The research identifies a 'modality gap' and a 'self-blame' phenomenon in blind users' interactions with agentic AI, advocating for non-visual, blame-aware explanation frameworks.
Claggett, Robert E
2 Pith papers cite this work. Polarity classification is still indexing.
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A validated survey instrument grounded in real GenAI incidents reveals public perceptions of failure modes, risks, and stakeholder responsibilities, showing potential for guiding AI literacy efforts.
citing papers explorer
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Explainable AI for Blind and Low-Vision Users: Navigating Trust, Modality, and Interpretability in the Agentic Era
The research identifies a 'modality gap' and a 'self-blame' phenomenon in blind users' interactions with agentic AI, advocating for non-visual, blame-aware explanation frameworks.
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What People See (and Miss) About Generative AI Risks: Perceptions of Failures, Risks, and Who Should Address Them
A validated survey instrument grounded in real GenAI incidents reveals public perceptions of failure modes, risks, and stakeholder responsibilities, showing potential for guiding AI literacy efforts.