AI-powered chatbots and image generators can feel like magic, but that magic comes at a steep environmental cost.

They're trying to promote AI as this transformative technology and they're glossing over the fact that there's some trade-offs here.

It's Wednesday, February 21st and after consulting with the relevant experts, it's Science Friday. I'm Scifra producer D Peter Schmidt.

Researchers are learning that the data centers used to power AI models like chat GPT

need an enormous amount of not just electricity, but fresh water to keep everything

running smoothly.

And the industry shows no signs of slowing down, as Open AI is seeking to raise $7 trillion to reshape the global semiconductor industry for AI chip production.

Dr. Jesse Dodge, research scientist at the Allen Institute for AI, joins Ira to talk about how much energy and water these

data centers are using and what regulations these companies could face.

Welcome to Science Friday.

Hi, thanks for having me.

You're welcome. Okay, so why do these AI models use so much energy?

Today AI systems are run on supercomputers. When I started doing AI research more than a decade ago, I was able to run most of the

training and production of AI systems on my laptop, but what we've seen over the last decade is this dramatic increase in computational

cost that's led to today's environment where most of the AI that you will interact

with online is run in a data center and primarily run on

GPUs. These GPUs are often very specialized hardware that are pretty

energy intensive.

So people don't often think about it,

but when you type a query to a chatbot or

search for something online,

that now has a significant energy consumption and therefore environmental impact.

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