Introduction
AI has the potential to transform many domains and industries across education, health, entertainment, and business. By enabling new ways to interact, communicate, and assist, AI can also offer new opportunities and solutions for accessibility.
However, AI also poses ethical and social challenges for accessibility. These challenges include managing AI systems for privacy, fairness, accountability, inclusiveness, and transparency. If AI isn't done responsibly, it could create new barriers or risks for people with disabilities, such as the digital divide, bias or discrimination, and the loss of control or agency. It's important to understand the principles and practices of responsible and inclusive AI for accessibility.
Which AI technologies do accessible solutions use?
Simply put, AI is software that imitates human behaviors and capabilities. Developers regularly use these key AI technologies to create accessible solutions:
- Machine learning: The way we "teach" a computer model to make predictions and draw conclusions from data. This technology is often the foundation for an AI system.
- Computer vision: Capabilities within AI to interpret the world visually through cameras, video, and images.
- Natural language processing: Capabilities within AI for a computer to interpret written or spoken language and to respond in kind.
- Speech recognition: Technology that enables a program to process human speech into a written format. It's also known as automatic speech recognition (ASR) or speech-to-text.
- Generative AI: Capabilities within AI that create original content in various formats, including natural language, images, and code.