How can you use artificial intelligence for accessibility?

1 Speech recognition

Speech recognition is the ability of a machine or software to identify and convert spoken words into text or commands. Speech recognition can improve the accessibility of educational technology by allowing learners to interact with content and applications using their voice, rather than typing or clicking. For example, you can use speech recognition to dictate your notes, search for information, control your device, or create captions for videos. Speech recognition can also help learners with hearing impairments, dyslexia, or language barriers to access audio content and feedback.

2 Text analysis

Text analysis is the process of extracting and interpreting meaning from written or spoken text using natural language processing (NLP), a branch of AI that deals with human language. Text analysis can improve the accessibility of educational technology by enabling learners to access text content in different formats and languages. For example, you can use text analysis to generate summaries, keywords, or questions from text, translate text into other languages, or convert text into speech or images. Text analysis can also help learners with visual impairments, reading difficulties, or cognitive disabilities to comprehend and engage with text content.

3 Image recognition

Image recognition is the ability of a machine or software to identify and classify objects, faces, scenes, or emotions in images or videos using computer vision, a branch of AI that deals with visual information. Image recognition can improve the accessibility of educational technology by providing learners with alternative ways to access visual content and feedback. For example, you can use image recognition to create descriptions, labels, or captions for images or videos, recognize emotions or gestures in videos, or generate images or videos from text or speech. Image recognition can also help learners with visual impairments, attention disorders, or social skills deficits to perceive and interpret visual content.

4 Adaptive learning

Adaptive learning is the ability of a machine or software to customize the learning experience for each learner based on their individual characteristics, goals, preferences, and performance using machine learning, a branch of AI that learns from data. Adaptive learning can improve the accessibility of educational technology by providing learners with personalized and flexible learning paths and support. For example, you can use adaptive learning to adjust the difficulty, pace, content, or feedback of the learning activities, recommend resources or strategies based on the learner's needs or interests, or monitor and evaluate the learner's progress and outcomes. Adaptive learning can also help learners with learning disabilities, motivation issues, or diverse learning styles to achieve their learning goals.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?