Soaring daily temperatures, wildfires in Canada, inexplicably hot ocean currents; the worries around climate change have intensified. There is another fear out there this year, though mixed with frenzied excitement– the promise of Artificial Intelligence, but also a shadow of worry on whether we have created a Frankenstein we cannot control. My fears, however, are not as much about an AI agent becoming more intelligent than us, but a two things more fundamental and immediate. One is this powerful new technology being used by a malevolent actors to influence elections and democracy itself by creating terabytes of fake news, or even building autonomous war weapons. The other worry, which is considerably less talked about is how AI and Generative AI can serve to accelerate global warming and climate change.

A lot has been written and talked about Blockchain and Crypto being an environmental disaster; but so is AI and Generative AI. There are three ways how Generative AI degrades the environment:

One, training the gigantic Generative AI models requires enormous amounts of energy, leading to vast carbon emissions. As an example, training a 213mn Generative AI model just once can spew out the same carbon emissions that 125 New York-Beijing round flight trips would! This is a small model, GPT3 is 800 times bigger with 175bn parameters and GPT4 and Google’s Bard are possibly even larger. Besides, most of these models are trained multiple times to achieve optimum accuracy.

Two, most of these models live on the cloud; for instance, GPT is on Microsoft Azure. The ‘cloud’ is nothing but hundreds of data centres around our planet, guzzling water and power in massive quantities. A recent Guardian article revealed that data centres currently consume 200 terawatt hours per year, roughly equal to what South Africa does today. With the emergence of Generative AI, it is estimated that by 2030, this electricity consumption will soon cross that of Japan, the world’s third largest economy! A global semiconductor conference recently predicted that the computing demand worldwide could outstrip the total world electricity power generation within 10 years.

Three, the bedrock of Generative AI models are the chips produced by the likes of TSMC and Nvidia. The colossal chip fabrication plants or fabs require huge amounts of electricity and pure water. A typical fab might require up to 5 million gallons of water and 30 to 50 megawatts of peak power a day – about the needs of a town with 50000 residents.

As Big Tech companies across the world, race to build larger and larger models, the cloud providers build ever more powerful clouds, and the semiconductor companies strive to build hundreds of more fabs across the world to satiate the demand of Generative AI and other technologies, the carbon footprints increase exponentially, clean power struggles to keep up, and the water tables plummet. It is a bleak picture, and what can we do about it? The first is to build this awareness among communities and societies. A lot of tech companies are aware of this, and Microsoft, Google and others have pledged to make their clouds ‘green’ in the coming decades. However, there are other things that the industry can do. Each time a model is created or trained the producer must estimate and budget the carbon footprint, so they

know what they are dealing it. Many use cases do not require a huge model, a smaller model using far less resources could do the job. Just throwing more compute power will not make a better model, there are other finetuning techniques which are much less power intensive. The good news is that the Big Tech companies have realised this, and are looking at smaller models, training them in places with cleaner energy, using specialised lower-consumption data centres, and tweaking training protocols to reduce the footprint. Indian companies also have stepped up on this; for instance, NTT and Airtel have set up captive solar plants to power their own data centres and Hyderabad-based CtrlS has proudly become the world’s first LEED certified Platinum Green Data Centre

Going forward, both governments and communities need to participate in this effort too. Many governments seem to be currently blinded by the dazzling possibilities of AI and Generative AI and rolling out incentives for new data centres and fabs; they should start factoring in the environmental issues. People and societies should weigh the benefits of this infrastructure being created in their community, and whether enough is being done to counter the degradation. If we do not wake up, we will not have to wait for a Terminator-like AI superintelligence threat, the acceleration towards global climate events would annihilate us sooner than that.