Rohit Nishant and Thompson S.H. Teo explore the environmental impact of AI and ML. Specifically, the applications where these technologies add the most value are those that require heterogenous data in complex settings (e.g., optimizing smart cities, modeling climate change). In the process of creating value, these large AI and ML models require energy-intensive computing, leaving a huge carbon foot­print. To counteract these concerns, Nishant and Teo offer the “Align, Reduce, Measure” (ARM) framework for mitigating the environmental impact of AI and ML algorithms. The framework encompasses the organiz­ational structure, addresses data heterogeneity, and measures results to create accountability.