Explainability

Explainability is the process of making machine learning model decisions understandable to humans, especially in cases where models evolve from data without human intervention. This is particularly challenging with complex models like deep neural networks.

Lack of AI explainability can lead to mistrust and misunderstanding, impacting the effectiveness of the model, especially in regulated environments like finance and healthcare.