A lot of the mech interp techniques are glorified notions of probing. If models were generally interpretable with respect to the things we cared about, we'd know know when they're hallucinating, for example.
Identifying that a common neuron or set of neurons fires for golden gate bridge can be done only because you already know that you're looking for golden gate bridge. If models had recovered some new truth (e.g., the silver door road), you wouldn't be able to elicit it without knowing to look for it a priori.
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Sparse autoencoders are not reliable. Ask your favorite AI. For example, https://proceedings.mlr.press/v267/kantamneni25a.html
A lot of the mech interp techniques are glorified notions of probing. If models were generally interpretable with respect to the things we cared about, we'd know know when they're hallucinating, for example.
Identifying that a common neuron or set of neurons fires for golden gate bridge can be done only because you already know that you're looking for golden gate bridge. If models had recovered some new truth (e.g., the silver door road), you wouldn't be able to elicit it without knowing to look for it a priori.