Agency in sustained human-AI chatbot talks emerges as co-constructed turn-by-turn through boundary-setting and intention-steering, organized in a new 3-by-4 framework of actors and actions.
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Malleable Prompting reifies subjective preferences from natural language into GUI widgets and modulates LLM token probabilities during decoding to enable controllable generation, with a user study showing improved precision and perceived controllability over standard prompting.
Narrix helps novices identify and reuse narrative strategies from examples through visualization and strategy-steered generation, improving retention, confidence, and adaptation over chat interfaces in a 12-person study.
Chaplains view AI chatbots as unable to provide attuned pastoral care for non-clinical emotional needs, based on themes of listening, connecting, carrying, and wanting.
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.
Attitude-congruent AI dialogues reduce immediate affective and opinion polarization more than incongruent ones, while incongruent dialogues increase cognitive trait empathy over two weeks.
citing papers explorer
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Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interaction
Agency in sustained human-AI chatbot talks emerges as co-constructed turn-by-turn through boundary-setting and intention-steering, organized in a new 3-by-4 framework of actors and actions.
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From Words to Widgets for Controllable LLM Generation
Malleable Prompting reifies subjective preferences from natural language into GUI widgets and modulates LLM token probabilities during decoding to enable controllable generation, with a user study showing improved precision and perceived controllability over standard prompting.
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Narrix: Remixing Narrative Strategies from Examples for Story Writing
Narrix helps novices identify and reuse narrative strategies from examples through visualization and strategy-steered generation, improving retention, confidence, and adaptation over chat interfaces in a 12-person study.
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Chaplains' Reflections on the Design and Usage of AI for Conversational Care
Chaplains view AI chatbots as unable to provide attuned pastoral care for non-clinical emotional needs, based on themes of listening, connecting, carrying, and wanting.
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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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Divergent Paths to Depolarization: Dialogue Design Determines the Prosocial Benefits of AI-Assisted Political Argumentation
Attitude-congruent AI dialogues reduce immediate affective and opinion polarization more than incongruent ones, while incongruent dialogues increase cognitive trait empathy over two weeks.