Measuring Temporal Awareness for Human-Aware AI

Abstract

This research investigated human performance in response to task demands that may be used to convey information about the human to an artificial agent. We performed an experiment with a dynamic time-sharing task to investigate participants development of temporal awareness of the task event unfolding in time. Temporal awareness as an extension, or a special case, of situation awareness, may provide for useful measures of covert mental models applicable to numerous tasks and for input to human-aware AI agents. Temporal awareness measures may be used to classify human performance into the control modes in the contextual control model (COCOM): scrambled, opportunistic, tactical, and strategic. Twenty-one participants participated in a withinsubjects experiment with an abstract task of resetting four independent timers within their respective windows of opportunity. The results show that temporal measures of task performance are sensitive to changes in task disruptions and difficulty and therefore have promise for human-aware AI.