Green AI: Measuring the Environmental Impact of AI Systems

Topic: Green AI: Measuring the Environmental Impact of AI Systems and Navigating U.S.-China Climate Cooperation

Abstract: The rapid expansion of AI  is driving unprecedented demand for energy, particularly in the operations of data centers, which significantly contribute to global carbon emissions. This presentation will present "White Paper on Global Artificial Intelligence Environmental Impact", which introduces the Green AI Index, a pioneering framework designed to assess the energy impact, and the carbon and water footprints of AI systems and data centers. The white paper analyzes environmental regulations and policies in the U.S., China, and Europe, providing insights into managing AI’s energy consumption and promoting sustainable practices. 

Additionally, this talk examines the geopolitical dimensions of climate change, particularly U.S.-China cooperation and competition. Both nations are leading in climate and AI innovation, yet they also face shared environmental challenges. Policy frameworks that address AI’s energy usage, alongside fostering U.S.-China collaboration on sustainability, are critical for ensuring that AI technologies contribute to global climate goals rather than hinder them.

Bio: Jerry Huang is a BA and MS candidate in Computer Science at Harvard University, focusing on the intersection of AI, sustainability, and international policy. He is a member of the Council of Sustainability Leaders at Harvard University, President of U.S.-Asia Sustainable Development Foundation and advisor to the Board of the Mingguang City Science and Technology Innovation Carbon Neutrality Research Institute.

Jerry is the lead author of the "White Paper on Global Artificial Intelligence Environmental Impact”. His work actively fosters U.S.-China collaboration in sustainability and renewable energy sectors, contributing to global efforts to mitigate climate change.