[glial]

In terms of being useful, it depends on the field. In reinforcement learning, for example, the entire field is divided into 'model-free' and 'model-based' approaches. Model-free approaches are learning state-action mappings, which are like habits or 'fast' thinking. Model-based approaches try to build a world model that allows planning and forecasting.

If you're looking for utility in terms of understanding cognition, here are some resources if you're interested - pop-sci books written by cognitive scientists:

- https://global.oup.com/academic/product/the-mind-within-the-...

- https://press.uchicago.edu/ucp/books/book/chicago/R/bo362751...

Is the division true? Of course not - to paraphrase Box, all models are wrong. But some are useful. This one is useful.