AI & ML
How Anthropomorphic Attitudes Toward Agents Divide User Behavior, and How Design Should Change
arXiv cs.HC0 views
arXiv:2610.13156v1 Announce Type: new Abstract: Studies of conversational agents rely on interviews, surveys, lab tasks, or taxonomies. Whether anthropomorphic naming splits those patterns, and whether replies should change, lack field evidence. We report a field study of a desktop assistant (May-August 2026; n=257). Stance is an anthropomorphic assistant name (118 users; 45.9%). Behavior comes from a 128-unit sparse-autoencoder codebook, identity tags, and opening lexicons. Ranks differ by stance (Spearman rho=+0.249 vs. null mean +0.382; p=.0419). Teacher and tutoring identities covary with renaming, an introverted task-only orientation against it; renamers greet more and command less; confiding shows the codebook's largest gap. We revise the agent: greet and receive affect on relational openings, execute directly on tasking. In 1,744 judgments (n=129), renamers chose the revised reply far more often than default-name users on being treated as a person and having affect received, less robustly on willingness to continue, and neither judged it worse on task interference.
Source:https://arxiv.org/abs/2610.13156PreviousThe AI Side of the Human-AI Companion Relationship: Contributions to Users' Mental ModelsNextFrom Observation to Intervention: Identifiability of Latent User Bias in Human-AI Interaction
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