In the future, humans will cooperate with a wide range of AI-based systems while they multitask, requiring these systems to consider human attention as a limited resource. We will discuss the problems that occur when users frequently switch their attention between multiple sources of information and sketch a new class of AI-based interfaces that integrally manage user attention, based on principles of (1) reinforcement learning, (2) cognitive models (i.e., “simulated users”), and (3) computational rationality.

Philipp Wintersberger is a Full Professor of Intelligent User Interfaces at IT:U Linz. He leads an interdisciplinary team of scientists focusing on human-machine cooperation in safety-critical AI-based systems. He has (co)authored various works published at major journals and conferences (such as ACM CHI, IUI, AutomotiveUI, or Human Factors), and his contributions have won several awards.