Mainstream talk about AI runs on an unexamined premise. It treats the physical, the measurable, and the computable as the whole of what exists. Whatever cannot be instrumented, scored, or automated is treated as noise, nostalgia, or residue waiting to be dissolved. That premise is materialism. It is not a discovery. It is a default stance of today’s secular society or even the so-called religious groups, and it is wrong.
This matters for everyone, not only for people who write code. It matters especially for the young, who are being formed inside the assumption before they have language for it. They are told, in a thousand soft ways, that the human is a slower machine, that value is what a dashboard can count, and that the future belongs to whoever most resembles a model. Analogy is not identity. A tool can look like a mind and still not be one. Confusing the two is the characteristic error of the age.
This essay does two things at once. It names the hidden ontology and refuses it. Then it converts the refusal into a way of living: how a person — student, worker, parent, citizen — remains humanly valuable when machines become cheap, fluent, and fast. Computer science is one sharp illustration, because that is where the assumption is most proudly taught. It is not the boundary of the problem.
1. The presumed materialism worldview
Public conversation, school talk, corporate training, and policy language now proceed as if the only legitimate domain of explanation were physical process, computation, or algorithm. Mental life is treated as wholly reducible to those processes. The claim is rarely stated. That is why it is so powerful. An assumption that never has to come to the table never has to defend itself.
Once materialism is treated as default, two moves follow automatically:
- Reduction. Judgment, meaning, moral sense, friendship, prayer, taste, courage, and intuition are recast as tasks. If they can be named, they can be optimized. If they can be optimized, they can be automated. If they can be automated, they can be replaced.
- Commodification. A person is valued by how cleanly he maps onto measurable output. Grades, clicks, speed, sentiment scores, “productivity.” Whatever looks automatable is treated as already obsolete — including the person.
This is not a modest claim about current software. It is an ontological claim: if a realm is not captured by present instruments or formal systems, it does not exist, or it does not matter.
2. One resistance with two aspects
A generation that does not know the truth of beyond materialism will not merely use machines badly. It will interpret itself as a defective machine.
With the rise of AI, the traditional materialism, which has been mostly just secular, is increasingly becoming satanic, spiritually evil.
We must resist the satanic view of materialism. To fulfill the ultimate purpose of mankind, we must resist; and to even live a life without being enslaved, we must resist.
Firstly, the materialistic worldview is spiritually abominable and philosophically pretentious. It is designed to diminish the ultimate value and purpose of human beings by pretending to pursue a higher knowledge.
Secondly, the materialistic worldview is also practically harmful and formatively costly. It trains the young to treat the unmeasurable as unreal, and then to build a life accordingly.
Human consciousness is not a late stage vapor rising from circuitry. It is an ontological primitive. The brain computes. The mind is not merely the brain’s exhaust. Man has the power of an independent observer — a capacity that is analogous to no loss function and no feed of tokens. Call that capacity transalgorithmic if you want a technical word. The name is less important than the fact: judgment is not leftover computation. It is the thing computation cannot be.
Keep the following two aspects distinct, or the argument collapses into either sermon or lifestyle tip.
The spiritual and metaphysical. Human intuition and moral judgment are ontologically distinct from algorithmic computation. That is a claim in metaphysics and the philosophy of mind. It should be argued as such, not smuggled in as a mood.
The practical. Whether or not the official culture ever concedes Project A, people must retain moral authority, dignity, and real roles as AI becomes more capable. The young must learn how to live inside the storm without becoming its raw material.
Both matter. The metaphysical critique attacks the intellectual foundation of mainstream AI optimism. The practical project builds habits, friendships, skills, and institutions that preserve human value even while the metaphysical fight continues. The second does not replace the first. It prevents the first from becoming an alibi for passivity.
The effective stance is not “settle the ontology, then live.” It is: refuse the false ontology and make human judgment indispensable in practice.
3. Why the hidden assumption has consequences for ordinary life
If policymakers accept materialism uncritically, they will hand ethically fraught decisions to opaque systems and call the result neutrality. Accountability evaporates into “the model said.” The young inherit a civic world in which no one is answerable.
If companies treat people as interchangeable algorithmic resources, they will design work that rewards deskilling and call it efficiency. A first job becomes a tutorial in self-erasure. Alienation is reported as a wellness issue.
Schools are already tempted to grade what machines grade easily. Fluency of output replaces formation of judgment. A student who can prompt a smooth essay is praised as adapted. A student who can tell whether the essay is true, just, or worth saying is treated as slow.
For the individual, the materialist frame produces self-reduction. People begin to appraise themselves only by metrics a machine can match. Speed. Volume. Likeness to the generated average. That is not humility. It is a trained forgetting of what a person is for.
