Data Centres, Water, and the Danger of Big Scary Numbers in the Workplace

This week Barry Phillips calls for better critiquing in the workplace of the big stats relating to AI and Data Centres

Transcript

Hello Humans!

And welcome to the weekly podcast that aims to address an important AI issue relevant to HR in five minutes or less.

Today I want to talk about water, data centres, and one of the great workplace diseases of our time: the big scary number with no context.

You’ve probably seen headlines saying data centres are “guzzling” water. And yes, data centres use water. Some use a lot of it, especially where water is used for cooling. That matters. Local communities are right to ask hard questions.

But here’s the problem. A number on its own is not a fact. It’s a fact-looking object. Rather like a dodgy CV, it may contain elements of truth, but it still needs checking.

Take the new Amazon data centre campus in Indiana. One figure doing the rounds is that it could use around 300 million gallons of water a year. That sounds enormous. And in one sense, it is enormous. Most of us don’t pop to the kitchen tap and casually draw 300 million gallons before breakfast.

But scale matters.

There are around 16,000 golf courses in the United States. U.S. golf facilities use in the region of 500 billion gallons of water a year. That works out at about 1.4 to 1.5 billion gallons every single day.

So, if we take the Amazon figure at face value, its annual water use is not more than a day of American golf-course irrigation. It is closer to five hours.

Five hours.

In other words, the data centre is presented as a thirsty monster, while the golf courses are quietly out the back drinking from a fire hose.

And almonds? California almond production is another useful comparison. Estimates vary, but almond farming in California appears to require several times more water than direct U.S. data-centre consumption. Again, that does not mean almonds are evil. I’m not here to cancel almond croissants. That would be a dark day for civilisation.

The point is simpler. When we talk about sustainability, AI and technology, we need proportion. We need context. We need grown-up thinking.

And that is where HR comes in.

You might be thinking, “What has this got to do with HR?” Quite a lot, actually.

First, HR is often responsible for how organisations train people to use AI. If employees are being told “AI is destroying the planet every time you write an email”, they may avoid useful tools for the wrong reasons. Equally, if they are told “AI has no environmental impact at all”, they are being sold fairy dust in a data-centre-branded bottle.

Neither is good enough.

Second, HR has a role in organisational trust. Employees are increasingly sceptical of corporate statements on sustainability, technology and ethics. And frankly, they should be. Some statements deserve scepticism. But scepticism is not cynicism. Cynicism says, “Everything is rubbish.” Scepticism says, “Show me the evidence.”

That is a workplace skill.

Third, HR should be helping employees build what I’d call “context literacy”. Not just digital literacy. Not just AI literacy. Context literacy. The ability to hear a big number and ask: compared with what? Over what period? Local or national? Water withdrawn or water consumed? Drinking water or reclaimed water? Direct use only, or including electricity generation?

Those questions are not pedantic. They are the difference between insight and panic.

So here’s a practical workplace idea. The next time your organisation discusses AI, sustainability or digital transformation, don’t just ask, “Can we use this tool?” Ask three better questions.

What is the real environmental impact?

What are we comparing it with?

And are we being honest enough to admit what we do not yet know?

Because the future of work will not be shaped only by technology. It will be shaped by whether people can think clearly about technology.

 In the AI age, organisations will not just need faster systems. They will need calmer minds. People who can pause before sharing the scary statistic. Leaders who can separate risk from rumour. Cultures where evidence beats outrage.

Because misinformation does not always arrive wearing a tin-foil hat. Sometimes it arrives in a smart infographic, with a dramatic headline and a number big enough to frighten the finance director.

So yes, let’s challenge data centres. Let’s demand transparency. Let’s ask hard questions about water, power and local impact.

But let’s also challenge bad comparisons.

The real workplace skill of the next decade may not be knowing all the answers.

It may be knowing when a big number is trying to mug your judgement in broad daylight.