This course aims to educate learners on the importance of accessibility in the context of artificial intelligence. The learning outcomes include understanding human-computer interaction, challenging ability assumptions, designing for users with disabilities, and implementing accessibility features such as alt text and audio CAPTCHAs. The course covers topics like dyslexia detection, making memes accessible, and designing for ability outliers. The teaching method involves lectures and real-world examples, with a focus on practical applications. The intended audience for this course includes individuals interested in technology, design, accessibility, and artificial intelligence.
Overview
Syllabus
Introduction.
Human-Computer Interaction.
The Long Slog Against Ability Assumptions.
What does a screen reader do?.
Alt Text Today.
Hiding Accessibility.
First and Second Class Abilities.
Designing What Users Don't Want.
Discoverability.
Help, my semantics became pixels.
Audio CAPTCHAs and Screen Readers.
People with Disabilities as Early Adopters.
Machine Learning Arcs and Cycles.
Designing for Ability Outliers.
Dyslexia Detection.
Making Memes Accessible.
Real-World Devices.
Real-World Touchscreens.
Adding Risk-Free Exploration to Legacy Touchscreens.
Blind Participant #5 Completing task with app guidance.
Taught by
Stanford Online
