AI-Mediated Negotiation: Design Reflections and Lessons

• URL: http://arxiv.org/abs/2606.21886v1
• Date: Sat, 20 Jun 2026 05:15:28 GMT
• Title: AI-Mediated Negotiation: Design Reflections and Lessons
• Abstract summary: We built Trucey, a theory-driven coaching system, to test conversational AI.<n>A pre-registered experiment and interviews complicated each of them.<n>We identify an unexamined scope condition on established HAI design guidelines.
• Score: 15.57105036031543
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Conversational AI promises a new kind of preparation for high-stakes workplace negotiations -- personalized, interactive, and capable of simulating realistic resistance. That promise is intuitive. We built Trucey, a theory-driven coaching system, to test it. The system encoded four assumptions: that articulation supports clarification, that personalization builds strategic competence, that chunked delivery reduces cognitive load, and that structured scaffolding removes metacognitive burden. A pre-registered experiment (N=267) and interviews (N=15) complicated each of them. Notably, the static handbook we included as a passive control outperformed both AI conditions on empowerment and usability. We reflect on why: each assumption encoded a specific model of how preparation unfolds, and the findings revealed that conversational AI imposes a linear execution model on a task that is fundamentally recursive. We identify an unexamined scope condition on established HAI design guidelines and close with a sequencing principle -- map before path, path before simulation -- for future AI coaching design.

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