Recent progress in artificial intelligence has transformed the way we live, work, and interact. Machines are mastering complex games and are learning increasingly challenging manipulation skills. Yet where are the robot agents that work for, with, and alongside us? These recent successes rely heavily on the ability to learn at scale, often within the confines of a virtual environment. This presents significant challenges for embodied systems acting and interacting in the real world. In contrast, we require our robots and algorithms to operate robustly in real-time, to learn from a limited amount of data, to take mission and sometimes safety-critical decisions, and increasingly even to display a knack for creative problem solving. Achieving this goal will require artificial agents to be able to assess - or introspect - their own competencies and their understanding of the world. Faced with similar complexity,  there are a number of cognitive mechanisms which allow humans to act and interact successfully in the real world. Our ability to assess the quality of our own thinking - that is, our capacity for metacognition - plays a central role in this. We posit that recent advances in machine learning have, for the first time, enabled the effective implementation and exploitation of similar processes in artificial intelligence. This workshop brings together experts from psychology and cognitive science with cutting-edge research in machine learning, robotics, representation learning and related disciplines, with the ambitious aim of re-assessing how models of intelligence and metacognition can be leveraged in artificial agents given the potency of the toolset now available.