The Reading the Mind in the Eyes Test (RMET) has received attention due to its correlation with collective intelligence. If the RMET is a marker of collective intelligence, training to improve RMET could result in better teamwork, whether for human-human or human-AI (artificial intelligence) in composition. While training on related skills has proven effective in the literature, RMET training has not been studied. This research evaluates the development of RMET training, testing the impact of two training conditions (Naturalistic Training and Repeated RMET Practice) compared to a control. There were no significant differences in RMET scores due to training, but speed of response was positively correlated to RMET score for high-scoring participants. Both management professionals and AI creators looking to cultivate team skill through the application of the RMET may need to reconsider their tool selection.

Traffic Incident Managers (TIMs) coordinate first responders and help resolve traffic-related incidents. Currently, some use over fifteen different software applications with unique functionalities across three monitors to manage incidents, leading to redundant data entry, unnecessary task switching, and delayed responses. 40 hours of TIMs' screens were recorded during their normal work hours at the Iowa Department of Transportation (DoT). The resulting task analysis from these videos greatly influenced the design of a simplified, web-based, user interface (UI) prototype. The new UI offers a 42.9% reduction in the steps required to manage an incident by combining the functionality of the fifteen different applications used in the existing system into a single, structured UI. This research approach offers a UI model to other DoTs that can lead to faster and more effective incident management.