CONCEPT
Thin Knowledge, Thick Knowledge
Lave's foundational distinction — pressed into service by On AI — between the propositional, transferable, context-free knowledge that AI produces with extraordinary efficiency and the situated, embodied, contextually embedded knowledge that only participation produces.
Thin knowledge is propositional. It can be stated, transmitted, tested. "The boiling point of water at sea level is 100 degrees Celsius." "A binary search has O(log n) time complexity." These propositions transfer well, can be looked up, and can be generated by a language model with near-perfect accuracy. Thick knowledge is relational. It cannot be fully stated because it includes elements that exist only in the relationship between the knower and the known — the feel of the system, the sense of what matters here, the intuition that something is off. A senior engineer who knows a codebase thickly knows which of its architectural incompatibilities is likely to cause a production incident under load, because she was on call the last time it happened — specific, situated, contextually embedded knowledge that no documentation captures.
In The You On AI Field Guide
The distinction is not absolute. It is a spectrum, and different kinds of knowledge