We Need to Talk About Generative AI: A New Blog Series

I’m not an ethicist. I’m not a technologist. And I can definitely attest that reading one Michio Kaku book does not a futurist make. But to not be curious, concerned, thrilled, terrified and generally fascinated by Artificial Intelligence is to bury your head in the proverbial sand (and yes, I know ostriches don’t actually do that.) Or at the very least, ignoring AI is to make the same mistake scientist Clifford Stoll made in 1995:

“I’d say [the Internet is] not that important. I think it’s grossly oversold and within two or three years people will shrug and say, ‘”Uh yep, it was a fad of the early 90’s and now, oh yeah, it still exists but hey, I’ve got a life to lead and work to do. I don’t have time to waste online.”

And, in the ad/marketing world, to ignore AI is to sign your organization’s death warrant. AI isn’t coming: it’s here. And not only is it here, it’s already making fundamental changes to the way marketers, strategists, creatives and technologists do their work. Which makes it incumbent on us, an agency with clients who look to us to innovate and eschew the status quo, to ask our questions and take part in a global conversation about what it all means.

Generative AI Effects

For our industry that largely means talking about the impacts, both positive and negative, that come with Generative AI specifically. If you or anyone you know have used ChatGPT or DALL-E, that’s generative AI. There are scores of variations of artificial intelligence, but generative AI is (in the most simple of simple terms) the technology that takes extant data, rearranges those billions of inputs in new and useful ways, and uses it to respond to user requests to do or make something.

This makes generative AI incredibly useful for thousands of everyday tasks in marketing and technology. Need campaign ideas? Ask AI. Need a blog post? Ask AI. Need help laying down the base code for a new website. Well, thankfully, only a human being can handle that one.

Just kidding. AI can do that, too.

So you might be wondering: is AI good? Yep! It’s helpful on a number of levels, in ways that free up human brain power to focus on more complex and strategic thinking. You may also be thinking “Wait, I thought there were huge problems with AI…” Right again. It can be used for some pretty duplicitous (or downright deceptive) purposes, there are ethical questions about who gets credit for things created by generative AI, and then there’s the ever-present fear of the whole planet getting Skynet-ed.

So we’re going to spend a few weeks (months?) exploring the good, the bad, and the ugly of AI and how it can, and almost certainly will, transform the way we do almost everything in our industry. Buckle up.

Environmental Sustainability

One of the most persistently overlooked impacts of the wonders of generative AI is the massive energy consumption required to power the physical infrastructure that underlies the systems. While the past few years have seen a flurry of concerns about the environmental impact of cryptocurrency, the recent proliferation of generative AI comes with its own sustainability concerns.

These large language models comprise hundreds of billions of parameters, and the computing power required to run those operations is gargantuan. By some estimates, the amount of energy needed to power GPT3 could have powered 120 U.S. homes for a year. That same amount of energy would take the average Tesla nearly 4 million miles. GPT3 also consumed about 700,000 liters of fresh water—that’s about 190,000 gallons for those of us in the U.S. who refuse to get with the times and use the metric system.

I should also mention one small detail. Those eye-popping consumption numbers were just to get GPT3 going. That’s before anyone even used it.

Another compounding factor is that thus far we’ve only talked about GPT3 as an example. That’s just one AI platform. The knock-on effect of hundreds and thousands of generative AI platforms coming online could create some serious environmental impacts. But, it’s not all doom and gloom for the future of AI when it comes to energy consumption. Kate Saenko, associate professor of computer science at Boston University, notes that there are reasons to be hopeful:

“The good news is that AI can run on renewable energy. By bringing the computation to where green energy is more abundant, or scheduling computation for times of day when renewable energy is more available, emissions can be reduced by a factor of 30 to 40 compared to using a grid dominated by fossil fuels.”

And the race to make AI systems less of a burden on the planet is already in motion. Even now, data farms in Iceland are harnessing hydroelectric and geothermal power for power, and Switzerland is experimenting with massive physical batteries that use the gravitational potential energy of 35-ton concrete blocks. So it’s not all bad. Like any nascent technology, it’s almost certain to become more efficient, more cost effective and, hopefully, less environmentally taxing to operate.

Thanks for sticking with us. Next time, we’ll have the dreaded job automation conversation.

—

*The content above was 100% written by a human being. I did use the internet, though. Sorry, Clifford Stoll.