Interpretability vs performance confusion

The interpretability-versus-performance tradeoff can be hard to balance because the best-performing model is not always the easiest to explain. Teams often want both, but the two goals do not always move together.

This becomes especially important in high-stakes settings where explanations matter for trust, debugging, or compliance. A stronger model may improve outcomes while making it harder to understand why it behaved a certain way.

The right choice depends on the use case. Some systems can afford more complexity, while others need simpler behavior even if performance is a little lower.