The Intelligence Staircase: We May Be Living Through the Moment Tim Urban Warned Us About
A reflection on Tim Urban’s 2015 “The AI Revolution” and the world of artificial intelligence in 2026
Tim Urban’s intelligence staircase was once a thought experiment. Today, it is becoming a framework for understanding a technological transition already underway.
In January 2015, writer Tim Urban published a remarkable two-part essay on his website Wait But Why titled “The AI Revolution: The Road to Superintelligence.”
At the time, artificial intelligence was largely invisible to the average person. Siri could answer simple questions. Google could recognize photographs. Computers could beat humans at chess. But the idea that ordinary people would soon carry on sophisticated conversations with machines, ask them to write software, analyze businesses, reason through scientific problems, create realistic images and video, or independently perform complex work still seemed like science fiction.
Urban’s article was therefore primarily about the future.
Eleven years later, it reads very differently.
We have not arrived at the superintelligence Urban described. Today’s AI remains inconsistent, sometimes makes elementary mistakes, and is nowhere near demonstrating superiority to humans across every dimension of intelligence.
But something important has happened.
We have begun climbing the staircase.
And for perhaps the first time in human history, we are being forced to seriously consider what it would mean to encounter an intelligence that eventually occupies a step above our own.
The Intelligence Staircase
One of Urban’s most powerful ideas was also one of his simplest.
He asked readers to imagine intelligence as a staircase.
Near the bottom are relatively simple animals. As we move upward, cognitive capabilities increase. Eventually we encounter more sophisticated mammals, primates, chimpanzees and finally humans.
The important point is not the precise position assigned to each animal. The staircase is a thought experiment.
It asks us to reconsider an assumption so deeply embedded in human thinking that we rarely notice it: because humans are the most intelligent creatures we encounter, we tend to imagine ourselves as being near the top of intelligence itself.
There is no evidence that this is true.
We may simply be the most intelligent creature that biological evolution has produced so far on this planet.
Imagine an ant. An ant can navigate its environment, communicate chemically with other ants, and participate in a colony that constructs sophisticated nests, organizes labour, defends itself, locates food and adapts to changing conditions.
Place an ant on the floor of the Large Hadron Collider and something interesting happens. The ant can physically experience the machine. It can walk across it. It can encounter its heat, vibrations, surfaces and smells. But it has absolutely no conception of what it is experiencing.
The ant does not know that the machine was designed. It does not understand physics or electricity. It does not know what a proton is. It does not know that humans exist as a technological civilization attempting to understand the fundamental structure of matter.
Most importantly, the problem cannot be solved by explaining it more slowly. You cannot sit beside the ant for six months and teach it particle physics. The limitation is not information. The limitation is cognitive capacity.
That is the unsettling idea at the heart of Urban’s staircase.
The Chimpanzee Looking at the Skyscraper
Urban makes the argument even clearer by moving closer to humans.
Consider a chimpanzee looking at a skyscraper. Chimpanzees are extraordinarily intelligent animals. They can learn symbols, solve problems, use tools, cooperate socially and understand relationships.
But the cognitive gap between a chimpanzee and a human produces an extraordinary difference in what each species can comprehend.
A chimpanzee can see a skyscraper. But it cannot understand structural engineering, architectural drawings, financing a billion-dollar development, electrical engineering, elevators, building codes, project management or the mathematics that allow engineers to calculate the forces acting upon the structure.
And here again is the critical point: we cannot teach the chimpanzee these things.
Urban’s argument is that an intelligence only a few meaningful steps above humanity could create precisely the same relationship between itself and us. A sufficiently superior intelligence might understand concepts that humans are not merely ignorant of, but are biologically incapable of understanding.
That is a much more profound idea than saying that a computer might someday be smarter than Einstein. It suggests there could be categories of thought unavailable to the human mind.
We Have Always Assumed Intelligence Stops With Us
Human civilization contains a peculiar contradiction.
