Team Cognition · Trust · Responsible AI
What does it take for humans and AI to be good teammates?
I'm Beau Schelble, Assistant Professor of Industrial & Systems Engineering at the University of Tennessee, Knoxville, where I direct the AI & Robotics for Collaborative Systems (ARCS) Lab. My students and I study team cognition, trust, and responsible AI in the settings where human-AI teamwork carries real consequences.
0+
Peer-Reviewed Publications
0
Best Paper Awards
$0K
Sponsored Research (PI)
0
ARCS Lab Researchers
The Question
AI is joining human teams in defense, healthcare, and manufacturing, as a teammate, not a tool. What does it take for that team to share understanding, sustain trust, and perform when the stakes are highest?
Most of our work circles a single question: what does it take for humans and artificial intelligence to genuinely operate as one team? We study the cognitive machinery of human-AI collaboration (shared mental models, trust, situational awareness, and information flow) in the high-stakes environments where getting it wrong costs lives, missions, and trust in the technology itself. We certainly don't have all the answers yet, but we think these are the right questions.
Research Program
What we study.
Five core thrusts and three applied domains, all circling the same question. Select any node to see what it means and a few representative papers.
Select a node to explore
Human-AI Team Design
How team roles, composition, and interaction shift when a teammate is artificial.
The foundation of the lab's work. We study how AI agents move from tools to teammates: how team composition, communication, leadership, and interaction design change when one or more teammates is artificial. This work spans empirical lab studies, computational simulations, and field-informed frameworks, and includes a systematic review of the empirical human-autonomy teaming literature that colleagues across the field have generously built upon.
Representative work
A Mixed Methods Approach to Analyzing the Role of AI Teammates in Transition Phases
Proceedings of the ACM on Human-Computer Interaction
Toward a Science of Human-AI Teaming for Decision-Making: A Complementarity Framework
PNAS Nexus
The Spread of Trust and Distrust in Human-AI Teams
Applied Ergonomics
Selected Work
Work I've been fortunate to be part of.
The ARCS Lab
AI & Robotics for Collaborative Systems
The AI & Robotics for Collaborative Systems (ARCS) Lab studies how humans and intelligent systems become more than the sum of their parts. We combine qualitative, quantitative, and computational methods to engineer human-AI teams that are trusted, ethical, and effective in the environments that matter most: defense, healthcare, manufacturing, and emergency response.
Active Sponsored Research
Preventing, Identifying, and Mitigating the Impact of Compromised AI Teammates
What happens when an AI teammate is compromised (hacked, spoofed, or degraded) and the team doesn't know? This project develops methods grounded in shared situation awareness and mental model accuracy to detect and recover from compromised AI teammates before they compromise the mission.
Latest
Recent updates.
"Artificial Enhancements" · Tickle College of Engineering
The Tickle College of Engineering featured the lab's work on AI teammates: AI agents built to act as genuine collaborators rather than chatbots, and the ARO-funded effort to detect and recover from compromised teammates across manufacturing, nuclear energy, disaster recovery, and healthcare.
ARO research featured by EurekAlert!
Coverage of the lab's Army Research Office cooperative agreement on preventing and recovering from compromised AI teammates, including how human-AI teams can recognize when an AI may have been attacked.
Invited seminar at UTK Psychology & Neuroscience
Dr. Schelble delivered "Human-AI Teaming: The Importance of Human-AI Complementarity" at the University of Tennessee Psychology & Neuroscience Department Seminar.