Generative AI – Energy Use and Environmental Impacts
These sources collectively provide a comprehensive overview of generative AI’s energy use and environmental impacts, covering aspects such as electricity consumption, carbon emissions, water usage, and potential mitigation strategies.
Yale Environment 360: As Use of A.I. Soars, So Does the Energy and Water It Requires. This publication offers in-depth analysis of AI’s environmental impact, including energy and water consumption.
Harvard Business Review: How to Make Generative AI Greener by Ajay Kumar and Tom Davenport. HBR provides practical steps for companies to reduce the carbon footprint of generative AI.
Wired: AI’s Energy Demands Are Out of Control. Welcome to the Internet’s Hyper-Consumption Era. The publication offers a comprehensive look at AI’s energy demands and their impact on power grids and water resources.
World Economic Forum: AI and energy: Will AI help reduce emissions or increase demand? Here’s what to know. WEF provides analysis on AI’s energy demand drivers and its potential impact on global emissions.
Scientific American: A Computer Scientist Breaks Down Generative AI’s Hefty Carbon Footprint. The magazine features an expert breakdown of generative AI’s carbon footprint.
ACM Digital Library: Controlling AI’s Growing Energy Needs. The library contains a study comparing energy consumption across different AI models, including image generation.
International Energy Agency (IAE): The agency offers data on AI’s electricity consumption compared to standard internet searches.