In the age of neural networks, the transparency and explainability of AI models have become problematic issues. Transparency refers to understanding the model's processes and logics. Transparency includes having access to the training data, knowledge of the architecture, and information about testing and monitoring. Explainability is about the ability to determine semantically what caused the…