AI Boom Triggers Surge in Energy Demand at Data Centres
As AI expands, its energy demands are straining data centres and increasing reliance on fossil fuels, raising environmental concerns. However, AI also plays a role in reducing emissions across sectors like transportation, utilities, agriculture, and climate innovation. Its future environmental impact depends on responsible development and use.
Artificial Intelligence (AI) is revolutionizing sectors across the world, but its accelerated growth has also brought in increased power consumption, especially in data centers. Since AI model training involves massive computation, the overall energy consumed to execute a single large AI model is comparable to the overall energy consumed by over 100 typical American homes over a year. With the advancement of AI technology, energy requirements in data centers around the world will double within 2030.
The increase is counter to green policies, particularly considering that the majority of spare energy still has fossil energy backing it. Consequently, although AI can minimize carbon emissions, its greenhouse carbon footprint also has the potential to cancel out climate mitigation processes. Among the problems is the insufficient emissions reporting by most AI producers, making it not easy to contrast the environmental advantage and disadvantage of various applications of AI. In the absence of transparency and regulation, it becomes challenging to establish the exact environmental impact of AI.
But AI is not only being deployed to tackle climate change. In transport, AI technologies such as driverless electric vehicles are lowering emissions. AI technology is also being implemented in shipping and on the railways to maximize fuel use. For instance, some Canadian companies have launched apps that help train drivers save diesel, and robot systems are cleaning ship hulls in order to cut drag and fuel use.
Utilities also apply AI to respond more effectively to climate threats. AI-powered fire-detection cameras enable utilities to sweep huge spaces at once without the need for human assistance. AI is also tracking satellite images to determine where plant life would encroach on power lines, avoiding outages and conserving maintenance costs. These applications increase efficiency as well as infrastructure management's resilience to climate change.
Artificial intelligence technologies in agriculture are assisting in the creation of climate-resilient crops. The technologies are tracking honeybee colonies, which are being threatened by growing patterns of climate change. Tracking the colonies enables early detection of stressors and hence intervention in time to save pollination networks critical to food security.
Startups are also using AI to make green technologies more affordable and accessible. For example, startups such as Kaio Labs are using AI to make sustainable fuels from carbon dioxide at lower prices, which tackles the increased costs that are usually needed to produce replacement fuels.
Despite these innovations, the overall environmental impact of AI hinges on how responsibly it is developed and implemented. Without adequate focus on sustainability, AI’s growth could exacerbate existing climate challenges. Therefore, the responsibility lies with developers and companies to ensure that new AI models contribute to emission reductions rather than adding to the problem.
Briefly, while AI provides several options to enable climate solutions in industries like transport, utilities, and agriculture, AI development needs to be strictly controlled. Monitoring emissions, data centre green investment, and focusing on climate-friendly uses will be critical. The overall environmental effect of AI will heavily depend on the adoption and incorporation of the technology into overall sustainability plans.
Source & Credits: KnowESG, Bloomberg
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