Do AI Systems Have World Models? Probing Reasoning, Forecasting, and Generalization

Behaviours that resemble world knowledge do not by themselves reveal what an AI represents internally. This talk uses Craik's account of mental models—supporting alternatives, prediction and transfer—to frame empirical tests. Spatial reasoning in language models and motion forecasting in visual models illustrate ways to probe those abilities, along with the limits of inferring world models from systems trained on human-produced representations.