The Science of Awe: Evolution, Culture, and Self-Transcendence
Abstract
In this talk I will chart the new science of awe. I will consider its deep mammalian origins and how it manifests in cultural processes like music, visual design, and spirituality and conceptions of the divine. Grounded in this understanding, I will consider what has been learned in terms of awe's influences upon self-representation, cognition, and physiology. Bringing these lines of evidence together, I will argue that awe is a self-transcendent emotion, which emerged in human evolution to enable individuals to fold into social collectives and to see the systems they are part of.
In this talk, I will ask whether the human brain's underlying computations are similar or different from the underlying computations in deep neural networks. The ability to think and reason using natural language separates us from other animals and machines. In the talk, I will focus on the underlying neural process that supports natural language processing and language development in children. Our study aims to model natural language processing in the wild. I will provide evidence that our neural code shares some computational principles with deep language models. This indicates that, to some extent, the brain relies on overparameterized optimization methods to comprehend and produce language. At the same time, I will present evidence that the brain differs from deep language models as speakers try to convey new ideas and thoughts. Together, our findings expose some unexpected similarities to deep neural networks while pointing to crucial human-centric missing properties in these machines.