AI Could Boost Fossil Fuel Emissions to Russia's Level
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- Will and Holly Alpine, former Microsoft sustainability workers who quit in early 2024, published research in npj Climate Action finding AI as a productivity enhancer for the fossil fuel industry could raise global energy-related emissions by 1.2 to 4.8 percent
- The study estimates additional annual emissions could range from Mexico's total to Russia's (the world's fourth-largest emitter), a scale that outpaces both AI's benefits to solar and wind and projections of emissions from the global data center buildout
- The Alpines coined the term "enabled emissions" — AI-supported greenhouse gas pollution that tech companies don't typically account for alongside operational and supply-chain emissions
- Chevron is building a behind-the-meter gas plant in Texas to power Microsoft data centers, and Chevron New Energies president Jeff Gustavson told analysts the company will "use some of that compute" to power AI inside Chevron
- Independent energy researcher Jon Koomey called the research "credible" and noted the net climate effect of AI remains unknown, since machine learning can make data center cooling 30-40 percent more efficient while also making fossil fuel extraction cheaper and faster
Why it matters: The Chevron-Microsoft gas plant is a live example of the self-reinforcing cycle the Alpines describe: fossil fuels power the data centers running the AI that makes fossil fuel extraction more efficient. If the study's high-end estimate holds, AI-enabled fossil fuel emissions would match Russia's entire annual output — a scale that dwarfs the data center footprint dominating today's AI climate debate, and one that current corporate sustainability accounting ignores entirely.
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