On Integrating Generative Models into Cognitive Architectures for Improved Computational Sociocultural Representations

Abstract

What might the integration of cognitive architectures and generative models mean for sociocultural representations within both systems? Beyond just integration, we see this question as paramount to understanding the potential wider impact of integrations between these two types of computational systems. Generative models, though an imperfect representation of the world and various con-texts, nonetheless may be useful as general world knowledge with careful considerations of sociocultural representations provided therein, including the represented sociocultural systems or, as we explain, genres of the Human. Thus, such an integration gives an opportunity to develop cognitive models that represent from the physiological/biological time scale to the social timescale and that more accurately represent the effects of ongoing sociocultural systems and structures on behavior. In addition, integrating these systems should prove useful to audit and test many generative models under more realistic cognitive uses and conditions. That is, we can ask what it means that people will likely be using knowledge from such models as knowledge for their own behavior and actions. We further discuss these perspectives and focus these perspectives using ongoing and potential work with (primarily) the ACT-R cognitive architecture. We also discuss issues with using generative models as a system for integration.