In her How to Use AI to Build Accessible Products presentation at Smashing Conf New York, Carie Fisher discussed using AI coding tools to test and suggest fixes for accessibility issues in Web pages. Here's my notes on her talk.
- AI is everywhere. You can use it to write content, code, create images, and more. It impacts how everyone will work.
- But ultimately, AI is just a tool but it might not always be the right one. We need to find the tasks where it has the potential to add value.
- Over 1 billion people on the planet identify as having a disability. Accessible code allows them to access digital experiences and helps companies be complaint with emerging laws requiring accessible Web pages and apps. Businesses also get SEO, brand, and more benefits from accessible code.
- AI tools like Github Copilot can find accessibility issues in seconds consistently, especially compared to the manual checks currently being done by humans. AI can also spot patterns across a codebase and suggest solutions.
- Existing AI coding tools like Github Copilot are already better than Linters for finding accessibility issues.
- AI can suggest and implement code fixes for accessibility issues. It can also be added to CI/CD pipelines to check for accessibility issues at the point of each commit. AI can also serve as an accessibility mentor for developers by providing real-time suggestions.
- More complex accessibility issues especially those that need user context may go unfound when just using AI. Sometimes AI output can be incomplete or hallucinate solutions that are not correct. As a result, we can't over rely on just AI to solve all accessibility problems. We still need human review today.
- To improve AI accessibility, provide expanded prompts that reference or include specifications. Code reviews can double check accessibility suggestions from AI-based systems. Regularly test and refine your AI-based solutions to improve outcomes.
- Combing AI and human processes and values can help build a culture of accessibility.