Research
The problems we work on.
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.
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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 publications
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
Addressing the Role of Context on Trust in Human-AI Teams: The Influence of Team Role and Violation Type in High-Risk Tasks
Ergonomics
Team Cognition & Shared Mental Models
The moment a human mind and an AI agent lock into shared understanding.
High-performing teams think together. We measure and model shared mental models, team situational awareness, and transactive memory in teams that include AI, asking what an AI teammate must know, share, and anticipate for the team to develop genuine shared cognition.
Representative publications
A Mixed Methods Approach to Analyzing the Role of AI Teammates in Transition Phases
Proceedings of the ACM on Human-Computer Interaction
The Spread of Trust and Distrust in Human-AI Teams
Applied Ergonomics
Should AI Teammates Give All the Answers? Examining the Role of Different AI Information-Sharing Techniques on Team Cognition in Human-AI Teams
International Journal of Human-Computer Interaction
Modeling Perceived Information Needs in Human-AI Teams: Improving AI Teammate Utility and Driving Team Cognition
Behaviour & Information Technology
Trust in Human-AI Teams
How trust forms, breaks, spreads, and recovers across human-AI teams.
Trust is the load-bearing wall of human-AI collaboration. We study how trust develops and is violated in high-risk tasks, how trust and distrust spread contagiously through multi-human multi-AI team constellations, and how context and team role reshape the consequences of AI failure. Funded by the Army Research Office to study compromised AI teammates.
Representative publications
Human or AI Advice? Examining Trust, Influence, and Responsibility in Ethically-Charged Human-AI Team Decision-Making
Journal of Cognitive Engineering and Decision Making
The Spread of Trust and Distrust in Human-AI Teams
Applied Ergonomics
Addressing the Role of Context on Trust in Human-AI Teams: The Influence of Team Role and Violation Type in High-Risk Tasks
Ergonomics
Examining the Role of AI Information-Sharing on Trust in Human-AI Teams
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
AI Ethics & Responsible AI
What ethical AI teammates owe their human counterparts.
AI teammates make decisions with moral weight. We empirically investigate how the ethicality of AI actions shapes trust and performance, how AI should explain and justify ethically-charged decisions, and how to design adaptive autonomy that keeps AI behavior aligned with team ethics, work that reviewers and colleagues have been kind enough to recognize with several best paper awards.
Representative publications
Human or AI Advice? Examining Trust, Influence, and Responsibility in Ethically-Charged Human-AI Team Decision-Making
Journal of Cognitive Engineering and Decision Making
Addressing AI Vulnerabilities Through Human-Centered Approaches and Risk Frameworks
Advances in Human-AI Collaboration, John Wiley and Sons (in press)
Ethical Adaptation: Exploring the Use of Adaptive Autonomy in the Design of Ethical AI Teammates in Healthcare
AI and Ethics
An Analysis of Ethical Rationales and Their Impact on the Perceived Moral Persona of AI Teammates
AI and Ethics
Intelligent Information Sharing
The right information, to the right teammate, at the right moment.
An AI teammate that says everything is as useless as one that says nothing. We model what information humans actually need from AI teammates, when sharing builds team cognition versus eroding it, and how information-sharing strategy drives trust: the difference between an AI that interrupts and an AI that anticipates.
Representative publications
Should AI Teammates Give All the Answers? Examining the Role of Different AI Information-Sharing Techniques on Team Cognition in Human-AI Teams
International Journal of Human-Computer Interaction
Examining the Role of AI Information-Sharing on Trust in Human-AI Teams
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Modeling Perceived Information Needs in Human-AI Teams: Improving AI Teammate Utility and Driving Team Cognition
Behaviour & Information Technology
What You Say vs What You Do: Utilizing Positive Emotional Expressions to Relay AI Teammate Intent within Human-AI Teams
International Journal of Human-Computer Studies
Defense & Security
Human-machine teaming where the stakes are highest.
Command-and-control, battlefield AI, and compromised-teammate scenarios. The lab's ARO-funded work develops methods to prevent, identify, and mitigate compromised AI teammates using shared situation awareness and mental model accuracy. Invited briefings include West Point's Technical Advisory Panel on AI in warfare and the National Academies Board on Human-Systems Integration.
Representative publications
Modeling Human Behavior in Cybersecurity: Leveraging Structural Equation Modeling to Address Cognitive Biases and Enhance Defense Strategies
Foundations of Cyber Deception, Springer Nature
Addressing the Role of Context on Trust in Human-AI Teams: The Influence of Team Role and Violation Type in High-Risk Tasks
Ergonomics
The Role of Autonomy Levels and Contextual Risk in Designing Safer AI Teammates
2024 IEEE International Conference on Human-Machine Systems
The Complex Relationship of AI Ethics and Trust in Human-AI Teaming: Insights from Advanced Real-World Subject Matter Experts
AI and Ethics
Healthcare
Ethical adaptive AI for clinical teams.
Healthcare teams are adopting AI faster than we understand its team-level effects. We study adaptive autonomy and ethical AI teammate design for clinical environments, where an AI teammate's judgment intersects with patient safety.
Manufacturing & the Future of Work
What work becomes when your coworker is an algorithm.
From intelligent manufacturing floors to ad hoc virtual teams, we examine how AI teammates reshape work itself: training, meaningfulness, collaboration technology, and the principles organizations need to integrate AI without breaking their teams.
Representative publications
A Comment on "Can You Outsmart the Robot? An Unexpected Path to Work Meaningfulness": Calling for a Different Path for the Future of Human-Robot Teaming
Academy of Management Discoveries
A Comparative Evaluation of Ad Hoc Team Performance, Effectiveness, and Interactions in Modern Collaborative Technology
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Empirical Impacts of Independent and Collaborative Training on Task Performance and Improvement in Human-AI Teams
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Refocusing Human-AI Interaction Through a Teamwork Lens
Handbook on Virtual Work, Edward Elgar Publishing