It is simple.

 Sure, here are some key points about interpretable AI:

It's a form of AI that is designed to be transparent and easily understood by humans
It provides insight into the decision-making process of AI systems
Helps humans understand and trust the decisions made by the AI
Helps to detect and address any potential biases in the model
Helps to identify any errors in the model and correct them
Interpretability is particularly important in fields such as healthcare, finance, and criminal justice, where the decisions made by AI systems can have a significant impact on people's lives.
There is a trade-off between interpretability and accuracy when developing AI systems
Therefore, it's important to strive for a balance between interpretability and accuracy when developing AI systems.