Hidden Environmental Impact of AI

Published Date : 29/07/2025 

AI not only facilitates environmentally harmful practices but is also resource-intensive, particularly in the training and usage of advanced models like ChatGPT and GenAI. 

In recent years, AI has gained huge popularity in the fields of science, social studies, and technology for solving complex problems, from diagnosing diseases to forecasting floods. Its potential in addressing the climate crisis is also praiseworthy — for instance, in aiding environmental research, which has contributed to mapping deforestation and soil erosion, as well as forecasting droughts and wildfires. Activists are now using Global Fishing Watch, which employs machine-learning software to identify overfishing and illegal fishing in specific areas, thereby protecting our ecosystems. However, behind all this excitement, there is an uncomfortable truth — AI might be doing more harm than good for the environment.

AI’s Profit Problem

The rise of AI has opened many opportunities for businesses to maximize their profits, but this comes at a price. Businesses increasingly rely on AI, leading to increased resource extraction, industrial production, and global consumption. For instance, deep learning technologies are used by major corporations to analyze massive geological datasets, aiming to identify new oil and gas reserves. Additionally, smart submersibles, led by AI, can now detect untapped oil and gas reserves in remote parts of the ocean. Moreover, to generate profit, states and firms often exaggerate the benefits of new AI technology for personal gain, while downplaying or concealing its environmental costs. The tech world works by hyping people up — for example, when start-ups claim ‘technological breakthroughs’ to attract funding from investors. Large firms, such as Amazon and Google, dominate this space, controlling the technology and shaping public perception. The result? Increased production, overconsumption, and escalating pressure on the planet’s already limited resources.

AI’s Own Environmental Footprint

AI not only facilitates environmentally harmful practices but is also resource-intensive. Training advanced AI models, such as ChatGPT and GenAI, requires enormous amounts of electricity. According to the United Nations Environment Programme, a single search made through ChatGPT consumes ten times more energy than a simple Google search. Intuitively, complex models tend to be even more energy-intensive and have a negative impact on the overall environmental footprint. Moreover, once an AI model is trained, the energy demand does not stop; rather, it continues to consume electricity every time it is used. The rise of AI has also fueled the expansion of data centers, which require vast amounts of water to cool equipment and prevent overheating. They also produce electronic waste and generate significant greenhouse gas emissions. As companies constantly release newer and more powerful models, the carbon emissions continue to rise at a pace that far outweighs any emissions that AI tools could help reduce.

Smart Tech Needs Smart Governance

If left to corporations alone, AI risks being misused for short-term profits, leading to long-term environmental degradation. Without proper regulation, AI could become a tool of overproduction and unsustainable consumption. Hence, I believe that the best way to manage the risks of AI is to combine technology with politics to provide innovative solutions to environmental crises and to ensure that AI development is aligned with environmental and social goals. The Government should more closely control AI development to prioritize its use for public interest, particularly among researchers, scientists, and institutions working on climate and sustainability. Additionally, state-funded AI initiatives can help transform industries with low-carbon technologies while also preventing businesses from overusing these technologies for purely profit-driven purposes. In today’s world, we are not passive receivers of technology; rather, we have the power to shape it to our advantage responsibly. Hence, we must redefine its purpose as a tool to ensure sustainable development. 

Frequently Asked Questions (FAQS): 

Q: What are some positive uses of AI in environmental research?

A: AI is used in environmental research to map deforestation and soil erosion, forecast droughts and wildfires, and identify overfishing and illegal fishing activities.

Q: How does AI contribute to environmental harm?

A: AI facilitates environmentally harmful practices such as increased resource extraction, industrial production, and global consumption, and is also resource-intensive, requiring significant amounts of electricity and water.

Q: What are the energy requirements for training advanced AI models?

A: Training advanced AI models like ChatGPT and GenAI requires enormous amounts of electricity, with a single search through ChatGPT consuming ten times more energy than a simple Google search.

Q: How can governments regulate AI to ensure it benefits the environment?

A: Governments can regulate AI by controlling its development to prioritize public interest, particularly among researchers and scientists working on climate and sustainability, and by funding initiatives that transform industries with low-carbon technologies.

Q: What is the role of smart governance in managing AI risks?

A: Smart governance combines technology with politics to provide innovative solutions to environmental crises and ensures that AI development is aligned with environmental and social goals, preventing misuse for short-term profits. 

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