SOURCE-LINKED INTELLIGENCE
Benevolent Bias in Multi-Turn Human-Agent Dialogue
Bias in human-agent interaction can manifest not only through hostile language but also as benevolent bias, whereby unequal treatment hides behind a warm, positive tone. To make it detectable, we operationalise benevolent bias along two dimensions, tone and treatment, yielding three classes: neutral support, overt bias, and benevolent bias. Building on these definitions, we construct BENEVDIAL, a class-balanced corpus of 362,880 multi-turn support dialogues spanning user and agent demographics, roles, and generators, to support controlled evaluation. We then test two detector families on it: o
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-29T11:42:45.000Z
First collected: 2026-09-21T07:51:58.603Z. This is not the publication date.