Bottlenecks in Mechanistic Interpretability: Evidence and Goals
joshua_saxe · x · 2026-08-11
Joshua Saxe argues that mechanistic interpretability is crucial but currently bottlenecked by ambiguities in framing, epistemology, and definitions. To unbottleneck the field, the discourse needs to mature around several core questions:
- Standards of Evidence: In complex systems, is merely showing that SAE activations correlate with high-level qualitative behavior enough to make strong claims about internal mechanisms?
- The Goal: If the ultimate goal is control, why aren't mech-interp based control methods baselined against mainstream SFT or prompt-based techniques?
- Methodological Rigor: How are we justified in making mechanism claims by stacking a 'nonlinear probe' on top of a less interpretable massive model?
The author warns that the field risks repeating the mistakes of LIME and Shapley values from the 2010s: appearing useful but falling short of genuine understanding.
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