Explainable AI (XAI): Making AI Decisions Transparent and Trustworthy
Sahar Bukhari · 2025
Artificial intelligence systems are progressively used in high-stakes domains ranging from legal decisionmaking and healthcare diagnostics to financial services. Yet, the "black box" nature of numerous AI models can dent trust, accountability, and safety. This paper deliberates the importance of explainable AI (XAI)-methods that make AI decision processes explainable and why transparency is critical in fields like law, medicine, and finance. We acme recent realworld specimens where lack of explainability led to complications, and how XAI can help certify AI decisions are fair, ethical, and yielding with regulations.