Metrics and Models for Real Time Inference and Prediction of Trust in Human-autonomy Teaming
Abstract
In future operational Air Force and Space Force settings, humans will interact with ever-more autonomous technical systems. Due to the safety- and mission-critical nature of such systems, warfighter and guardian mistrust, distrust, over reliance, or skepticism of autonomy may lead to ineffective team performances and even disastrous outcomes. A key component to ensure high-performing human-autonomy teams (HAT) is properly calibrated trust. Trust pertaining to many HAT tasks is dynamic, ever-changing in response to repeated human-autonomy interactions. Therefore, to ensure seamless HAT, there is an urgent need to account for this dynamic nature of trust and devise objective, unobtrusive means of inferring and predicting trust.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 22, 2024
- Source ID
- FA95502310032
Entities
People
- Zhaodan Kong
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of California, Davis