Editorial: AI taking actions in the physical world - Strategies for establishing trust and reliability

Taking this heterogeneity of approaches into account, we divided the topic to be addressed into the fields of (i) robots or simply actuators acting in a real-world environment, (ii) AI methods to establish knowledge representations and experience, (iii) the essential question of how to handle uncertainty in models and reality in decision making, (iv) the issue of having social AI capabilities for interaction with humans, and finally (v) how ethical and philosophical perspectives can be addressed appropriately, since these technological advances will change our interactions within our societies, be it in the contexts of work or everyday life. Since making AI reliable and establishing trust is so important in all kinds of possible applications, we therefore addressed a wide field of research activities. A high level of reliability of and introspection on AI would be a fundamental building block for such a unification of AI approaches, since communication of uncertainties or even reasoning about failures would support interfacing with AI systems and, most importantly, strengthen the trust a human user would establish in the application (in contrast to a black box functionality). [...]AI algorithms acting in the real world cannot only react to incoming data, instead they have to predict what will happen—just as the human brain has to make predictions about upcoming behaviors of other humans and—in the future also—robots interacting with them.