allows users with sight loss to have text content read aloud, while STT functionality enables those with sight loss to interact with the product using spoken language. Care must also be taken to ensure that these functionalities do not conflict with other accessibility tools that may be in use.
There are many excellent AI tools available in this space, but do ensure that your chosen speech-to-text tool will handle the languages and accents of your intended end user base.
Sight Loss Inclusion: High Contrast and Large Font Options
To help make your product inclusive for users with sight loss, providing high contrast colour schemes and the option to enlarge font sizes can significantly improve readability and usability. AI products should offer customisable settings that allow users to adjust the visual elements according to their preferences and needs. To reduce the potential risk of fatigue, these settings should ideally be remembered for each user.
Voice Command Navigation
Voice command navigation enables users with sight loss to navigate through AI products using spoken commands, speech recognition provides an intuitive and hands-free experience. Implementing natural language processing capabilities allows users to interact with the product in a conversational manner, making it more accessible and user-friendly.
Additionally, in the real world, this capability is a huge benefit to users using mobile interfaces, proving that good accessible design is not just for people with disabilities.
Fairness for all: Alternative Input Methods
In addition to voice commands, AI products should support alternative input methods such as gesture controls, keyboard shortcuts, and tactile interfaces. These alternative input methods provide users with diverse abilities the flexibility to interact with the product in a way that suits their needs and preferences.
Audio Descriptions and Captions
Including audio descriptions and captions for multimedia content such as videos and images is essential for users with sight loss. Audio descriptions provide verbal descriptions of visual elements, while captions provide synchronised text for spoken content, ensuring that all users can access and understand multimedia content seamlessly further helping to make an inclusive product.
Datasets have to Suitably Represent Minority Groups and avoid Biases
Where machine learning is performed directly to build specific AI models or Large Language Models (LLMs) are used it is vital to ensure they are trained on data that represents minority groups, such as those who particularly benefit from Accessibility features. Where you are building your own models, ensure that data collection and training include suitable proportions that represent all of your target user groups. Where using pre-built models, get your data scientists to check what data that has been used to train them and validate that this is representative of your users.
If your product requires model development it is important to remember that the model will need to be maintained, feeding it with up-to-date data. Each time this happens the data will need to be assured for inclusivity and the whole solution tested against the updated model.
User Testing with Diverse Audiences
Conducting comprehensive user testing with diverse audiences, including users with hearing and sight loss, is essential for identifying accessibility barriers and refining the user experience. Capturing feedback from real users allows product teams to address usability issues and ensure that the AI product meets the needs of all users. You may well find that these inclusive practices will uncover use cases that you hadn't considered, further improving your product for all users groups.
How Do I Know my AI Product is and will Continue to Deliver Inclusivity?
Standard Quality Assurance processes and tools are not sufficient to test AI systems. Additional approaches are required to check the validity of elements of the product that utilise Generative AI. Additionally procedures will be required to handle model changes which will happen independently from managed product releases.
This area is a particular challenge for AI products as the relative immaturity of the industry means that there is a lack of tooling available and more effort than expected will be required to either manually test or to custom build tooling.
Inclusive AI Product Design: Summary
Designing AI products that are accessible for users with hearing and sight loss requires thoughtful consideration of their unique needs and preferences. By incorporating features such as text-to-speech, high contrast options, voice command navigation and alternative input methods, AI products can provide a truly inclusive experience for all users - delivering a product with potentially wide reaching societal impact. Our research has shown that products built with these features included from the outset are also better for users without disabilities.
The single most important best practice is to design inclusion in from the start, not only is it cheaper and easier than retro-fitting, this inclusive approach leads to a more cohesive finished product.
Together, let's strive to build a more accessible and inclusive digital future for everyone.
ConnectingYouNow incorporates inclusive design principles from the outset, ensuring that the platform is accessible to users with diverse needs. This includes features such as talk or type options and screen reader compatibility, fostering a more inclusive user experience.