Shaolei Ren
Engineering Professor
UC Riverside engineering professor whose research uncovered the “secret water footprint” of AI — showing that training and running large models silently evaporates millions of litres of fresh drinking water.
In his words
Water used for AI computing is mostly “blue water” — fresh water from rivers and lakes, which humans could use directly.
Biography
Shaolei Ren is an associate professor of electrical and computer engineering at the University of California, Riverside, specialising in sustainable computing. In 2023 he and his co-authors published “Making AI Less ‘Thirsty,’” the paper that first quantified how much fresh water the AI boom quietly consumes through data-centre cooling and power generation.
The water AI drinks
Ren’s team estimated that training GPT-3 in Microsoft’s U.S. data centres could directly evaporate around 700,000 litres of clean freshwater, and that a short exchange with a chatbot can consume the equivalent of a 500-millilitre bottle. Scaled up, they projected that global AI could account for 4.2 to 6.6 billion cubic metres of water withdrawal by 2027 — more than the total annual withdrawal of several countries.
His warning lands hardest because much of this happens in drought-stressed regions where data centres compete with households for the same aquifers, largely invisibly. Ren has since joined a United Nations panel probing AI’s environmental impact and argues for transparency first: “we need to know what water consumption is so that we can make an informed decision.” His accounting complements the energy work of Alex de Vries and the broader environmental critique of Kate Crawford.
Where they stand in the war
Who backs them up
Sources & further reading
Canonical record: https://battlelines.ai/topic/shaolei-ren