Why I Always Ask: Which AI?

Recently, I had a call with a doctor who wanted to discuss a possible workshop collaboration. I love a good debate, but somewhere between introductions and logistics, the conversation became an hour-long monologue about the dangers of data centres and the existential threat of AI.

What struck me wasn’t her intensity - it was how easily we all slip into talking about 'AI' as if its one thing. As a cosmetic doctor, she almost certainly uses tools powered by AI every day: diagnostic imaging, scheduling algorithms, facial-mapping tech. They just don’t come branded as AI.

That’s the problem with how we talk about artificial intelligence. We use it like an umbrella term for everything from a chatbot to medical diagnostics. The word has become a catch-all for both innovation and fear.

When people say they’re “anti-AI,” I always want to ask, which AI? The one helping doctors detect early signs of illness? The one optimising renewable energy? Or the one generating your meeting summaries?

But whether we call it medical AI, creative AI, or generative AI, all of it still relies on the same hidden foundation: the physical infrastructure that keeps the digital world alive. Every query, upload, and model runs through a network of servers, cables, and cooling systems. These are the engines of our so-called intelligence.

When people talk about AI as if it floats in the cloud, they miss the truth that it lives in buildings, powered by electricity, cooled by water, and maintained by people.

That’s exactly why infrastructure literacy matters. Digital inclusion isn’t just about learning how to use technology; it’s about understanding what’s behind it. The servers, the energy, the data, and the human labour keeping it all running.

You can’t build ethical technology on vague language, and you can’t discuss AI responsibly without understanding the systems that sustain it.

Precision isn’t pedantic, it’s power.

Next time someone tells you they’re anti-AI, ask them which one.