An Isolation Forest model is trained to detect anomalies in server logs. A data scientist explains: "Isolation Forest works by trying to isolate each data point using random splits — anomalies are isolated faster." A colleague asks: "why would anomalies be isolated faster than normal points?" What is the correct mechanistic explanation?