  In what sense does a large language model have knowledge? The answer to this
question extends beyond the capabilities of a particular AI system, and
challenges our assumptions about the nature of knowledge and intelligence. We
answer by granting LLMs "instrumental knowledge"; knowledge defined by a
certain set of abilities. We then ask how such knowledge is related to the more
ordinary, "worldly" knowledge exhibited by human agents, and explore this in
terms of the degree to which instrumental knowledge can be said to incorporate
the structured world models of cognitive science. We discuss ways LLMs could
recover degrees of worldly knowledge, and suggest such recovery will be
governed by an implicit, resource-rational tradeoff between world models and
task demands.
