Understanding Lived Experience: Bridging Artificial Intelligence and Natural Language Processing with Humanities and Social Sciences

Abstract

Abstract True human-centered Artificial Intelligence (AI) is impossible without addressing the inherent and diverse aspects of humanness. Deep learning models have achieved remarkable success in some tasks in vision and language processing, and few can deny it. However, as it moves forward, the field cannot continue to pretend it can do it all by itself, especially when we advertise it as ‘human-centered AI’. It has come the time to open up the stage for methodological pluralism in the interest of critical and democratic science, and for the benefit of society. In this paper, I want to draw particular attention to the aspect of lived (subjective) experience, one research area highly misunderstood and hugely neglected in AI, and especially in Natural Language Processing (NLP). Our intensions, selfhood, autonomy, emotions, feelings, sensory knowledge, cultural history are integral components of our intelligence. Thus, the future AI and NLP models will need to more closely align with the embodied component of human intelligence. As we push the limit of creativity and innovation in AI, we need to develop a new way of looking at human experience, with a better scientific understanding of intelligence and its own practices, at the intersection of many disciplinary fields.