Eye gaze can convey information about intentions beyond what can beinferred from the trajectory and head pose of a person. We propose eye-trackingglasses as safety equipment in industrial environments shared by humans androbots. In this work, an implicit intention transference system was developed and implemented. Robot was given access to human eye gaze data, and it responds tothe eye gaze data through spatial augmented reality projections on the sharedfloor space in real-time and the robot could also adapt its path. This allows proactivesafety approaches in HRI for example by attempting to get the human'sattention when they are in the vicinity of a moving robot. A study was conductedwith workers at an industrial warehouse. The time taken to understand the behaviorof the system was recorded. Electrodermal activity and pupil diameter wererecorded to measure the increase in stress and cognitive load while interactingwith an autonomous system, using these measurements as a proxy to quantifytrust in autonomous systems.