The Law That Is Changing the Education of Humanity

The math of the solar industry is not an anomaly. It is a template.

In 1977, the cost of solar power was approximately six dollars per watt. Today, that cost has plummeted to well below twenty cents per watt. This collapse did not happen through random chance or minor incrementalism. It happened because of Swanson’s Law: for every doubling of cumulative solar panel production, the cost of solar energy drops by roughly twenty percent. A predictable, compounding decay of cost driven by scale and technological refinement.

Do not mistake this for a story about renewable energy. We are currently watching a nearly identical curve emerge in artificial intelligence. Track the cost per million tokens in large language models over the last three years. The trajectory mirrors the solar curve almost exactly. As compute scales and architectures improve, the cost of generating highly sophisticated, human-level reasoning is approaching zero.

This is the part where most university administrators get excited about cutting adjunct positions.

They are making a catastrophic error. They are falling victim to the Jevons Paradox.

The Coal Engine That Consumed More Coal

In 1865, the economist William Stanley Jevons observed something that upended the conventional logic of his era. The industrial revolution had produced dramatically more efficient steam engines. Everyone assumed these efficient engines would consume less coal. Instead, the opposite occurred.

More efficient engines made coal-powered production cheaper. Cheaper production made it profitable to run more machines in more places. Total coal consumption skyrocketed. The efficiency gain did not lead to conservation. It fueled massive expansion.

This is the Jevons Paradox: when the efficiency of a resource increases, total consumption of that resource rises rather than falls. Lower cost does not reduce demand. It creates more of it.

The Scarcity We Have Been Managing

Currently, the cost of delivering high-quality, personalized instruction is high. Because a skilled human tutor is expensive, we limit instruction to a narrow set of subjects and a fixed number of students. We use classrooms to manage the scarcity of human attention. We use curricula to determine what is worth learning. The high cost of delivery acts as a ceiling on how much education can actually occur.

As AI drives the cost of instruction toward zero, that ceiling disappears.

We will not see a world where students use AI to do less work. We will see a world where students demand an infinite expansion of curriculum. When a personalized, infinitely patient tutor costs practically nothing, the student does not stop at the syllabus. They demand mastery of quantum mechanics, classical literature, organic chemistry, and Mandarin Chinese, all delivered through a feedback loop calibrated to their specific gaps. The demand for education will not contract. It will explode.

This is the Jevons Paradox applied to learning.

The Strategic Error

The institutions that are currently trying to use AI as a cost-cutting tool are optimizing for a shrinking market. If you replace an adjunct professor with a chatbot to balance a structural deficit, you are essentially using a solar boom to power a candle factory. You are cutting your way into irrelevance.

The real opportunity is in expansion of the frontier. The institutions that survive will be the ones that use the collapsing cost of instruction to increase the depth and breadth of what they offer. They will redirect the surplus created by AI efficiency into higher-order learning: critical thinking, ethical application, synthesis across disciplines, judgment under genuine uncertainty. The things that are hard to automate because they require a human in the room who has made real decisions with real consequences.

The instructor does not disappear. The instructor shifts from deliverer of information to curator of cognitive complexity. The classroom moves from transmission of facts to validation of mastery and management of nuance. We do not need humans to lecture on the basics of biology. We need humans to design the learning architectures that prevent a student from drowning in an ocean of infinite, low-cost information.

The Harder Question

There is a deeper issue that no amount of strategic repositioning fully resolves.

For centuries, the university has derived its prestige and its power from the management of scarcity. It held the keys to the library. It controlled access to the professor. It acted as the gatekeeper of the credential. The value of a degree was tied directly to the difficulty of accessing the knowledge required to earn it.

The Swanson curve is destroying that scarcity. The Jevons Paradox is making demand for that knowledge infinite.

We are approaching a point where knowledge is effectively free and infinitely accessible. If the scarcity of information is gone, what is the purpose of the institution that once guarded it? If anyone can achieve mastery through a zero-cost, personalized AI tutor, the traditional university model of information delivery becomes a relic.

The role of the university must be redefined. It can no longer be a warehouse of knowledge. The question is not how we preserve the old model using new tools. The question is what remains of the university when the very thing it was built to provide is no longer a scarce resource.

That question does not have a comfortable answer. But it is the only one worth asking right now.