  This paper addresses the evaluation of the performance of the decision
support system that utilizes face and facial expression biometrics. The
evaluation criteria include risk of error and related reliability of decision,
as well as their contribution to the changes in the perceived operator's trust
in the decision. The relevant applications include human behavior monitoring
and stress detection in individuals and teams, and in situational awareness
system. Using an available database of cross-spectral videos of faces and
facial expressions, we conducted a series of experiments that demonstrate the
phenomenon of biases in biometrics that affect the evaluated measures of the
performance in human-machine systems.
