Vero: A Method for Remotely Studying Human-AI Collaboration

Hohenstein, Jess
Larson, Lindsay E.
Hou, Yoyo Tsung-Yu
Harris, Alexa M.
Schecter, Aaron
Dechurch, Leslie
Contractor, Noshir
Jung, Malte F.
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Despite the recognized need in the IS community to prepare for a future of human-AI collaboration, the technical skills necessary to develop and deploy AI systems are considerable, making such research difficult to perform without specialized knowledge. To make human-AI collaboration research more accessible, we developed a novel experimental method that combines a video conferencing platform, controlled content, and Wizard of Oz methods to simulate a group interaction with an AI teammate. Through a case study, we demonstrate the flexibility and ease of deployment of this approach. We also provide evidence that the method creates a highly believable experience of interacting with an AI agent. By detailing this method, we hope that multidisciplinary researchers can replicate it to more easily answer questions that will inform the design and development of future human-AI collaboration technologies.
Applications of Human-AI Collaboration: Insights from Theory and Practice, ai, human-ai collaboration, method, remote, teams
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