Big tech 'covering up the threat AI poses to the climate'

The likes of Apple, Microsoft, Google, Amazon and Meta are deliberately talking up the “profound risks to society and humanity” from the rise of artificial intelligence to distract from the risks the technology poses now because they do not want to engage in that conversation.

That is according to Stephanie Hare, author of Technology is Not Neutral, who told The Scotsman’s annual data conference that the focus should be on the “now risks” of AI rather than what will happen in the future.

Her comments refer to an open letter signed by more than 1,100 executives in the tech industry – who just so happen to work at some of the biggest companies in the world – published by non-profit campaign group the Future of Life Institute in March. The letter demanded that the development of advanced AI systems is paused.

Hare told delegates at the conference, “Data Futures, AI Futures”, hosted by The Scotsman and the Data-Driven Innovation initiative, that this could be linked to climate change, highlighting that while putting the scale of the AI future risk on a par with pandemics and nuclear war, it may not mention of global warming.

This was because large data centres used by big tech need vast amounts of water and electricity to operate, Hare claimed. She added: “We think about the cloud – such a beautiful image of nature comes to mind. We’re not thinking about warehouses with thousands and thousands of servers, humming with electricity. It is very energy-intensive and water-intensive [to cool the servers]. And we don’t have transparency around how much water data centres use, because they aren’t required to report it.

“These companies love to hoover up everyone’s data… but don’t like to share about their data centres. They consider it proprietary information – corporate secrets – but there is a water scarcity problem on the planet.”

Hare argued the increasing widespread use of AI models could make things far worse. She continued: “Chat GPT was made available to the public in November, 2022, and became the fastest-starting app in history with 100 million active users by February, 2023. It’s hard to verify, but people are now saying up to 200 million.”

Hare cited research by Professor Kate Crawford, which claimed that a typical ChatGPT exchange of 20 to 50 questions consumed half a litre of water.

“Every time you use ChatGPT, imagine taking half a litre of water and pouring it on the ground,” Hare asked the event audience, “for me, this is a very powerful visual.

“Maybe if people knew what the water cost of ChatGPT was, perhaps they wouldn’t be so quick to use it. Having transparency around data allows you to make different choices. A community or country can decide to site a data centre near sources of water, so people know how much they are consuming.”

Hare stressed that the letter had been signed by many very credible scientists and leaders in the field – who called for a pause on developing AI. “Who’s supposed to pause?” she asked. “The people who signed the letter are not going to stop, so what were they really asking for?

Tougher regulation on examining climate data could have a huge effect, she argued, adding that “if you don’t have transparency on data, you cannot do effective governance, regulation and policymaking. The big thing is who gets priority over the needs for water and electricity when machines needed to run our entire cities are so embedded in human society. If you have a drought situation, do you shut off the water of a city of, say 70,000 with a data centre based there powering the infrastructure for millions?

“But we don’t want to throw the baby out with the bathwater. There are lots of really exciting benefits that we will get from AI, we just want to do it sustainably, responsibly and ethically. The data on water and carbon footprints is not publicly available. Companies need to be compelled to share it. Then we can have discussions about hosepipe bans, water restrictions, electricity prices, and energy bills.

“All those things are going to be turbo-charged as AI Large Language Models are integrated into our society on a much larger scale. Before we do that, we have a really exciting opportunity to get the building blocks right.”