Climate Change is the Focus at COP28: Technology Must Be Included in the Dialogue

There is another topic that rarely makes it to conversations on climate change – technology. Since last year, the advent of Generative Artificial Intelligence (GenAI) has created a wave of frenzied excitement,

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COP28

Soaring daily temperatures, wildfires in Canada, inexplicably hot ocean currents; the worries around climate change have intensified. The COP28 Summit currently underway in Dubai is looking at all the ways in which human activity is creating uncertainty in the climate as we know it, impacting our lives in a multitude of ways.

There is another topic that rarely makes it to conversations on climate change – technology. Since last year, the advent of Generative Artificial Intelligence (GenAI) has created a wave of frenzied excitement, as well as a shadow of worry on whether we have created a Frankenstein that we may not be able to control. What is considerably less talked about is how AI and GenAI 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 are AI and GenAI. There are three ways in which GenAI degrades the environment:

·         One, training gigantic GenAI models requires enormous amounts of energy, leading to vast carbon emissions. For example, training a 213mn GenAI model just once can spew 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 uses today. With the emergence of GenAI, 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 predicted that the computing demand worldwide could outstrip the total world electricity power generation within 10 years.

·         Three, the bedrock of GenAI 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 amount a town with 50,000 residents would use each day.

 

As Big Tech companies across the world, race to build larger and larger models, cloud providers build ever more powerful clouds, and semiconductor companies strive to build hundreds of fabs across the world to satiate the demand for GenAI 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?  We must build awareness among communities and societies by bringing Technology and its impact on climate change into conversations at large climate summits around the world. This will create an environment where Big Tech can participate in the dialogue and be responsible while they continue to create cutting-edge technologies that make our world a better place.

 

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 with. Many use cases do not require a huge model, a smaller model using far fewer resources could do the job. Just throwing more compute power will not make a better model, there are other fine tuning 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 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.

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