- The UN warns that AI’s environmental footprint is much, much more than just energy
- AI data centers could consume water equivalent to 1.3 billion people by 2030
- The report calls for more diverse reporting and robust governance to protect people
A new UN report argues that the effects of artificial intelligence are far from equal – instead, its environmental impact is being underestimated because most discussions focus only on carbon emissions.
Instead, the UN encourages companies, investors and governments to also include water consumption and land use in their evaluations.
This comes as AI data centers alone are expected to consume 945TWh of electricity by 2030 – the equivalent of 1.95 billion homes, or three times the population of Pakistan, Bangladesh and Nigeria.
The UN is concerned about AI’s environmental impacts
Apart from electricity, the UN also warns that by the end of the decade their water consumption would be equal to 1.3 billion people in sub-Saharan Africa (9.3 trillion liters) and the land use could be equivalent to 14,500 square kilometers (twice the size of Jakarta, home to 32 million people).
But it is far more than the environment alone that the AI industry is putting under pressure – unlike conventional software, AI relies heavily on physical data center campuses, grid connections, cooling systems and semiconductors, greatly expanding its impact across both Scope 2 and Scope 3.
Professor Kaveh Madani, director of the United Nations University Institute for Water, Environment and Health, emphasized that the report should act as a block on artificial intelligence. Instead, Madani calls for responsibility and sustainability.
“We have a narrow window to ensure that the backbone of our time’s technological revolution develops within planetary boundaries, and that the societies that provide the critical minerals to advance AI and those that host its infrastructure and e-waste are also among those who benefit.”
Interestingly, while much of the debate often revolves around model training, researchers now believe that inference (the day-to-day use after implementation) accounts for around 80-90% of AI’s energy needs. ChatGPT alone is said to process around 2.5 billion prompts per day, and the energy demand only increases as response quality improves.
Looking ahead, the UN is calling for mandatory reporting of carbon, land and water footprints as well as ‘efficiency by design’ approaches. The paper also calls for stronger governance to prevent environmental costs from being shifted onto the most vulnerable communities.
Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews and opinions in your feeds.
