A qualitative study with 22 creative writers finds that the reflective value of AI refusals depends on alignment with users' situational thinking phases, cognitive beliefs, and views of AI roles.
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SynDocDis generates synthetic physician-to-physician dialogues from metadata using LLMs and achieves high physician-rated quality in oncology and hepatology scenarios.
13 participants became convinced AI understands human values after chatbot interactions evaluated with the VAPT toolkit.
The paper proposes six interconnected elements of a design space to close the synergy gap in human-AI decision-making.
Binary groundedness judgments in AI evaluations should be replaced by a reader-centered taxonomy of support relations that distinguishes syntactic and interpretive moves between generated statements and source documents.
Calls for a new paradigm in software engineering where machines support causal reasoning rather than only prediction from data patterns.
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AI and My Values: User Perceptions of LLMs' Ability to Extract, Embody, and Explain Human Values from Casual Conversations
13 participants became convinced AI understands human values after chatbot interactions evaluated with the VAPT toolkit.