AI Explainability: Beyond Black Boxes, Towards Trust
Navigating the world of artificial intelligence can feel like peering into a black box. We feed it data, and it spits out answers, often with impressive accuracy. But how does it know? Understanding the inner workings of AI, specifically how it arrives at its conclusions, is becoming increasingly crucial. This concept is known as AI explainability, and it's transforming the landscape of AI development and deployment.
What is AI Explainability?
AI explainability, often shortened to XAI, refers to techniques and methods that allow human users to understand the decisions, behaviors, and predictions made by an AI model. It goes beyond simply getting the right answer; it's about understanding why the AI arrived at that answer.
Why is Explainability Important?
Explainable AI isn't just a nice-to...








