The Delusion of AI — Episode 1 of 4
Imagine walking into your kitchen to toast one tiny marshmallow.
Instead of lighting a small flame, you turn on all four stove burners. You crank the oven to maximum heat. You start the microwave. Then you switch on every appliance in the house at the same time.
You would never do that.
It would feel absurd. Wasteful. Almost comically excessive.
And yet, every time we send a casual prompt to a generative AI tool, something similar happens somewhere in the background.
A sentence appears on our screen in three seconds.
A caption is written.
An email is polished.
A strategy is summarized.
A video is generated.
The whole experience feels light, clean, instant, and almost free.
But it is not free.
It is powered by electricity. It is cooled by water. It is supported by land, servers, chips, cables, backup power, and a growing industrial infrastructure most users never see.
This is the first delusion of AI dependency:
We think we are using something weightless.
In reality, we are leaning on one of the heaviest machines humanity has ever built.
The interface is clean. The system is not weightless.
AI feels frictionless because the screen hides almost everything.
We sit in a chair, type a short instruction, and receive a polished answer almost instantly. The response looks like thought. Sometimes it even feels like magic.
But there is no magic in physics.
There is only infrastructure.
Far away from the clean interface, there are data centres: huge buildings filled with servers, advanced chips, cooling systems, cables, transformers, backup generators, and constant energy demand.
These machines do not simply “think” in the air.
They run.
They heat up.
They need cooling.
They draw electricity from real grids.
In many places, they rely directly or indirectly on water.
They occupy land.
They expand into communities.
They compete for power capacity with homes, businesses, factories, hospitals, and future development.
We call it “the cloud” because the word sounds soft.
But the cloud is not floating above us.
It is sitting somewhere.
On land.
Connected to power.
Managing heat.
Using water.
Expanding through real infrastructure.
The interface feels weightless because the weight has been moved somewhere else.
AI is not just search
For decades, most of us understood the internet through search.
A search engine usually retrieves something that already exists: a page, a link, an article, a file, a result.
Generative AI does something different.
It does not only retrieve.
It produces.
It predicts, calculates, rewrites, summarizes, generates, reasons, and sometimes runs through several hidden steps before giving us an answer.
That difference matters.
A casual AI interaction may feel similar to typing something into Google, but behind the scenes it can require far more computation.
Not every prompt has the same cost.
A short answer is not the same as a long reasoning task.
A simple rewrite is not the same as image generation.
A quick summary is not the same as video generation.
A basic question is not the same as a deep research task.
The exact energy cost of one prompt varies depending on the model, hardware, data centre, location, task type, output length, and cooling system.
But the broader truth is clear:
The more powerful the system, the less casual our usage should be.
One person asking AI to rewrite a sentence is not the crisis.
Hundreds of millions of people using AI as the default replacement for thinking, writing, searching, deciding, designing, and creating — that is where the pressure begins.
At scale, small habits become infrastructure problems.
The water problem is easy to ignore
The hidden cost of AI is not only electricity.
It is also water.
Data centres generate heat, and heat has to be managed. Depending on the location and cooling method, water can become a major part of keeping those systems operational.
That water is invisible to the user.
You do not see it leaving a local system.
You do not see it evaporating.
You do not see the stress it may place on communities already dealing with water pressure.
You only see the answer.
That is the dangerous part.
The cost is real, but the user experience hides it.
We have trained ourselves to think of digital tools as clean because they do not leave smoke in our room.
But environmental pressure does not disappear just because it happens outside our field of vision.
A machine can feel clean to the person using it while still being heavy for the place supporting it.
That is one of the central contradictions of modern technology.
The closer the experience gets to magic, the easier it becomes to forget the machinery behind it.
The grid is now part of the AI conversation
AI is no longer only a software story.
It is becoming an energy story.
A water story.
A land story.
A grid story.
And eventually, a political story.
The International Energy Agency estimated that data centres consumed about 415 TWh of electricity in 2024 and could more than double by 2030.
In Ireland, data centres consumed 22% of metered electricity in 2024.
In parts of the United States, especially data-centre-heavy regions like Virginia, the pressure is already being felt at grid level.
This is not a minor technical footnote.
It is a structural shift.
Because electricity systems do not grow instantly.
Power plants take time.
Transmission lines take time.
Renewable energy projects take time.
Grid upgrades take time.
Permits, land, local opposition, financing, regulation, and infrastructure planning all take time.
AI demand, however, is arriving now.
That creates a tension most users never think about when they ask a model to write a caption, generate a picture, summarize a PDF, or produce a quick idea.
The front end feels instant.
The back end is slow, physical, expensive, and limited.
That gap is where the delusion lives.
This is not an anti-AI argument
Let’s be clear.
The answer is not to reject AI completely.
AI can help doctors.
It can support education.
It can accelerate research.
It can help small teams do work that once required large resources.
It can reduce repetitive work.
It can support people who struggle with writing, language, learning, or access.
It can make businesses more efficient.
Used consciously, AI is not the enemy.
The problem is not AI itself.
The problem is unconscious AI dependency.
The problem is using a powerful industrial system for every tiny mental task without asking whether it is necessary.
The problem is treating AI like air.
Free.
Invisible.
Unlimited.
It is none of those things.
The deeper cost is not only environmental
The environmental cost matters.
But the deeper danger may be psychological.
If we use AI to support our thinking, it can be powerful.
If we use it to avoid thinking, it becomes a cage.
A beautiful cage, perhaps.
Fast.
Helpful.
Polished.
Comfortable.
But still a cage.
The more we outsource small acts of effort, the weaker our own muscles become.
Creative muscles.
Analytical muscles.
Writing muscles.
Decision-making muscles.
Judgment muscles.
That is why AI dependency is so seductive.
It does not feel like collapse.
It feels like convenience.
It feels like productivity.
It feels like progress.
But if our feet never touch the ground, eventually we forget how to stand.
The real question
This is the core of the AI delusion.
We look at our screens and see a beautifully written email, a perfect caption, a polished idea, or a flashy AI-generated video.
And we think:
Look how advanced we are.
We are flying into the future.
But if we look down, the ground tells another story.
We are trading real-world resources — electricity, water, land, grid capacity, environmental resilience, and human mental effort — for digital convenience.
And we are doing it so casually that many of us no longer notice the trade.
The question is not whether we should use AI.
The question is whether we are using it consciously.
Do we need AI for this task?
Is this prompt worth the machine behind it?
Am I using AI to think better, or to avoid thinking at all?
That distinction may decide whether AI becomes a tool that expands human ability, or a system that quietly weakens it.
Because if we burn the house down just to keep the magic chair plugged in, where will we live when we finally want to stand up?
Next in the series
Episode 2: The Internet Eating Itself
What happens to original human creativity when the internet runs out of human ideas, and AI models are forced to feed on themselves?
Did you realize a simple AI interaction could carry a real physical cost?
I would like to hear how you personally think about this tradeoff: useful tool, dangerous dependency, or something in between?
Visit my website.
