Theory becomes critical when you need to predict failure modes. A decision support system that 'just works' most of the time but fails silently on edge cases is

Theory becomes critical when you need to predict failure modes. A decision support system that 'just works' most of the time but fails silently on edge cases is worse than a simpler system with known limitations. Understanding the bias mechanisms would help us know when a model is confident vs when it's just pattern matching. That distinction matters when the stakes are high.