Socially-Aware User Interfaces - Can Genuine Sensitivity Be Learnt at all?

Recent years have initiated a paradigm shift from pure task-based human-machine interfaces towards socially-aware interaction. Advances in deep learning have led to anthropomorphic interfaces with robust sensing capabilities that come close to or even exceed human performance. In some cases, these interfaces may convey to humans the illusion of a sentient being that cares for them. At the same time, there is the risk that - at some point - these systems may have to reveal their lack of true comprehension of the situative context and the user’s needs with serious consequences to user trust. The talk will discuss challenges that arise when designing multimodal interfaces that hide the underlying complexity from the user, but still demonstrate a transparent and plausible behavior. It will argue for hybrid AI approaches that look beyond deep learning to encompass a theory of mind to obtain a better understanding of the rationale behind human behaviors.