We readily acknowledge cognitive ceilings in every other species. Nobody finds it controversial to say that a dog cannot understand calculus. We do not conclude that the dog simply needs a better teacher. We recognize that its brain does not possess the necessary architecture.
Yet when we reach humans, we quietly abandon the principle. We tend to imagine that given enough time, education and scientific progress, humans can ultimately understand anything that exists.
Why?
There is no obvious evolutionary reason that should be true. Our brains evolved because particular forms of intelligence helped our ancestors survive and reproduce. Evolution did not design Homo sapiens to understand quantum mechanics, cosmology, protein folding, higher-dimensional mathematics or the origin of consciousness.
We acquired enough general intelligence that we eventually discovered those subjects. But that does not mean our cognitive capabilities are unlimited.
There may be questions whose answers are sitting in front of us in much the same way the principles of structural engineering are sitting in front of a chimpanzee looking at the Empire State Building. We simply cannot see them.
That possibility changes the meaning of artificial intelligence.
AI Does Not Necessarily Have Our Biological Ceiling
Human intelligence is constrained by biology. Our brains must operate within limits of energy, size, neural transmission speed, working memory, fatigue and lifespan. We forget things. We have emotional biases. We can consciously concentrate on only a tiny amount of information at once.
Most importantly, upgrading human intelligence is extraordinarily difficult. A brilliant mathematician cannot simply install another billion neurons before breakfast.
Machines operate under different constraints. Computers can gain more memory. They can operate faster. They can be copied. They can access tools. They can communicate with other machines. They can search enormous bodies of information. They can run vast numbers of calculations. Increasingly, AI systems can be given time to reason through problems, evaluate alternatives, use external tools and revise their approaches.
Urban divided AI into three broad categories: Artificial Narrow Intelligence (ANI), systems exceptionally capable within particular domains; Artificial General Intelligence (AGI), intelligence comparable to human beings across the general range of intellectual activities; and Artificial Superintelligence (ASI), intelligence significantly beyond the best human minds across essentially every important intellectual field.
In 2015, humanity lived comfortably in the first category. In 2026, that description no longer fits nearly as comfortably.
What Has Happened Since 2015
The most striking thing about rereading Urban today is how dramatically the technological environment has changed.
In 2015, computers could perform calculations and play games extremely well but struggled with many things humans found effortless. Understanding ordinary images, language and context remained difficult.
Many of those capabilities are now routine.
Modern frontier AI can interpret images, converse across languages, write computer programs, analyze documents, generate images and video, solve mathematical problems, summarize scientific literature and perform increasingly complicated sequences of actions using software tools.
That does not mean today’s AI is universally smarter than humans. Far from it.
One of the strangest characteristics of current AI is its jagged frontier. A system can perform extraordinarily difficult intellectual tasks and then fail at something seemingly trivial. It can solve advanced mathematics and still misunderstand a simple real-world situation that a child immediately recognizes.
So we have not simply created an artificial human brain. We have created something stranger. Its strengths and weaknesses do not perfectly correspond to ours.
The Staircase May Not Have Human-Shaped Steps
When Urban wrote about the Intelligence Staircase, it was natural to imagine an AI gradually climbing through familiar levels: mouse, chimpanzee, average human, Einstein, and then beyond.
Reality may be messier.
Today’s AI can already be dramatically superhuman in certain dimensions while surprisingly poor in others. It can retrieve vastly more information than a human, process large collections of documents extraordinarily quickly, translate among languages almost instantaneously and produce computer code in seconds. Yet it can fail at elementary tasks.
This suggests that artificial intelligence may not climb Urban’s staircase one conventional step at a time.
It may construct an entirely different staircase.
And eventually those staircases may intersect.
Something Else Has Changed: AI Is Beginning to Act
For most of the computer age, computers were tools. A human decided what needed to happen and operated the tool.
Generative AI initially appeared to preserve this relationship. We asked a question; the machine produced an answer.
But AI is increasingly moving from answering to doing.
