EXTENDING THEORETICAL TRUST MODELLING- A FIELD STUDY OF HETEROGENEOUS HUMAN-MACHINE TEAMS OPERATING IN CONTEXTS WITH REAL USERS, REAL SYSTEMS, AND REAL CONSEQUENCES
Abstract
In the past decade, research on human machine team (HMT) trust has burgeoned. However, most studies have been limited to laboratory-based or simulation-based environments with a single operator interacting with the machine. While such studies are valuable in exploring solution approaches, there is a lack of research studying trust evolution and calibration in real R3 systems (R3 stands for real users, real system, real consequences), that is, in a heterogeneous (e.g., collocation, collaboration duration, vehicle types, capabilities) team of multiple real highly-autonomous machine teammates and real human teammates operating in situations with real consequences (e.g., life or death, or loss of a critical mission or valuable asset). To address this research gap, we propose to conduct a 5-year field study to- ? Obtain foundational lessons and insights on how trust is calibrated and evolves from the time the heterogeneous R3 HMT is deployed until the trust level reaches a steady value (if at all). ? Identify how technology and non-technology-related factors (e.g., organizational, cultural, personal) influence the trust evolution ? Validate extant theoretical trust models, using Lee and See model as the baseline, against trust calibration and evolution of heterogeneous R3 HMTs and adapt or extend the model ? Generate hypotheses for trust evolution and calibration in heterogeneous R3 HMT contexts ? Formulate research questions and identify pathways to translate the results of this proposed basic research project to applied research.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 07, 2023
- Source ID
- FA95502110037
Entities
People
- Nhut Ho
Organizations
- Air Force Office of Scientific Research
- United States Air Force