Proceedings of the Annual Meeting of the Cognitive Science Society

Foundation models, large-scale artificial intelligence (AI) systems trained on vast amounts of data and able to engage with a wide range of tasks, have captivated public attention and promise transformative impact across many fields, from mathematics to education. The capacity for such models to fluidly engage in natural language carries huge potential implications for cognitive science: for the first time, we have computational models that bring us a significant step toward the generality of human cognition, thereby inviting us to reconceptualize how we may build models of the human mind. Yet, major questions remain as to how to build such models, what kind of data is needed for this, and what the implications are for cognitive science.