Modern AI agents can be given a goal, formulate intermediate steps, use software, search information, write and execute code, inspect the results, revise their approach and continue working.
This is still imperfect. Human supervision remains important. But conceptually it represents a major change.
Intelligence becomes much more consequential when it can take action. A brilliant thinker locked in a room can provide advice. Give that thinker a computer, communications systems, tools, memory and authority to act, and intelligence becomes agency.
That is another step toward the world Urban was asking us to imagine.
Science May Be Where We First See the Staircase Clearly
Perhaps the most consequential development is happening in science.
Scientific progress has historically been constrained by human cognitive bandwidth. There are millions of scientific papers. No researcher can read them all. Disciplines become increasingly specialized. A discovery in molecular biology might have implications for materials science that neither community recognizes. Humans can formulate hypotheses, but we can investigate only a tiny fraction of the possible hypotheses.
AI changes the economics of thinking.
A machine can potentially examine enormous amounts of literature, identify patterns across disciplines, propose hypotheses, run simulations, write analytical software and help design experiments.
We have not created an artificial scientist that renders human researchers obsolete. But we may have created its ancestor.
What Happens When the Machine Sees Something We Do Not?
For the moment, when AI helps solve a scientific problem, humans generally expect to understand the answer. The AI proposes something. Humans examine it. Humans verify it. Humans decide whether it makes sense.
But suppose AI capabilities continue improving.
Eventually we may encounter a peculiar situation. An AI produces a solution. We test the solution. It works. We ask why. The AI provides an explanation. And we cannot fully understand it.
Not because the explanation is badly written, but because understanding it requires relationships between concepts that exceed what a human brain can comfortably represent.
This would be an extraordinary moment in intellectual history.
For thousands of years, humanity has effectively operated according to the principle: if something can be known, humans can eventually know it.
We may instead discover: something can be knowable without being humanly comprehensible.
Intelligence May Become a Telescope for Thought
There is another, more optimistic way of looking at this.
Humans cannot see infrared light, so we built instruments that can. We cannot see distant galaxies clearly, so we built telescopes. We cannot perceive individual atoms, so we built microscopes. We cannot naturally detect gravitational waves, so we built instruments capable of detecting distortions smaller than anything our senses could perceive.
Human civilization advances partly by constructing technologies that extend our biological limitations.
AI could become something similar: a telescope for intelligence.
Instead of allowing us to see farther than our eyes permit, it could allow civilization to think farther than the unaided human brain permits.
That may ultimately prove more significant than replacing jobs, writing emails or generating software. We could use artificial intelligence to explore conceptual territory humans could never reach alone.
The critical difference from a telescope, however, is that the telescope does not decide where to point itself. An advanced AI might.
There Is Another Form of Superintelligence We Often Ignore
Urban’s staircase generally compares one intelligence with another. But modern AI introduces another possibility: collective intelligence.
No individual human understands modern civilization. No single person knows how to build a semiconductor fabrication plant, design a modern aircraft, manufacture an MRI machine, operate the international banking system, construct a nuclear reactor, understand every branch of medicine and maintain the internet.
Civilization works because knowledge is distributed among billions of people and institutions.
AI can increasingly connect those islands of knowledge.
Imagine an intelligence capable of simultaneously drawing upon the expertise represented by thousands of physicists, physicians and software engineers; every published chemistry paper; every engineering manual; every clinical trial; vast economic datasets; and much of the written history of humanity.
It does not need to become a magical omniscient mind for the effect to be extraordinary. Simply connecting human knowledge more effectively than humans can connect it ourselves could produce something functionally superhuman in important domains.
The Question Is No Longer Whether AI Can Beat Humans
For decades, we measured artificial intelligence by asking whether it could beat us. Can it beat the chess champion? Recognize the photograph? Pass the exam? Write the program? Diagnose the disease? Solve the mathematics problem?
Those are understandable benchmarks.
But the more important question is: what happens when AI can solve problems that humans cannot solve?
