I have a feeling a lot of people won’t bother to read the article and will just react based off of the (admittedly alarmist) title, but it’s important to note that unlike a lot of articles that tackle environmental concerns on AI, Spectrum *does* offer potential solutions to mitigate the problem:
>Supply-side solutions, such as using alternative fuels for backup generators and sourcing electricity from clean fuels, can reduce AI’s public health impact, but they come with significant challenges. Clean backup generators that offer the same level of reliability as diesel are still limited. And despite advancements in renewable energy, fossil fuels remain deeply embedded in the energy fuel mix. The U.S. Energy Information Administration projects that coal-based electricity generation in 2050 will remain at approximately 30 percent of the 2024 level under the alternative electricity scenario, in which power plants continue operating under rules existing prior to April 2024. Globally, the share of coal and other fossil fuels in electricity generation has remained nearly flat over the past four decades, underscoring the difficulty of entirely changing the energy supply that powers data centers. We believe that demand-side strategies that consider the spatial and temporal variations in health impacts can provide effective and actionable solutions immediately. These strategies are particularly well-suited for AI data centers with substantial operational flexibility. For example, AI training can often run at any available data centers and typically do not face hard deadlines, so those jobs can be routed to locations or deferred to times that have less impact on public health. Similarly, inference jobs—the work a model does to create an output—can be routed among multiple data centers without affecting user experience. By incorporating public health impact as a key performance metric, these flexibilities can be harnessed to reduce AI’s growing health burden. Crucially, this health-informed approach to AI requires minimal changes to existing systems. Companies simply need to consider public health costs when making decisions.
Responsible_Owl3 on
Isn’t “air pollution from AI” a tiny portion of the air pollution generated globally?
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I have a feeling a lot of people won’t bother to read the article and will just react based off of the (admittedly alarmist) title, but it’s important to note that unlike a lot of articles that tackle environmental concerns on AI, Spectrum *does* offer potential solutions to mitigate the problem:
>Supply-side solutions, such as using alternative fuels for backup generators and sourcing electricity from clean fuels, can reduce AI’s public health impact, but they come with significant challenges. Clean backup generators that offer the same level of reliability as diesel are still limited. And despite advancements in renewable energy, fossil fuels remain deeply embedded in the energy fuel mix. The U.S. Energy Information Administration projects that coal-based electricity generation in 2050 will remain at approximately 30 percent of the 2024 level under the alternative electricity scenario, in which power plants continue operating under rules existing prior to April 2024. Globally, the share of coal and other fossil fuels in electricity generation has remained nearly flat over the past four decades, underscoring the difficulty of entirely changing the energy supply that powers data centers. We believe that demand-side strategies that consider the spatial and temporal variations in health impacts can provide effective and actionable solutions immediately. These strategies are particularly well-suited for AI data centers with substantial operational flexibility. For example, AI training can often run at any available data centers and typically do not face hard deadlines, so those jobs can be routed to locations or deferred to times that have less impact on public health. Similarly, inference jobs—the work a model does to create an output—can be routed among multiple data centers without affecting user experience. By incorporating public health impact as a key performance metric, these flexibilities can be harnessed to reduce AI’s growing health burden. Crucially, this health-informed approach to AI requires minimal changes to existing systems. Companies simply need to consider public health costs when making decisions.
Isn’t “air pollution from AI” a tiny portion of the air pollution generated globally?