4 steps to using AI in an environmentally responsible way

CodeCarbon, a lightweight, open-source software package that integrates into a Python codebase, is one of the tools that can help organizations conduct these steps. By automatically fetching power and grid data, CodeCarbon can track the amount of carbon dioxide (CO2) produced by the cloud or by local computing resources used to execute an experiment such as training a machine-learning algorithm. It then provides developers with dashboards displaying the CO2 outcomes of the experiment or series of experiments. This visibility into the CO2 impact creates opportunities to reduce the resulting carbon footprints, by hosting the cloud infrastructure in geographical regions that use renewable energy sources, or by using more efficient hardware. CodeCarbon was jointly developed by Mila, a world-leading AI research institute in Montreal; BCG GAMMA, Boston Consulting Group's global data science and AI team; Haverford College in Pennsylvania; and Comet, a meta machine-learning platform.