Explainability in AI

Explainability in AI refers to the ability to understand and interpret how an AI system makes its decisions or predictions. It's about making the processes transparent so that users can see which factors influenced the outcome. This helps build trust, enables people to identify errors or biases, and ensures that AI decisions align with ethical standards. In essence, explainability allows us to peek inside the "black box" of AI and understand its reasoning, making its use more responsible and accessible across various applications.