From Observation to Automation: AI-Enhanced Analysis of Hybrid Collaboration

Abstract

Hybrid collaboration presents unique challenges that are distinct from what we see in purely remote or purely co-located forms of collaboration. To investigate these challenges, traditional observational methods are often too labor-intensive, limiting scalability and real-time adaptability. To address these challenges, we developed ACACIA (AI Chain for Augmented Collaborative Interaction Analysis), an AI-powered tool to automate and enhance the study of hybrid teamwork. This paper presents the current state of ACACIA, highlights its strengths, and discusses persistent challenges. Furthermore, it explores recent trends of AI-supported collaboration, providing first visions into its future and inviting discussion on how intelligent tools can transform the way we study and optimize hybrid collaboration. We envision custom GPT models trained specifically for the analysis of hybrid collaboration as well as real-time AI-powered collaboration assistants, aiming for a future in which purely observational research is shifting towards scalable, automated analysis of hybrid collaboration.