Interpretability (machine learning)

Explainable AI (XAI) refers to artificial intelligence systems that allow humans to understand and oversee their decision-making processes, countering the "black box" nature of machine learning. XAI algorithms follow principles of transparency, interpretability, and explainability, providing a basis for justifying decisions, tracking them, and improving the algorithms. This is particularly important in fields like medicine, defense, finance, and law where understanding decisions and building trust in algorithms is crucial.