Humans are vastly modifying the earth system, with identifiable impacts across the land surface, ocean and atmosphere. Here, we will explore three example applications of how explainable AI (XAI) techniques can help us visualize and quantify these changes over time. First, we will demonstrate how we can utilize XAI methods to quantify the footprint of human activity across the global land surface in near-real time. Second, we will demonstrate the utility of XAI for extracting forced climate patterns through time amidst a sea of climate noise and model disagreement. Third, we will show how XAI can help us better understand and predict temporal variations in decadal warming trends. All three parts of this talk serve as examples of how viewing our climate through an AI lens has the power to uncover new insights into anthropogenic change - allowing scientists to ask "why?" but now with the power of machine learning.