High agreeableness in LLM voice assistants increases older adults' empathy perceptions and real-time explanations outperform history-based ones, but personality does not affect perceived intelligence.
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A qualitative-to-quantitative scoring framework is proposed to evaluate how well model-agnostic XAI methods support EU AI Act explainability requirements.
citing papers explorer
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The Differential Effects of Agreeableness and Extraversion on Older Adults' Perceptions of Conversational AI Explanations in Assistive Settings
High agreeableness in LLM voice assistants increases older adults' empathy perceptions and real-time explanations outperform history-based ones, but personality does not affect perceived intelligence.
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Assessing Model-Agnostic XAI Methods against EU AI Act Explainability Requirements
A qualitative-to-quantitative scoring framework is proposed to evaluate how well model-agnostic XAI methods support EU AI Act explainability requirements.