WHAT IS Explainable AI (XAI)?

Описание: Explainable AI (XAI) refers to techniques and methods that make AI decisions transparent, understandable, and trustworthy to humans. Traditional machine learning and deep learning models often act as “black boxes”, giving accurate results without revealing how they reached those conclusions. XAI solves this by providing human-interpretable explanations — for example, showing which features influenced a prediction or visualizing how a model weighs inputs. Techniques like LIME (Local Interpretable Model-agnostic Explanations), SHAP (SHapley Additive exPlanations), and attention maps help uncover a model’s reasoning process. In business, XAI is crucial for finance, healthcare, and legal systems, where decisions must be auditable and fair. In short, Explainable AI builds trust between humans and machines — ensuring that powerful AI systems not only predict accurately but also justify their actions clearly.