Multi-turn neural transparency using behavioral vectors and dynamic visualizations improves user anticipation and evaluation of LLM trait expression while reducing overconfidence, per a randomized study with 246 participants.
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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.
A qualitative study of a provotype shows that adding transparency and control features to AI recommender interfaces helps users understand personalization, address filter bubble concerns, and build trust.
citing papers explorer
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Multi-Turn Neural Transparency: Surfacing Neural Activations Improves User Calibration to LLM Behavioral Drift
Multi-turn neural transparency using behavioral vectors and dynamic visualizations improves user anticipation and evaluation of LLM trait expression while reducing overconfidence, per a randomized study with 246 participants.
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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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Rethinking User Empowerment in AI Recommender System: Innovating Transparent and Controllable Interfaces
A qualitative study of a provotype shows that adding transparency and control features to AI recommender interfaces helps users understand personalization, address filter bubble concerns, and build trust.