(GIST OF SCIENCE REPORTER) CLEAN AI

(MAY-2025)

CLEAN AI

Context:

A recent report from the International Monetary Fund (IMF) says that even though AI needs a lot of energy, the economic benefits it will create (like more productivity, more jobs, more innovation) will be greater than the environmental damage it might cause.
The countries must make sure that AI is powered by clean energy (like solar, wind, or nuclear) as much as possible.

Key Points to remember:

The world is entering a new era powered by Artificial Intelligence (AI). AI has the potential to transform industries, create new jobs, and drive economic growth. But like every major technological advancement, it also brings new challenges — especially for the environment.
AI and sustainable development do not have to be enemies. With the right policies and planning, countries can embrace AI without sacrificing their environmental goals. India, too, must stay firmly on the path of building sustainable AI infrastructure.

AI’s Growing Appetite for Energy

AI requires vast computing power. Training AI models, storing data, and running AI-based applications depend on huge data centres — facilities that consume enormous amounts of electricity. The IMF report notes that in the United States, which is the largest hub for AI computing in the world, the expansion of AI alone could increase electricity prices by up to 9%.

If this electricity comes from fossil fuels like coal and oil, it would mean a significant rise in carbon emissions.
On the other hand, if AI data centres are powered by renewable energy like solar, wind, or even nuclear power, the environmental damage can be greatly reduced.

Thus, the choice of energy sources will determine whether the AI revolution becomes a threat to climate goals or supports a cleaner future.

India’s Position

In India, the government is making initial investments in AI infrastructure through the IndiaAI Mission.

As of now, India’s AI development is not large enough to significantly impact the country’s overall energy mix.
But this is the right time to embed sustainable practices into the AI journey from the very beginning.
At the AI Action Summit in Paris earlier this year, India made it clear that it aims to develop AI responsibly, keeping sustainability in mind. This approach is smart and necessary for several reasons:
India has a net zero target for 2070 — meaning it aims to balance the amount of carbon dioxide it emits with the amount it removes.
If AI infrastructure grows without green energy planning, it could add to emissions, making the net zero target harder to achieve.

How AI Can Become Greener

There are two main reasons why focusing on green energy for AI is especially important:

1. Massive Electricity Consumption

Data centres are already among the highest electricity consumers globally, and AI will only make this worse.
Without renewables, the rise in energy demand could mean more pollution and higher energy costs.
By using solar, wind, and nuclear power, countries can meet AI’s energy needs without worsening the climate crisis.

2. Unique Opportunity for Captive Renewable Infrastructure

Data centres offer a special advantage: they occupy hundreds of acres of land, often in concentrated hubs.
These spaces are perfect for installing solar panels or wind turbines nearby, making them partly self-sufficient in energy.
Some Indian companies are already moving in this direction, signing agreements to buy renewable energy specifically for powering their data centres.

There is also exciting potential in small modular nuclear reactors (SMRs):

SMRs could provide clean, steady electricity to large data clusters without emitting greenhouse gases.
Combined with solar and wind energy, SMRs could dramatically cut the carbon footprint of AI operations.

Beyond Electricity: Other Environmental Challenges

AI’s environmental impact is not limited to electricity use. There are other important areas to watch:

Mining of minerals: AI hardware like chips and servers require rare minerals, the extraction of which can harm ecosystems.
Water usage: Data centres use large amounts of water for cooling their systems.
Electronics waste: Manufacturing electronics leaves behind industrial waste and effluents.