Explainable AI

Explainable AI is a subfield of artificial intelligence that focuses on developing systems that can provide clear and understandable explanations for their decisions and actions. This is achieved through the use of techniques such as model interpretability, feature attribution, and model explainability. Explainable AI is important because it allows users to trust and understand the results of AI systems, which is critical in high-stakes applications such as healthcare and finance. Explainable AI also enables the identification and mitigation of biases in AI systems, which can lead to unfair outcomes.