And beyond that: what happens when AI can formulate questions humans never thought to ask?
The most profound intelligence changes the framework through which the problem itself is understood. Newton did not merely solve equations; he conceptualized gravity in a new way. Einstein did not simply calculate more quickly than his contemporaries; he reconceptualized space and time. Darwin did not merely accumulate biological observations; he recognized the organizing principle of natural selection.
If machines eventually acquire that capability at a level beyond humans, they may not merely provide better answers to our questions. They may discover that we have been asking the wrong questions.
And That Creates a New Human Problem
Suppose a future AI tells us: “I have discovered a new approach to economics that increases global prosperity dramatically.”
We ask how it works. It gives us a 5,000-page explanation involving relationships among economics, psychology, network theory, game theory and mathematics. Thousands of experts study it. They conclude that portions appear correct. Nobody understands the whole thing. Simulations show that it works.
Do we implement it?
Now substitute a cancer treatment, a new energy system, a financial-market architecture, a climate intervention, a military strategy, or a technology capable of modifying human biology.
At that point the central problem is no longer intelligence. It is trust.
How does a less intelligent species responsibly supervise a more intelligent system?
That may ultimately be one of the hardest governance problems humanity has ever faced.
But We Should Be Careful Not to Declare Victory Too Early
There is an important danger in applying Urban’s argument to 2026. We could become so impressed by AI’s progress that we prematurely declare that superintelligence has arrived.
It has not.
Today’s systems remain unreliable. They hallucinate information. They make reasoning mistakes. They can be brittle. They sometimes require enormous computational resources to accomplish things humans do effortlessly. They can perform spectacularly on one benchmark and fail badly on another.
The staircase is therefore not a claim that today’s AI stands above humanity. It is a framework for understanding what could happen if the trajectory continues.
And the trajectory deserves our attention.
The Most Important Change Since Urban Wrote His Article
There is a fascinating difference between reading Urban in 2015 and reading him now.
In 2015 the argument required imagination. The reader had to accept several hypothetical propositions: imagine computers that understand language; imagine computers that can reason; imagine computers that can create; imagine computers that can write software; imagine computers that understand images; imagine computers that can use tools; imagine computers that can perform intellectual work.
Today we no longer have to imagine those things.
We can argue about how well AI performs them. We can argue about whether machines truly “understand.” We can debate whether AGI has arrived or what the term should even mean.
But the capabilities themselves exist.
That moves Urban’s thought experiment out of the realm of distant speculation.
We are conducting the experiment.
2015 to 2026 Is Only Eleven Years
This may be the most important perspective of all.
Urban published his essay in January 2015. Only eleven years have passed.
Consider how small eleven years is historically. A child born when Urban wrote the article is barely entering adolescence.
Yet during that interval we moved from AI systems that most people encountered indirectly to machines with which hundreds of millions of people can converse naturally and which increasingly participate directly in professional, scientific and creative work.
This is no longer an obscure computer-science project. It is becoming infrastructure. And the underlying systems continue improving.
Perhaps We Are Looking at the Staircase Incorrectly
There is another possibility.
Perhaps humans do not need to compete with the machine on the staircase at all.
Human civilization’s greatest advantage has never been individual intelligence alone. It has been our ability to combine intelligence.
Language allowed one brain to transfer knowledge to another. Writing allowed knowledge to survive its creator. Printing allowed knowledge to spread. Libraries accumulated it. Universities organized it. Computers processed it. The internet connected it.
Artificial intelligence may be the next stage.
Instead of Human versus AI, the more useful model may become Human + AI.
The important unit of intelligence may therefore cease to be the individual person. It may become the human-machine system.
That possibility dramatically changes Urban’s staircase. We may not watch another intelligence climb past us. We may climb with it.
But That Requires a Different Human Skill
If machines become better at producing answers, human value increasingly shifts toward something else: choosing the questions.
Judgment becomes more important. Curiosity becomes more important. Values become more important. Understanding people becomes more important. Determining objectives becomes more important. Knowing what should happen becomes more important than knowing how to calculate what can happen.
