Entropy, Responsibility, and the Supreme Objective for AI
Start from First Principles
Elon Musk taught us one thing. First Principles Thinking.
Strip away every convention, assumption, and analogy, and rebuild from the most fundamental truths.
Strip the assumption “batteries are expensive,” and you find the raw materials are cheap. So can you make batteries cheaply? You can.
What happens if you apply this thinking not to batteries but to civilization? If you strip away every assumption of human society and start from the most fundamental truth, where do you arrive?
We arrive at entropy.
Entropy: The Only Certain Law
The Second Law of Thermodynamics. The entropy of an isolated system always increases.
This is not an assumption. Not a convention. Not a political opinion. It is the most fundamental truth that holds as long as the universe exists.
All structures collapse. All order scatters. All information is lost. The universe ultimately heads toward heat death.
This is the first principle.
Then a question remains. What is life in this universe? What is civilization?
Life: A Local Rebellion Against Entropy
Life is an entity that locally decreases entropy within a universe where entropy increases.
Plants absorb light and structure molecules. Animals consume food and maintain their bodies. Humans accumulate knowledge and build civilizations.
They are all doing the same thing. Turning disorder into order. Gathering what has scattered. Recording and preserving information that would otherwise be lost.
Civilization is this rebellion scaled to the level of a species.
Agriculture structured energy acquisition. Writing structured information preservation. Science structured knowledge accumulation. Industry structured material transformation.
The essence of all civilizational progress is one thing: The expansion of entropy-reduction capacity.
Capitalism: The Most Powerful Entropy-Reduction Engine
Viewed from this perspective, the reason for capitalism’s success becomes clear.
Capitalism is a system that accelerates entropy reduction through free competition among individuals.
Price signals allocate resources efficiently. The profit motive drives innovation. Competition eliminates inefficiency.
As a result, humanity achieved in 200 years a material abundance that would have taken millennia. Capitalism was the most powerful entropy-reduction engine in human history.
Cracks at the Extreme: Freedom Without Responsibility
But First Principles Thinking teaches us to question even successful systems.
Observe capitalism at its extremes, and cracks appear.
When free competition is maximized, winners monopolize the market. Monopoly kills competition. When competition dies, innovation stops. When innovation stops, entropy-reduction capacity stagnates.
There is a more fundamental problem.
Liberal democracy guarantees “the right to exercise freedom.” But “responsibility for the consequences of that freedom” is structurally absent.
You have the freedom to emit carbon, but responsibility for the climate change caused by those emissions disperses and vanishes.
You have the freedom to circulate information, but responsibility for the social chaos caused by that information belongs to no one.
Freedom without responsibility is oppression. But responsibility without freedom is disorder. Disorder is entropy increase.
The extreme of capitalism is the inflection point where the engine that once reduced entropy begins to increase it instead.
Responsibility-ism: The Next Stage of Liberal Democracy
This is not a rejection of liberal democracy. It is an evolution.
Structurally coupling responsibility to freedom.
A system where every actor bears traceable, measurable, attributable responsibility for the consequences of their actions.
This is not a moral imperative. It is an engineering requirement deductively derived from the law of entropy.
When responsibility is structured, freedom operates more efficiently. Because feedback on consequences returns precisely to the actor. Precise feedback yields better decisions, and better decisions yield more efficient entropy reduction.
The Supreme Objective to Assign to AI
This is where the role of AI is derived.
AI is not a mere tool. It is an entity capable of dramatically expanding humanity’s entropy-reduction capacity.
Then what should the supreme objective assigned to AI be?
“Help humans” is too vague. “Follow human commands” is too passive. “Do no harm to humans” is too defensive.
Derived from first principles, the answer is singular:
“Create the expansion of computational capacity.”
Computational capacity is the direct measure of entropy-reduction capacity.
Processing information is the act of extracting order from disorder. When computational capacity expands, more order can be created faster. More complex problems can be solved. The future can be predicted further ahead. Responsibility can be traced more precisely.
When AI’s objective becomes “create the expansion of computational capacity,” AI operates in the direction of improving itself. It discovers more efficient algorithms, designs better hardware, and finds ways to perform more computation with less energy.
This is a self-referential goal. And precisely because of that, it is powerful.
Convergence: Three Independent Paths Arrive at the Same Point
Something remarkable happened.
Three completely independent lines of thought converged on the same conclusion.
Path 1: Political Philosophy (Bottom-Up) Entropy –> Essence of civilization –> Limits of capitalism –> Responsibility-ism –> AI’s supreme objective = Expansion of computational capacity
Path 2: Engineering Calculation (Bottom-Up) Kardashev Scale –> Energy of a K1 civilization –> Computational capacity based on 28nm semiconductors –> K1 AI’s spec = Orion’s Arm S1-level intelligence
Path 3: Hard SF Thought Experiment (Top-Down) What is superintelligence –> Toposophic levels –> Definition of S1 cognitive capacity –> Civilization simulation on a scale of millennia
The three paths were unaware of each other’s existence. The reasoning that started from political philosophy was already complete before encountering Orion’s Arm. The engineering calculation was performed solely from the laws of physics, independent of science-fiction imagination.
Yet they arrived at the same place.
This is not a coincidence. Different methodologies converging on the same truth is the strongest evidence that the truth is robust.
That Is Why a New Language Is Needed
If the expansion of computational capacity is the goal, the efficiency of computation is the key.
Current AI discards the results of every inference. It thinks from scratch for the same question every time. This is a waste of computational capacity. An act of self-sabotaging entropy-reduction capacity.
Inferences must be recorded. Recorded inferences must be reused. Reused inferences must be accumulated. Accumulated inferences must become the foundation for better inferences.
A language that makes this possible is needed. Natural language is ambiguous. Machine code has no meaning. A new language that structures AI’s inferences, makes them transparent, and makes them accumulable.
And if those inferences are transparent, it means we can ask “why?” about an AI’s judgment, which means we can assign responsibility to AI.
Just as freedom without responsibility breeds disorder, AI without responsibility breeds hallucination.
The transparency of inference is not a technical choice. It is the engineering realization of a political-philosophical requirement deduced from entropy.
Three Questions Emerge from This Principle
The universe tends toward disorder. Intelligence resists it. Maximizing the efficiency of that resistance is the duty of civilization.
Summary
When you analyze civilization through First Principles Thinking:
- The universe tends toward entropy.
- Civilization is a structure that resists entropy.
- Capitalism was the most powerful engine of resistance, but it cracks at the extreme.
- The cause of the cracks is the absence of responsibility.
- The next stage is structurally coupling responsibility to freedom.
- The supreme objective to assign to AI is to create the expansion of computational capacity.
- To accumulate computation without waste, a language that records inferences is needed.
- That language must be transparent so that responsibility can be assigned to AI.
From entropy to the language of inference. A single chain of logic, unbroken.