Intelligence as a Utility Bill
If cognition is becoming metered infrastructure, what are we using it for?
We are witnessing the transformation of thinking into infrastructure.
For the entirety of human history, intelligence was bound to biology. If you needed strategy, analysis, or translation, you had to find a human brain. Today, that connection is permanently broken. Intelligence is becoming a utility bill—a metered, scalable flow of cognition that you plug into, pay for by the token, and scale up or down like electricity or water.
But as intelligence turns into raw infrastructure, we are forced to ask a question we have never had to answer before:
If cognition is becoming a utility bill, what is the bill actually for?
Audio companion
The Price of a Hand
A short audio companion for the essay. Press play if you want the mood underneath the argument.
Cheap Intelligence, Unequal Power
Once intelligence gets cheap, direction becomes the bottleneck. The question becomes who can command cheap thinking at scale, feed it better inputs, and aim it at outcomes that compound.
Power has always been intelligence multiplied by leverage.
In the agrarian era, leverage was land and physical labor. In the industrial era, it was capital, steam, and factories. In the digital era, it was code and distribution networks. AI adds scalable cognition to the stack. Cheap cognition accelerates concentration for whoever already owns leverage.
Basic thinking becomes a commodity. The chatbot spreads fast, then loses its edge as an advantage. The durable edge moves to the owners of proprietary datasets, physical infrastructure, capital, distribution channels, and sovereign authority.
Everyone gets the chatbot. The owners get the compounding machine.
When intelligence becomes abundant, raw intelligence becomes less scarce. The scarce things become leverage, judgment, trust, and taste.
The Tanzania Contrast
This is where the AI conversation becomes geographically and morally strange. Humanity is already living several futures at once.
I was recently in Tanzania, talking with locals. In the Silicon Valley echo chamber I live in, the daily language is AGI timelines, token throughput, model capability, and human obsolescence. There, the future arrives as a technical argument.
In Tanzania, the future sounded plainer. A normal life. School for their kids. A $200-a-month salary. That number does real work in the argument. One group is debating whether work survives intelligence abundance. Another is trying to reach the first reliable rung of work at all.
We asked questions about the country, its history, and the web of local cultures around us. Some locals had fragments. We had ChatGPT and AI search open, checking their history and local context in real time. As foreigners, we could build a working map of their past faster than some people living inside it could explain it.
That is leverage you can feel in a conversation. Access, language, bandwidth, confidence, and a tool that turns curiosity into an answer before the next question lands.
Then we drove out and saw elephants and lions on the savannah. They gave no fucks about any of it. Their day was food, heat, threat, distance, grass.
Silicon Valley’s future, Tanzania’s future, and the savannah’s future were running beside each other on the same planet. The argument about AI gets dishonest when it treats one of them as the master timeline.
The Priority Gap
That contrast is hard to sit with. In one part of the world, we are spending hundreds of billions of dollars building machines that write corporate emails, generate targeted advertising, optimize sales funnels, and summarize meetings. In another, basic physical survival remains unsolved.
The numbers make this priority gap brutal:
- The World Food Programme (WFP) reports that 363 million people are at risk of acute hunger in 2026. [1]
- WHO and UNICEF estimate that 2.1 billion people still lack safely managed drinking water. [2]
- Meanwhile, Stanford’s AI Index reported $252.3 billion in corporate AI investment in 2024 alone. [3]
- The IEA projects data-center electricity use could double to about 945 TWh by 2030. [4]
Too much of this intelligence is being pointed at small commercial optimizations before it is pointed at large human needs.
This is not a naive argument that AI is bad. It is an argument that the real test of our era is not AI capability—it is human direction. Power without purpose is just acceleration. And acceleration without humanity is not progress. It is just speed.
What is it for?
Ultimately, people do not want tokens. They do not want models, and they do not want productivity dashboards. They want:
- Less fear.
- Safe children.
- Food on the table.
- Clean water from the tap.
- Work that gives dignity.
- Health, meaning, and enough agency to breathe.
If metered intelligence cannot move us closer to solving these ancient, physical, human problems, then we have built the greatest cognitive engines in history and pointed them at the smallest possible goals.
The tragedy of AI will not be that it destroys us.
The tragedy will be that it reveals our priorities, and we fail the test.
Maybe the future of humanity will not be decided by whether AI becomes smarter than us, but whether we become wise enough to use it for anything that actually matters.
Run this essay on your own work
Paste this into ChatGPT or Claude. It applies the essay's framework to your situation, and asks for your context first.
You are auditing what I actually spend intelligence on, now that thinking is metered like electricity. Work in this order: 1. Review your memory of me, and my past chats if you can search them. Classify what I have been buying with all those questions: commodity thinking anyone could ask for, or judgement, taste, and leverage that compound. 2. If your record of me is thin, ask what I do, what assets and relationships I control, and where my income actually comes from. 3. Apply the rule: power is intelligence multiplied by leverage — proprietary data, capital, distribution, authority. Cheap cognition compounds for whoever already owns leverage. Then give me two ranked lists — what in my position erodes as intelligence gets cheap, and the leverage to start building now, with the first concrete move for each — plus the one habit in my AI usage you would change first. If you can browse the web, read the full essay first — it carries the complete argument and sources: https://thejop.com/essays/intelligence-utility-bill/ Prompt from "Intelligence as a Utility Bill" — Johnny Opinion Press, thejop.com
Sources
- [1]A global food crisisWFP · accessed 2026-06-17
- [2]Progress on household drinking water, sanitation and hygiene 2000-2024WHO/UNICEF Joint Monitoring Programme · accessed 2026-06-17
- [3]Artificial Intelligence Index Report 2025Stanford HAI · accessed 2026-06-17
- [4]Energy and AIIEA · accessed 2026-06-17
“The danger is not that intelligence becomes cheap. The danger is that cheap intelligence reveals how small our ambitions are.”
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