White Paper on Global Artificial Intelligence Environmental Impact
The rapid growth of AI models and data centers has led to significant environmental impacts, including substantial energy consumption, carbon emissions, water usage, and electronic waste. Data centers now account for approximately 1-2% of global electricity consumption, and large-scale AI models, such as GPT-3, require energy equivalent to the yearly usage of 120 U.S. homes. These growing environmental concerns highlight the urgent need for comprehensive assessment and regulation. This paper introduces the AI Green Index, a framework designed to evaluate the environmental impact of AI models and data centers. The index offers a standardized, quantifiable metric to assess both carbon and water footprints across the life cycle of AI technologies. By promoting transparency, sustainable practices, and carbon-efficient innovations, the Green AI Index aims to guide stakeholders in reducing environmental impacts. Additionally, the paper analyzes current policies in major regions, including China, the U.S., and the EU, providing insights into strengths and weaknesses in environmental governance. The white paper seeks to inform researchers, industry leaders, and policymakers, fostering collaboration toward a sustainable AI future
Please note that all purchases are final and nonrefundable.
The rapid growth of AI models and data centers has led to significant environmental impacts, including substantial energy consumption, carbon emissions, water usage, and electronic waste. Data centers now account for approximately 1-2% of global electricity consumption, and large-scale AI models, such as GPT-3, require energy equivalent to the yearly usage of 120 U.S. homes. These growing environmental concerns highlight the urgent need for comprehensive assessment and regulation. This paper introduces the AI Green Index, a framework designed to evaluate the environmental impact of AI models and data centers. The index offers a standardized, quantifiable metric to assess both carbon and water footprints across the life cycle of AI technologies. By promoting transparency, sustainable practices, and carbon-efficient innovations, the Green AI Index aims to guide stakeholders in reducing environmental impacts. Additionally, the paper analyzes current policies in major regions, including China, the U.S., and the EU, providing insights into strengths and weaknesses in environmental governance. The white paper seeks to inform researchers, industry leaders, and policymakers, fostering collaboration toward a sustainable AI future
Please note that all purchases are final and nonrefundable.
The rapid growth of AI models and data centers has led to significant environmental impacts, including substantial energy consumption, carbon emissions, water usage, and electronic waste. Data centers now account for approximately 1-2% of global electricity consumption, and large-scale AI models, such as GPT-3, require energy equivalent to the yearly usage of 120 U.S. homes. These growing environmental concerns highlight the urgent need for comprehensive assessment and regulation. This paper introduces the AI Green Index, a framework designed to evaluate the environmental impact of AI models and data centers. The index offers a standardized, quantifiable metric to assess both carbon and water footprints across the life cycle of AI technologies. By promoting transparency, sustainable practices, and carbon-efficient innovations, the Green AI Index aims to guide stakeholders in reducing environmental impacts. Additionally, the paper analyzes current policies in major regions, including China, the U.S., and the EU, providing insights into strengths and weaknesses in environmental governance. The white paper seeks to inform researchers, industry leaders, and policymakers, fostering collaboration toward a sustainable AI future
Please note that all purchases are final and nonrefundable.