AI has become many students’ secret tutor, weapon, and companion. While numerous AI detectors and plagiarism checkers closely monitor usage, it’s undeniable that AI usage has become prevalent. Even teachers use generative AI to create lesson plans or instruct students to use it strictly for “ideation.” Generative AI like Gemini or ChatGPT has become a part of society.
Since Open AI’s release of ChatGPT in November 2022, accessible autonomous technology has transformed our world. The remains caught between the benefits and dangers of humanities. Coined as the AI “gold rush” the rapid development of AI has accumulated a staggering demand for energy.
AI brings our world forward yet spins us faster across climate change.
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Even before the rise of AI, data centers gobbled up energy supplies. For example, there are over 100 Amazon centers worldwide, with 50,000 servers (“AWS Global Infrastructure”). A globalized market, wide resource line, and complex delivery system were recipes for mass data-storage facilities. Just from one major company, it’s clear that the web of interconnected industries is energy guzzlers.
Generative AI demands much higher amounts of energy than standard computing. According to Noman Bashir, a Climate Impact Fellow at MIT Climate and Sustainability Consortium, “A generative AI training cluster might consume seven or eight times more energy than a typical computing workload.”
The Harvard Business Review states that a single AI model consumes hundreds of megawatts of hours of energy per day, emitting hundreds of tons of carbon dioxide. Moreover, research suggests that AI model training consumes freshwater resources due to heat emitted by data centers (Shaolei and Wierman).
AI usage has spiked in recent years, posing exponential increases in energy consumption. Data from Statista suggests that AI usage soared from approximately 116 million in 2020 to 378 million in 2025, with projections of 729 million by 2030.
The energy industry is the second-largest energy consumer. Making human lives convenient inevitably propels the world into climate change. Overconsumption does not provide any marginal benefits. By definition, overconsumption means expending more resources than what can be replaced. If our resource expenditure is too great, our actions today will detract resources from our tomorrow.
Energy inefficiency is often due to insufficient government management facilities. According to a diagram from the Lawrence Livermore National Laboratory (LLNL) at the Department of Energy, in 2017, 66.7% of energy generated in the US was rejected energy (“The Environmental Impact”).
But what can we do to change this trend?
Changing the source of generative AI energy is one main solution. According to Associate Professor Yuan Yaohe from Yale University, promoting solar or wind power dependence for AI data centers is a major step that must be taken. On the producer’s side of the equation, programmers can refine AI generative algorithms to optimize energy usage (“Can We Mitigate AI’s Environmental Impacts?”). The UNEP states that over 190 countries have adopted ethical AI usage guidelines. Furthermore, the UNEP recommends establishing standardized AI energy consumption monitoring systems. Meanwhile, consumers of AI can help make progress through mindful AI consumption (“AI has an environmental problem”)
The future of AI is inevitably upon us, but all stakeholders must take action to protect our environment from this innovation. Amid advancing policies and adaptions, technology and environmental resilience are finding ways to co-exist.
Works Cited
"AI has an environmental problem. Here's what the world can do about that." UNEP, 21 Sept. 2024, www.unep.org/news-and-stories/story/ai-has-environmental-problem-heres-what-world-can-do-about. Accessed 24 Jan. 2025.
"AWS Global Infrastructure." Amazon, aws.amazon.com/about-aws/global-infrastructure/. Accessed 24 Jan. 2025.
"Can We Mitigate AI's Environmental Impacts?" Yale School of the Environment, environment.yale.edu/news/article/can-we-mitigate-ais-environmental-impacts#:~:text=Transitioning%20to%20renewable%20energy%20sources,can%20mitigate%20these%20negative%20impacts. Accessed 24 Jan. 2025.
"The environmental impact of wasted electricity." Arcadia, 1 Nov. 2021, www.arcadia.com/blog/the-environmental-impact-of-wasted-electricity. Accessed 24 Jan. 2025.
"Number of artificial intelligence (AI) tool users globally from 2020 to 2030." Statista, www.statista.com/forecasts/1449844/ai-tool-users-worldwide. Accessed 24 Jan. 2025.
Ren, Shaolei, and Adam Wierman. "The Uneven Distribution of AI's Environmental Impacts." Harvard Business Review, 15 July 2024, hbr.org/2024/07/the-uneven-distribution-of-ais-environmental-impacts. Accessed 24 Jan. 2025.