Google released a study claiming its Gemini AI uses just five drops of water per text prompt, but environmental experts are calling the research misleading for omitting critical indirect water consumption from power generation. The controversy highlights growing scrutiny over AI's true environmental cost as data centers expand globally.
Google just sparked a fierce backlash from environmental researchers over its new study claiming Gemini AI uses barely five drops of water per text prompt. The tech giant's research, released amid mounting pressure over AI's environmental toll, puts water consumption at just 0.26 milliliters and energy use equivalent to watching TV for nine seconds. But leading experts are calling it a masterclass in corporate obfuscation.
"They're just hiding the critical information," Shaolei Ren, an associate professor at UC Riverside who studies AI's environmental impact, told The Verge. "This really spreads the wrong message to the world."
The controversy centers on what Google left out. The company's figures only account for direct water cooling in data centers, completely ignoring the massive indirect water consumption from electricity generation. According to Bloomberg analysis, the majority of a data center's water footprint actually comes from power generation - water that's used in gas and nuclear plants to create steam for turbines and cool reactors.
"You only see the tip of the iceberg, basically," says Alex de Vries-Gao of Digiconomist and PhD candidate at Vrije Universiteit Amsterdam, who has extensively studied data center energy consumption. When accounting for total water usage including power generation, previous research has found AI prompts can consume up to 50ml of water - nearly 200 times Google's estimate.
Google's methodology choices are equally problematic, experts argue. The study uses only "market-based" carbon emissions accounting, which factors in Google's renewable energy purchases, while ignoring "location-based" emissions that reflect the actual environmental impact where data centers operate. This approach follows corporate preferences rather than Greenhouse Gas Protocol standards that call for reporting both metrics.
The timing couldn't be more pointed. AI's voracious appetite for computing power has triggered a massive buildout of gas and nuclear plants to meet soaring electricity demand. Meta recently announced plans for gas-powered data centers, while Google itself has struck deals for small modular nuclear reactors to power AI operations.
Despite Google's claims of dramatic efficiency improvements - a 33x reduction in energy per prompt over the past year - the company's overall environmental footprint tells a different story. Google's "ambitions-based carbon emissions" jumped 11% last year and 51% since 2019, according to its latest sustainability report. The company also quietly started excluding certain emission categories from its climate goals this year.
"If you look at the total numbers that Google is posting, it's actually really bad," de Vries-Gao notes. The efficiency gains Google touts may be real, but they're being overwhelmed by the Jevons paradox - where efficiency improvements lead to increased overall consumption.
Google executives Amin Vahdat and Jeff Dean defended the research as providing "more standardized parameters" for measuring AI's environmental impact. The company claims to go further than previous studies by including energy from idling machines and cooling infrastructure. But the paper hasn't undergone peer review, and Google spokesperson Mara Harris only said the company is "open" to submitting it in the future.
The academic community isn't buying it. Ren criticizes Google for using median rather than average calculations while refusing to share underlying data about prompt lengths or token counts. "This really spreads the wrong message to the world," he argues, especially as policymakers worldwide grapple with regulating AI's environmental impact.
The dispute reflects broader tensions as Big Tech races to dominate AI while facing growing scrutiny over sustainability claims. As data centers consume ever more water and electricity, Google's study appears designed more for public relations than scientific rigor - a concerning trend as the AI boom accelerates without adequate environmental oversight.
Google's Gemini water study represents a troubling trend of corporate environmental accounting that obscures rather than illuminates AI's true impact. While the company touts efficiency gains, its overall emissions continue climbing as AI deployment accelerates. The expert criticism highlights the urgent need for standardized, transparent environmental reporting as policymakers worldwide wrestle with AI regulation. Until companies like Google provide complete data including indirect impacts, the tech industry's sustainability claims will remain as shallow as five drops of water.
