I'm seeing some glaring problems from the author's analysis. The biggest is that the author is mixing together freshwater consumption in industry, agriculture, and power generation vs. potable drinking water. From my quick searches, industry, agriculture, and thermoelectric power generation, generally consume massive amounts of non-potable water. This can certainly put strain on reservoirors, aquifers that are also the source of water which is purified for drinking water in localities with low freshwater overall. . However, this ignores the problem entirely about consuming capacity for purification, which data centers do consume that agriculture and industry, agriculture, and thermoelectric power generation do not. Mixes these two together for percentages, but it conceals the additional strain on local water systems specifically for datacenters that isn't present with the other industries being called out for high water consumption. My local water co-op is currently servicing two large datacenters, and two more are going in right now. One is a "good citizen" that is using a closed-loop system that consumes a small fraction of water, similar to another non datacenter business, the other datacenter is using an open-loop system which is the dramatically larger consuming method. Why does a datacenter use one of the other? Open-loop is significantly cheaper to build and power for the owner. Our local water system is getting strained by the increase in data center growth and we're having to expand water purification and delivery infrastructure in the county. Data centers aren't generally employers of large number of workers, so this means we're losing capacity in our locality to host other businesses that would drive local growth. Lastly, data the author cites is from 2023 and 2024. The 2023 data would nearly be considered ancient history in the AI/LLM world. Keep in mind, ChatGPT was only released in 2022.