Human agency relocates from interface affordances to conversational processes of goal articulation, output evaluation, and outcome negotiation in AI interactions.
PaTAT: Human-AI Collaborative Qualitative Coding with Explainable Interactive Rule Synthesis
2 Pith papers cite this work, alongside 61 external citations. Polarity classification is still indexing.
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Users adjust AI agent personalities differently by task context, forming distinct profiles that increase perceived anthropomorphism, autonomy, and trust.
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After the Interface: Relocating Human Agency in the Age of Conversational AI
Human agency relocates from interface affordances to conversational processes of goal articulation, output evaluation, and outcome negotiation in AI interactions.
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From Fixed to Flexible: Shaping AI Personality in Context-Sensitive Interaction
Users adjust AI agent personalities differently by task context, forming distinct profiles that increase perceived anthropomorphism, autonomy, and trust.