Interpretability in AI

Interpretability in AI refers to how easily humans can understand the reasoning behind an AI’s decisions or predictions. It’s about making the AI's processes transparent so we can see why it arrived at a specific conclusion. This helps build trust, identify errors, and ensure decisions align with ethical standards. Think of it like reading a clear explanation or reasoning behind a recommendation, rather than a mysterious "black box." Ultimately, interpretability makes AI more accessible and accountable, allowing users to grasp how and why it works the way it does.