Let’s Build AI Data Centers, We’re Not Going To Meet Climate Goals Anyway – Eric Schmidt

The ongoing boom in artificial intelligence (AI) has sparked a massive surge in spending on data centers, which are essential for providing the computational power needed to train and operate complex AI models.

However, this rapid expansion comes with significant environmental costs, as data centers require vast amounts of energy to function. According to a report from McKinsey, data centers are projected to consume 35 gigawatts of power annually by 2030, a significant increase from the 17 gigawatts used in 2023.

The energy demands of AI are emerging as a challenge to global climate goals, especially in the U.S., where the Biden administration has set ambitious targets for the power sector to become carbon-neutral by 2035 and for the U.S. economy to reach net-zero emissions by 2050. However, AI’s rapid growth, with its enormous energy consumption, threatens to derail these efforts, as many in the industry are turning to fossil fuels to meet energy needs.

Eric Schmidt, former CEO of Google and a prominent figure in the AI industry, voiced these concerns at an AI summit in Washington D.C. last Tuesday. His comments underlined the mounting tension between AI’s energy needs and the global push for decarbonization.

Schmidt, who also chaired the National Security Commission on Artificial Intelligence, acknowledged that while there are potential solutions to mitigate AI’s environmental impact, such as better batteries and more efficient power infrastructure, these measures are unlikely to keep pace with AI’s skyrocketing demand for resources.

“All of that will be swamped by the enormous needs of this new technology,” Schmidt said during his speech. “Because it’s a universal technology, and because it’s the arrival of an alien intelligence we may make mistakes with respect to how it’s used, but I can assure you that we’re not going to get there through conservation.”

Schmidt’s remarks highlight a notable shift in the tech industry, where early enthusiasm for achieving climate goals is giving way to a more pragmatic approach, driven by the extraordinary resource demands of AI. For years, tech companies like Google, Amazon, and Microsoft were at the forefront of efforts to reduce their carbon footprint and champion renewable energy.

However, as AI advances at an unprecedented pace, many companies are now grappling with the realization that maintaining sustainability commitments might not be feasible without significantly rethinking their approach.

When asked whether AI’s energy demands could be met without abandoning conservation goals, Schmidt expressed skepticism.

“I don’t think we’re going to hit the climate goals anyway because we’re not organized to do it,” he said.

This sentiment reflects a growing recognition within the tech industry that while sustainability remains an important goal, the rapid expansion of AI may take precedence. For Schmidt, the focus is less on restricting AI to meet climate targets and more on leveraging AI’s potential to solve global challenges.

“Yes, the needs in this area will be a problem,” Schmidt said, “but I’d rather bet on AI solving the problem than constraining it and having the problem,” he said.

Over the past decade, companies like Google and Microsoft committed to substantial investments in green energy and pledged to reduce their carbon footprints. Google, for example, has long prided itself on its efforts to be the first major company to run completely on renewable energy. Yet, the energy demands of AI threaten to undercut these efforts, as the resource-intensive nature of AI technology—particularly the computational power required for training large models—pushes companies to seek more immediate, and often less sustainable, solutions.

The environmental impact of AI is already being felt, and it has vast implications. McKinsey’s report said that if current trends continue, data centers will become one of the largest consumers of energy worldwide. This surge in energy use is not only a threat to climate goals but also a stark indication of how AI is reshaping the tech industry in unexpected ways. The pressure on power grids and the need for more resources have prompted some companies to revert to fossil fuels to keep pace with AI’s growth.

Schmidt’s comments highlight the broader implications of this energy-intensive technology. While AI holds incredible potential to revolutionize industries and solve complex global problems, its environmental footprint cannot be ignored. Schmidt, who in 2022 founded White Stork, a defense company that uses AI for drone technology, has previously spoken about the need to harness AI’s capabilities for purposes like national security.

At a lecture at Stanford University in April, Schmidt described the war in Ukraine as a turning point that led him to become an “arms dealer,” using AI to develop drones for “robotic wars.” His statements further underline AI’s far-reaching impact beyond the tech sector, showing how its applications are extending into areas like defense, which brings additional energy demands and environmental concerns.

Schmidt’s view that AI growth will eventually outstrip preventive measures reflects a broader shift in the tech industry’s relationship with sustainability. As companies increasingly prioritize AI development over environmental concerns, they risk sidelining the very climate goals they once championed. This shift is mirrored across the industry, where executives and policymakers alike are reevaluating how to balance the demands of AI with the urgent need to combat climate change.

In the race to develop more sophisticated AI models, companies are finding that energy requirements are becoming a significant obstacle. The surge in energy demand has spurred discussions about how best to address AI’s environmental impact without stifling innovation. For some, like Schmidt, the solution lies in continuing to push the boundaries of AI and hoping that the technology itself can eventually offer solutions to the problems it creates.