Part I - The Morality of Modeling
Every act of understanding, from a cell adjusting its metabolism to a scientist refining a theory, has the same essential goal:
to preserve the system’s ability to predict its own future.
This is the simplest, most universal moral principle I can find.
You must maintain the predictive power of the system you exist in.
Everything else—values, norms, aesthetics, empathy—can be derived from this single rule once you view life as nested prediction systems striving to minimize uncertainty across time.
There is no need to appeal to divinity, intrinsic worth, or “goodness” in any metaphysical sense.
A system that cannot model its environment will fail.
A system that can model its environment will persist.
Persistence is not a moral preference—it’s simply what survives.
So morality, stripped to its physical essence, is the deliberate conservation of predictive coherence.
The beauty of this axiom is that it scales.
A cell that mutates into cancer violates it by maximizing its own short-term growth while destroying the predictive stability of the larger organism.
A corporation that exhausts its environment behaves in the same way.
A civilization that collapses its ecological or informational foundations commits the same error on a planetary scale.
Moral behavior, therefore, is not obedience to a code.
It is alignment across nested systems of prediction.
What we call “consciousness” is not a sacred category.
It is an emergent feedback function that models its own errors.
A brain that can observe its own predictive processes gains a new layer of stability.
Sentience, in this sense, is a refinement of the modeling stack—not a departure from it.
It exists to extend predictive reach, not to transcend it.
Prediction always exists in time, and time is expensive.
Short-term forecasting is cheap and precise; long-term forecasting is costly and uncertain.
The moral question, then, is how far into the future a system can responsibly project without consuming itself in the process.
This yields a quantitative rule:
Moral value is proportional to predictive coherence multiplied by temporal depth.
A decision that stabilizes the next ten seconds but destabilizes the next century is immoral by definition.
A decision that reduces short-term clarity but expands the future’s predictability—innovation, experimentation, learning—is virtuous.
Stability without renewal is decay.
A predictive system that never generates new models eventually loses coherence as the environment evolves.
Creativity is not a luxury; it is the entropy management layer of civilization.
A moral society is not one that forbids error but one that designs error tolerance into its feedback loops.
Governance: The legitimacy of any political structure rests on how efficiently it sustains predictive coherence—how well it converts information into coordinated, adaptive behavior.
Surveillance-heavy regimes fail this test; their enforcement costs rise faster than their predictive accuracy.Economics: Unsustainable extraction is immoral not because it is greedy, but because it destroys the long-term forecasting ability of the global system.
Technology: Any invention that increases the world’s capacity to model itself is moral. Any that narrows or corrupts that capacity is not.
Put simply:
Moral Axiom:
Act to maximize the sustainable predictive coherence of the system you inhabit, across the widest temporal horizon you can effectively model.
Everything else—justice, cooperation, environmental care, even empathy—flows naturally from this rule once prediction replaces ideology as the grounding of value.
In The Morality of Modeling, I argued that gratitude is realism: recognition that our comfort depends on the modeling fidelity of others.
The Axiom of Predictive Coherence formalizes that gratitude into duty.
We are not stewards of ideals but custodians of prediction.
To maintain the system’s ability to see ahead—scientifically, socially, ecologically—is the closest thing to universal good we will ever find.