XAI

XAI covers techniques for making AI decisions understandable to humans: which inputs mattered, why this output, what would change the answer. It matters most where decisions carry consequences (credit, hiring, medical, security alerts) and where regulators expect reasons. In practice explainability is a spectrum, and knowing a model's limits honestly is often more valuable than a tidy story constructed after the fact.