TRAIL: A Platform for Configurable Human--AI Teaming Experiments

• URL: http://arxiv.org/abs/2607.12180v1
• Date: Mon, 13 Jul 2026 21:59:13 GMT
• Title: TRAIL: A Platform for Configurable Human--AI Teaming Experiments
• Abstract summary: An AI teammate's design properties can shape a team's trust, coordination, and decisions.<n>We present the Team Research and AI Integration Lab (TRAIL), a web platform that makes the AI teammate a customizable design object.<n>In a real six-session classroom deployment (about 51 students), TRAIL sustained longitudinal chaining, held the AI to a stable minority of the conversation.
• Score: 1.53934570513443
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: An AI teammate's design properties (personality, communication style, when it speaks) can shape a team's trust, coordination, and decisions. Studying this rigorously demands infrastructure no existing tool provides: reproducible configuration of an AI teammate embedded in instrumented, real-time collaboration sustained over time. We present the Team Research and AI Integration Lab (TRAIL), a web platform that makes the AI teammate a configurable, reproducible design object, pairing a Big Five persona with a selective-participation message pipeline, dual memory, chained longitudinal experiments, and export-ready analytics. In a real six-session classroom deployment (about 51 students), TRAIL sustained longitudinal chaining, held the AI to a stable minority of the conversation, and enabled export-driven AI-human text-similarity analysis. A single blind persona change produced a design-consistent double dissociation: a cognitive-scaffolding agent drew stronger contribution ratings and closer linguistic alignment; a socially-supportive agent, a warmer team climate and lower over-reliance.

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