Explainable AI (XAI) helps us understand AI decisions and predictions.
Many AI models operate as "black boxes," making their decisions unclear.
XAI promotes transparency, ensuring AI systems are accountable and fair.
Common methods include LIME and SHAP for better model insights.
Understanding AI outputs fosters trust among users and stakeholders.
XAI is vital in healthcare, finance, and autonomous systems for safety.
As AI evolves, explainability will be crucial for responsible use and governance.