The Influence of Distributed AI in Trust and Collaboration for Search-and-Rescue Teams

要旨

Artificial intelligence (AI) is increasingly deployed in high-stakes domains such as search-and-rescue (SAR), where detections or classifications can shape how teams share information, build trust, and make time-critical decisions. This paper investigates how teams of SAR professionals incorporate AI into their teamwork, highlighting both benefits and challenges. To support this study, we developed the Council of Wizards, a multi-agent Wizard-of-Oz technique that simulates distributed AI systems, enabling scalable and controlled evaluation of collaborative dynamics. Using this novel method, we conducted an experiment with 24 subject-matter experts (SMEs) who reviewed SAR video footage as small teams and made group decisions, with or without AI support. Quantitative results showed that AI-assisted teams reached consensus faster than controls. Qualitative feedback revealed how participants interpreted trust cues, adapted strategies, and sometimes struggled with overload or conflicting detections. Findings illustrate how AI shapes teamwork in SAR and provide design implications for trustworthy distributed human-AI interactions.

著者
Matthew Wilchek
Virginia Tech, Arlington, Virginia, United States
Sally Dickinson
Virginia Tech, Blacksburg, Virginia, United States
Kurt Luther
Virginia Tech, Alexandria, Virginia, United States
Feras A.. Batarseh
Virginia Tech, Arlington, Virginia, United States

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Group Work

P1 - Room 127
7 件の発表
2026-04-17 20:15:00
2026-04-17 21:45:00