Using virtual agents to guide attention in multi-task scenarios

Abstract

Humans have the ability to efficiently decode human and human-like cues. We explore whether a virtual agent's facial expressions and gaze can be used to guide attention and elicit amplified processing of task-related cues. We argue that an emphasis on information processing will support future development of assistance systems, for example by reducing task load and creating a sense of reliability for such systems. A pilot study indicates subjects' propensity to respond to the agent's cues, most importantly gaze, but to not yet rely on them completely, possibly leading to a decreased performance. © 2013 Springer-Verlag.