This next paper is a bit quirky, but here goes: Introspection is hard to study in both humans and LLMs. But, we do have internal senses that are verifiable, like proprioception (the sense of where your arm is right now). What would proprioception look like in language models? As a digital analogue to the sense of position, a model could verbalize which expert activated in a certain layer for any previous token. It turns out that LLMs can learn a range of such proprioception skills where they understand and report on their internals. We can calibrate and score these reports, and evaluate whether training for proprioception changes model behaviors.