Professor, TU Delft

Talk: On Context Considerations in Estimating Social Experience in Ecologically Valid In-the-Wild Settings

One of the biggest challenges for automated cognitive evaluations of social situations is the ever present effect of context in dramatically influencing our judgements. Context is a heavily loaded term that is often used to describe anything from the time period before a relevant observation to someone's personality and its influence on their behaviour and judgements of a situation. Whilst I certainly do not have answers to crack the context problem in general, In the scope of measuring social experience in ecologically valid in the wild settings, I discuss some work that I have been involved in that offers potentially less mainstream perspectives on context in social situations. I conclude by discussing the open challenges that remain on this intriguing challenge.

Professor, ETH Zurich/University of Glasgow

Talk: Mind Meets Machine: Towards a Cognitive Science of Human—Machine Interactions

Understanding how we perceive and interact with others is a core challenge of social cognition research. This challenge is poised to intensify in importance as the ubiquity of artificial intelligence and the presence of humanoid robots in society grows. As robots advance from the pages and screens of science fiction into our homes, hospitals, and schools, they are poised to take on increasingly social roles. Consequently, the need to understand the mechanisms supporting human-machine interactions is becoming increasingly pressing, and will require contributions from the social, cognitive and brain sciences in order to make progress. This talk examines how established theories and methods from psychology and neuroscience are revealing fundamental aspects of how people perceive, interact with, and form social relationships with robots. I will also focus on a recently introduced framework for studying the cognitive and brain mechanisms that support human-machine interactions, which leverages advances made in social cognition and cognitive neuroscience to link different levels of description with relevant theory and methods. Also highlighted are unique features that make this endeavour particularly challenging (and rewarding) for brain and behavioural scientists. Overall, the framework offers a way to conceptualize and study the cognitive science of human—machine interactions that respects the diversity of social machines, individuals' expectations and experiences, and the structure and function of multiple cognitive and brain systems.

Associate Professor, Heriot Watt/Edinburgh Centre for Robotics

Chief Scientific Officer, CereProc

Talk: You Don't Need to Speak, You Need to Listen: Robot Interaction and Human-Like Turn-Taking

In this talk I argue that there has been a bias for social robots to be assistants, companions, wing-men and one-to-one carers. Thus, the social in most commercial social robots is a simulated social interaction with a single user, at best an echo chamber of unnecessary interaction, at worst an unethical deception aiming to trick people into a trusting relationship.

We can more effectively consider the ethics of building such systems and offer a framework for trust if we move from regarding such systems as social agents to regarding them as social actors. By aggressively challenging the technical constraints that have encouraged one-to-one interaction and by focusing on multi-party interaction we can broaden the scope of such systems. Instead of building smart systems that interact badly, we can build dumb systems that interact well to produce a new generation of systems that can act as mediators and facilitators and work within human communities and groups.