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125 points robin_reala | 1 comments | | HN request time: 0.288s | source
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simonw ◴[] No.46203241[source]
Something I'm desperately keen to see is AI-assisted accessibility testing.

I'm not convinced at all by most of the heuristic-driven ARIA scanning tools. I don't want to know if my app appears to have the right ARIA attributes set - I want to know if my features work for screenreader users.

What I really want is for a Claude Code style agent to be able to drive my application in an automated fashion via a screenreader and record audio for me of successful or failed attempts to achieve goals.

Think Playwright browser tests but for popular screenreaders instead.

Every now and then I check to see if this is a solved problem yet.

I think we are close. https://www.guidepup.dev/ looks extremely promising - though I think it only supports VoiceOver on macOS or NVDA on Windows, which is a shame since asynchronous coding agent tools like Codex CLI and Claude Code for web only run Linux.

What I haven't seen yet is someone closing the loop on ensuring agentic tools like Claude Code can successfully drive these mechanisms.

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PebblesHD ◴[] No.46203374[source]
Rather than improving testing for fallible accessibility assists, why not leverage AI to eliminate the need for them? An agent on your device can interpret the same page a sighted or otherwise unimpaired person would giving you as a disabled user the same experience they would have. Why would that not be preferable? It also puts you in control of how you want that agent to interpret pages.
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1. 8organicbits ◴[] No.46204152[source]
The golden rule of LLMs is that they can make mistakes and you need to check their work. You're describing a situation where the intended user cannot check the LLM output for mistakes. That violates a safety constraint and is not a good use case for LLMs.