An AI may eventually be able to design ten thousand extraordinarily effective strategies.
Someone still has to decide: effective at accomplishing what?
That is not merely a computational question. It is a human one.
The Most Dangerous Mistake May Be Anthropomorphism
We also need to resist imagining that a superior intelligence would simply be a very smart human.
A chimpanzee looking at us might make the same mistake. If it could imagine a more intelligent chimp, perhaps it would imagine one that climbs trees better, remembers more fruit locations and dominates competing groups.
It could never extrapolate from chimp intelligence to Shakespeare, calculus, constitutional democracy, particle accelerators and spacecraft. Those things are not merely more chimpanzee intelligence. They emerge from a qualitatively different level of cognition.
Likewise, when we imagine superintelligence, we naturally picture something like Einstein, but smarter.
That may be completely wrong.
An intelligence substantially above ours might develop conceptual structures we do not possess words for.
Imagine the Ant Again
The ant walks across a computer.
Inside that computer are billions of transistors performing operations billions of times each second. The computer may contain photographs of galaxies, medical records, symphonies, mathematical proofs, love letters, maps of the Earth, computer simulations and the collected works of Shakespeare.
The ant encounters all of it as a warm surface.
Everything is physically present. Almost nothing is intellectually accessible.
Now imagine that humanity is the ant.
Not because humans are stupid. Humans are astonishing. We decoded DNA. We split the atom. We landed on the Moon. We detected gravitational waves. We discovered galaxies billions of light-years away. We developed mathematics capable of describing phenomena completely invisible to our senses.
But none of those accomplishments demonstrates that our intelligence is unlimited. They demonstrate only how far this particular kind of primate intelligence has managed to travel.
There may still be an enormous staircase above us.
The Great Question of the 21st Century
Tim Urban’s 2015 article was ostensibly about artificial intelligence. But underneath it lies a much bigger question:
Is human intelligence the summit of intelligence—or merely one stage in its evolution?
For almost all of human history, that question was philosophical. Now it is becoming technological.
We are building systems whose capabilities are improving extraordinarily quickly. They are already superhuman in selected areas and deeply flawed in others. They increasingly reason, create, program, analyze and act.
Nobody can responsibly say exactly where this leads. Perhaps progress slows. Perhaps fundamental limitations emerge. Perhaps today’s architectures prove incapable of producing genuine general intelligence. Perhaps human intelligence remains uniquely capable in ways we do not yet appreciate.
All are possible.
But there is another possibility we can no longer dismiss.
We may be witnessing the beginning of a transition in which human beings cease to be the only source of advanced intelligence on Earth.
And if that happens, the most consequential event may not be the day a computer passes some official test for AGI. It may be the first time a machine discovers something important that humanity could never have discovered on its own.
At that moment, we will have empirical evidence that the staircase continues upward.
One Final Thought
There is a wonderful irony in Urban’s analogy.
The chimpanzee cannot build the skyscraper. But humans can build one for the chimpanzee.
An ant cannot understand a climate-controlled habitat. But humans can create one in which the ant colony thrives.
Inferior intelligence does not automatically imply irrelevance. It creates dependence on the objectives of the more capable intelligence.
That may ultimately be why the development of AI deserves so much attention.
The critical question is not simply: How intelligent can we make it?
It is: What will that intelligence be trying to accomplish?
And immediately behind that comes another question: Can humans remain capable of determining those objectives even after we are no longer capable of understanding everything the system can do?
Tim Urban’s staircase seemed almost absurdly speculative in 2015.
In 2026, we should look at it again.
The ant is still an ant. The chimpanzee is still looking at the skyscraper. Humanity still occupies its familiar step.
But for the first time in the history of our species, something unusual is happening.
We are building the next step ourselves.
Reference
Urban, Tim. “The AI Revolution: The Road to Superintelligence.” Wait But Why, 2015.
Comments