The Grounding Problem: An Approach to the Integration of Cognitive and Generative Models

Abstract

The integration of cognitive and neural AI paradigms is a promising direction for overcoming the limitations of current deep learning models, but how to effect this integration is an open question. We propose that the key to this challenge lies in addressing the question of grounding. We adopt a cognitive perspective on grounding, and identify five types of grounding that are relevant for AI systems. We discuss ways that grounding in both cognitive and neural AI systems can facilitate the integration of these two paradigms, illustrating with examples in the domains of computational creativity and education. Because grounding is not only a technical problem but also a social and ethical one, requiring the collaboration and participation of multiple stakeholders, prosecuting such a research program is both timely and challenging.