What is Explainable AI (XAI)?

Unpacking the 'Black Box': Making AI Decisions Transparent

Building Trust and Accountability in AI Systems

The Importance of Understanding AI Reasoning

**Explainable AI (XAI)** is a field of research and a set of methods that allow humans to **understand the output and reasoning of AI models**. Many advanced AI models, particularly deep neural networks, are often considered 'black boxes' because their decision-making processes are opaque. XAI aims to provide insights into *why* an AI system made a particular prediction or decision, increasing **transparency**, **trust**, and **accountability**. This is crucial for applications in sensitive domains like healthcare, finance, and legal systems, and is a cornerstone of **Responsible AI** development in 2025. XAI encompasses concepts like **AI Transparency** (openness about AI's purpose) and **AI Interpretability** (understanding how a model works). 🔍🤝