Prospects for Augmenting Team Interactions with Real-Time Coordination-Based Measures in Human-Autonomy Teams.

Area of Science:

• Human-Computer Interaction
• Team Dynamics
• Artificial Intelligence

Background:

• Complex teamwork necessitates coordination among members and technology, requiring adaptability for effective performance.
• Adaptive human-autonomy teaming systems aim to provide real-time feedback to improve team outcomes.
• Existing research lacks robust measures for team coordination and computational methods to detect changes.

Purpose of the Study:

• To review existing approaches to coordination dynamics and identify research gaps.
• To explore insights from social interaction, relationship science, and psychotherapy for coordination.
• To advance ideas for adaptive feedback systems to enhance human-autonomy team coordination and performance.

Main Methods:

• Literature review of coordination dynamics and feedback mechanisms.
• Identification of research gaps in measuring and detecting team coordination changes.
• Conceptualization of adaptive feedback systems for human-autonomy teams.

Main Results:

• Significant advancements in modeling team interaction dynamics exist, but coordination measurement is underdeveloped.
• Real-time coordination measurement offers potential for adaptive feedback to regulate team patterns.
• Insights from related fields can inform the development of coordination-based measures.

Conclusions:

• A theoretical and empirical foundation for measuring team coordination is critical for adaptive human-autonomy teaming.
• Developing computational methods to detect coordination changes is a key research gap.
• This work lays the groundwork for future human-autonomy teams that leverage coordination measures to augment team interactions and performance.