Vero: A Method for Remotely Studying Human-AI Collaboration Conference

Hohenstein, J, Larson, LE, Hou, YTY et al. (2022). Vero: A Method for Remotely Studying Human-AI Collaboration . 2022-January 254-263.

cited authors

  • Hohenstein, J; Larson, LE; Hou, YTY; Harris, AM; Schecter, A; DeChurch, L; Contractor, N; Jung, MF

authors

abstract

  • 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.

publication date

  • January 1, 2022

start page

  • 254

end page

  • 263

volume

  • 2022-January