🌍 Introduction: The Shift from Prediction to Understanding For the past decade, Artificial Intelligence (AI) has amazed the world with its ability to recognize patterns, generate text, and make predictions . From ChatGPT writing essays to Midjourney creating stunning visuals — these systems thrive on one thing: correlation . But there’s one major limitation no algorithm has fully conquered yet — understanding why things happen. That’s where causal inference comes in. This emerging field of AI is not about predicting what comes next, but explaining cause and effect — a crucial difference that could define the next wave of intelligent systems. In 2025 and beyond, Causal AI might be to this decade what deep learning was to the 2010s. Let’s break down why. 🧩 What Is Causal Inference (in Simple Terms) Imagine you notice that when people carry umbrellas, it rains. A traditional AI system might conclude: “Umbrellas cause rain.” That’s because it sees a correlation ...