Explainable AI (XAI) aims to make AI models transparent. Instead of being a black box, AI shows the reasoning behind its outputs. This is critical in areas like healthcare, finance, and legal decisions, where trust and accountability matter. Techniques include visualizations, rule extraction, and simplified models. XAI allows users to verify results, detect bias, and improve AI systems. Understanding AI decisions ensures responsible deployment and increases adoption in sensitive fields.
**Key takeaway:** Transparency makes AI trustworthy.