The Future of Generative AI and Increased Accessibility

Human hand touching finger tips to the finger tips of a robotic hand. Photo by cottonbro studio

What Really Is Artificial Intelligence?

To explore how Artificial Intelligence (AI) may be used to increase accessibility, it’s important to understand the distinctions between its subsets. AI is a broad term encompassing systems and algorithms designed to perform tasks that typically require human intelligence. This includes Machine Learning and Generative AI, subsets that are distinct from Narrow AI (sometimes referred to as “Weak AI”).

Narrow AI is built for specific tasks, such as speech recognition, data analysis, or playing chess. These systems follow predefined rules or patterns to provide outputs based on the input they receive. On the other hand, Generative AI is designed to create new, original content—whether it be text, images, music, or code—by identifying patterns in large sets of training data. While Narrow AI focuses on recognizing existing patterns, Generative AI can produce entirely novel outputs, making it a transformative technology for creative and personalized applications.

In practice, both Narrow AI and Generative AI can be combined. For example, a system might use Narrow AI to recognize a user’s behavior and then employ Generative AI to create customized content based on that behavior.

Image of an all black 2-dimensional side profile of a head with google eyes throughout the brain and neck. AI is written above the head. Photo by Tara Winstead

What Does Accessibility Look Like Now?

Despite technological advances, fewer than 3% of websites currently offer fully accessible options. Accessibility features, such as enhanced color contrast, text-to-speech, and voice activation, are becoming more common but are often not implemented effectively. As a result, many websites and software fail to fully comply with accessibility standards, limiting the utility of these features.

For some individuals with disabilities, unemployment rates can reach as high as 80%. AI technologies hold promise in bridging this gap—not only by supporting productivity and communication but also by streamlining job searches and offering tools that improve daily functioning. Some estimates suggest that increasing accessibility through AI could assist with up to 40% of the work tasks performed by people with disabilities.

Image of moss, sticks, and flowers floating in the shape of a brain. Photo by Google DeepMind

How Has AI Been Useful Thus Far?

A compelling example of AI’s impact on accessibility comes from Virginia Representative Jennifer Wexton, who used AI-based voice recovery technology after being diagnosed with Progressive Supranuclear Palsy. A startup specializing in voice recreation enabled her to communicate once more, using a synthetic voice that mirrored her own.

This is only one of many applications where AI is enhancing accessibility:

• Wearable Health Monitoring: Devices like Fitbits and Apple Watches employ AI to detect health anomalies, offering real-time insights for managing conditions.
• Speech Recognition and Live Subtitles: AI-driven speech recognition tools can transcribe live audio into subtitles, greatly aiding those who are deaf or hard of hearing.
• Image Recognition: For those with visual impairments, AI-powered image recognition can identify objects, colors, and scenes, providing audio descriptions of their environment.
• Alternative Text for Media: Generative AI can produce detailed alternative text descriptions for visual or auditory media, enhancing the content’s accessibility for those who may be unable to see or hear it.

Image of a woman being given a flower by a robotic device. Photo by Pavel Danilyuk

However, it’s essential that individuals with disabilities remain at the center of the design process for AI solutions. Generative AI, in particular, carries risks for vulnerable users due to potential biases in training data. Algorithms trained on unrepresentative datasets may unintentionally discriminate against those who deviate from the “average” user profile. It is therefore crucial to develop AI systems with diverse and representative data to ensure they serve all users equitably.

What Are the Implications for People Without Disabilities?

AI technologies designed for accessibility often have wider benefits for all users. For example, voice assistants, real-time translation, and personalized recommendations—initially designed to support those with disabilities—can enhance usability and convenience for everyone. Generative AI can generate detailed audio descriptions of surroundings, create personalized user interfaces, and transform how people interact with technology in various contexts.

These advancements could pave the way for new applications in biofeedback, media generation, and communication, making technology more intuitive and adaptable for users of all abilities.

Image of a tunnel with vibrant colored walls (blues, greens, and reds). The walls have different shapes as well as arrows and x signs. Photo by Google DeepMind

How Will Artificial Intelligence Change the Frenalytics Software?

Frenalytics is committed to delivering a user-centered experience, and AI has the potential to significantly enhance this mission. Generative AI and Machine Learning could be employed to personalize lessons based on past user responses, dynamically adjusting content to target areas needing improvement. This personalized approach can optimize learning outcomes and engagement.

Moreover, AI could introduce new ways to interact with Frenalytics software, including improved language translation, text-to-speech, and image-to-speech functionalities, all aimed at fostering a more inclusive and adaptive learning environment.

Generative AI holds the promise of transforming accessibility and creating a more inclusive world. By considering the ethical implications, addressing data biases, and centering the needs of all users, AI can be harnessed responsibly to empower individuals with disabilities—and ultimately enhance experiences for everyone.

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