We are happy to present the keynote speakers:
University of Manchester, UK
Developmental Robotics for Language Learning, Trust and Theory of Mind
Growing theoretical and experimental research on action and language processing and on number learning and gestures clearly demonstrates the role of embodiment in cognition and language processing. In psychology and neuroscience, this evidence constitutes the basis of embodied cognition, also known as grounded cognition (Pezzulo et al. 2012; Borghi & Cangelosi 2014). In robotics and AI, these studies have important implications for the design of linguistic capabilities in cognitive agents and robots for human-robot collaboration, and have led to the new interdisciplinary approach of Developmental Robotics (Cangelosi & Schlesinger 2015). During the talk we will present examples of developmental robotics models and experimental results from iCub experiments on the embodiment biases in early word acquisition and grammar learning (Morse et al. 2015; Morse & Cangelosi 2017) and experiments on pointing gestures and finger counting for number learning (De La Cruz et al. 2014). We will then present a novel developmental robotics model, and experiments, on Theory of Mind and its use for autonomous trust behavior in robots (Vinanzi et al. 2019). The implications for the use of such embodied approaches for embodied cognition in AI and cognitive sciences, and for robot companion applications will also be discussed.
Anna CIAUNICA, Ph.D.
Institute of Philosophy, Porto & Institute of Cognitive Neuroscience Alexandra House, London
(Dis)Embodied Perception of the Self and Other in Human and Artificial Agents
The capacity to integrate self-related information across multiple sensory channels is fundamental to building cohesive representations of our self, body and world in a constantly changing environment. Self-perception scaffolds both our subjective experience of being present, in the here and now, and our successful navigation in a complex physical and social world. Recent years have seen a substantial increase in research aiming at implementing complex forms of mental states such as self-consciousness in artificial agents such as robots and machines. Here I discuss the mechanisms underlying embodied self-perception in humans and to what extent we can “transfer” this knowledge into artificial bodies and minds in order to build autonomous and self-conscious agents. I then discuss whether examining alterations of self-perception and disembodiment can help us reveal important facets of our typical sense of self and about conscious experiences more generally. I focus particularly on depersonalisation disorder as a case study, a fascinating and intriguing phenomenon, typically manifesting as a disruption of bodily self-awareness which induces a disturbing feeling of self-detachment and self-estrangement. I argue that the case of depersonalisation may help us shed light on key differences between self-consciousness in human versus artificial agents.
University of Memphis, USA.
Wide and wild: An embodied-enactivist model of applied linguistics
I'll outline a wide view of social cognition to include embodied and situated processes of intersubjective interaction, for example, nonverbal cues, joint attention and joint action, social affordances and direct enactive perception of intentions and affective states. I'll propose an integrative model that combines the concept of meshed architecture (inspired by performance studies), interventionist causality and dynamical systems theory. This model helps to capture and organize the many different factors involved in social cognition, and I'll show how it can apply in the area of applied linguistics, specifically to conversation analysis, with some reference to research on Autism Spectrum Disorder (ASD).
Indiana University, USA
Training Perception and Action to do the Right Thing
By one account, formal thought in mathematics and science requires developing deep construals that run counter to perception. This approach draws an opposition between superficial perception and principled understanding. In this talk, I advocate the converse strategy of grounding scientific and mathematical reasoning in perception and action. Relatively sophisticated reasoning is typically achieved not by ignoring perception, but rather by adapting perception and action routines so as to conform with and support formally sanctioned responses. Perception and action are more sophisticated than usually thought, particularly because they can be adapted to do the (cognitive) Right Thing. The first case study for this thesis concerns arithmetic and algebraic reasoning, where we find that mathematical proficiency involves executing spatially explicit transformations to notational elements. People learn to attend mathematical operations in the order in which they should be executed, and the extent to which students employ their perceptual attention in this manner is positively correlated with their mathematical experience. People also produce mathematical notations that they are good at reading. Based on observations like these, we have begun to design, implement, and assess virtual, interactive sandboxes for students to explore algebra. The second case study involves students learning about science by exploring simulations. We have developed a computational model of the process by which human learners discover patterns in natural phenomena. Our approach to modeling how people learn about a system by interacting with it follows three core design principles: 1) perceptual grounding, 2) experimental intervention, and 3) cognitively plausible heuristics for determining relations between simulation elements. In contrast to the majority of existing models of scientific discovery in which inputs are presented as symbolic, often numerically quantified, structured representations, our model takes as input perceptually grounded, spatio-temporal movies of simulated natural phenomena.
University of Edinburgh, UK
Native speakers and multilinguals in 4E perspective
Neurolinguists studying the ‘bilingual brain’ have recently voiced concerns about how lack of attention to contextual factors and individual variation has left some of their key findings highly vulnerable. Applied linguists have for thirty years expressed worry over the ‘native speaker’ as the implicit target of language teaching and learning, to the point of denying that the concept has any validity – even though theoretical linguists continue unabashedly to take nativeness as their lodestar. Tentative steps have been taken to rethink key problems and issues of linguistics in the light of 4E cognition, which actually has a longer heritage in the study of language than is generally recognised. This paper focusses particularly on what is gained by conceiving of nativeness and multilingualism in terms of more than intracranial knowledge – whilst acknowledging that to do so opens a Pandora’s box, with contents ranging from Otto’s notebook (as imagined by Clark & Chalmers) to Latour’s ‘Parliament of Things’, which we might instinctively prefer to keep contained.