  Immersive analytics has the potential to promote collaboration in machine
learning (ML). This is desired due to the specific characteristics of ML
modeling in practice, namely the complexity of ML, the interdisciplinary
approach in industry, and the need for ML interpretability. In this work, we
introduce an augmented reality-based system for collaborative immersive
analytics that is designed to support ML modeling in interdisciplinary teams.
We conduct a user study to examine how collaboration unfolds when users with
different professional backgrounds and levels of ML knowledge interact in
solving different ML tasks. Specifically, we use the pair analytics methodology
and performance assessments to assess collaboration and explore their
interactions with each other and the system. Based on this, we provide
qualitative and quantitative results on both teamwork and taskwork during
collaboration. Our results show how our system elicits sustained collaboration
as measured along six distinct dimensions. We finally make recommendations how
immersive systems should be designed to elicit sustained collaboration in ML
modeling.