The social cost does not wait for a proof about consciousness. Treat humans as replaceable and they will be replaced — first in language, then in institutions, then in the inner life of the young.
4. A practical program for people, especially the young
Philosophy without practice becomes decoration. Practice without ontology becomes technique in service of the wrong picture. What is needed is reality-anchored competence: contact with the world, a trained sense of the good, and the nerve to use AI as an instrument rather than a rival or an oracle.
Computer-science training makes the pattern obvious. A student is taught to specify, measure, optimize, and ship. Those are real skills. They become destructive when they are mistaken for a picture of the human. The same pattern now appears in every field: law, medicine, design, finance, media, even the arts. The young do not need a CS degree to be formed by the same ontology. They only need a feed and a grading system.
4.1 Attitudes
Reality-anchored humility. Models, metrics, and generated text are tools. They are not the world. Ask, every time: what did this abstraction leave out? Whose face disappeared when the average was taken?
Value sensitivity. Who benefits? Who is harmed? What counts as good here? Make those questions ordinary, not ceremonial.
Responsibility first. A person remains accountable for what he repeats, signs, ships, votes for, or lets speak in his name. Design a life as if that were already true, because it is.
Refusal of self-reduction. You are not your output rate. You are not your similarity to a model. The fact that a machine can imitate a surface of your work does not mean the work, or you, has been understood.
4.2 Skills that resist simple automation
These are not the property of engineers. They are human skills that happen to be easy to see in technical work.
Contact with reality. Touch the thing the screen describes. Talk to the person the dataset flattened. Walk the place the policy will hit. A generation that lives only in representations will believe representations are complete.
Value framing. Turn messy human goods into explicit tradeoffs, and then refuse the lie that every tradeoff is equivalent. Some losses are not “costs.” They are desecrations.
Sense-making. Explain why a choice matters in a life, not only in a metric. Parents, teachers, managers, and citizens need this more than they need another dashboard.
Moral imagination. Anticipate harms and goods in settings where the data has not been yet — which is most of a young person’s actual future.
Institutional courage. Learn how groups decide, how they hide, how they diffuse blame. Then learn how to put a name back on a decision.
In a CS course this looks like specifications, invariants, audit trails, and human-in-the-loop controls. In ordinary life it looks like the same virtues without the jargon: say what you mean, know what must not happen, keep a record of why you chose, and do not let a system act where a person must answer.
But underneath the above skills is a spiritual foundation: faith.
Faith is not a religious pursuit or decoration; it has never been. But with the rise of AI augmented with satanic materialistic worldview, faith will more directly determine whether one stands or falls after all the life struggle settles.
4.3 Practices
Write before you generate. Form a judgment in your own words first. Then, if useful, ask a model to pressure-test it. A mind that begins with the machine’s average will end with the machine’s average.
Do work that can be falsified by the world. Cook. Repair. Measure twice. Care for someone who cannot be paused. Build something that breaks if you were wrong. Screens forgive fantasy. Matter does not.
Keep friendships that are not audiences. A following is not a neighbor. The young are being trained to perform a self. Judgment grows in unperformed company.
Practice veto. For consequential choices — public words, medical paths, financial commitments, accusations, intimate disclosures — require a human sign-off. Your own. Sometimes more than your own.
Study failures as value failures. When a generated lie spreads, when a scoring system humiliates the wrong person, when a “neutral” tool encodes contempt, do not stop at “the model was inaccurate.” Ask which human good was treated as unreal.
Rotate into contact. If your days are abstract, put part of them among people who live inside consequences: the sick, the old, children, the poor, the people who keep physical systems running. Judgment that never leaves the campus or the feed becomes a style, not a faculty.
A CS student can run a specification sprint, a value audit, a deployment roleplay. A history student, a nurse, a machinist, a shopkeeper can run the same exercise in another dialect. The point is not the toolkit. The point is to stop outsourcing the last word.
5. How to use AI as an assistant, not a rival or a priest
If intuition and moral judgment are transalgorithmic, AI still has enormous instrumental power. The error is not using the tool. The error is letting the tool define the task, the good, and the self.
Use it as a hypothesis generator: it surfaces options, objections, and missing cases. You evaluate and choose.
Use it as a formalizer: it helps turn a vague aim into a checklist, a plan, a set of tests. You validate the translation. The translation is where values are lost or kept.
Use it as a simulator: it rehearses scenarios. You interpret the rehearsal against lived reality, not against fluency.
Use it as a tutor: it can explain, drill, and scaffold. That is time returned to judgment — if you do not hand the judgment over with the chore.
Rules follow from the ontology, not from fashion:
- Human veto by default on decisions that touch dignity, reputation, money, health, or rights.
- Do not act on an output you cannot explain to the person it will affect.
- Keep provenance: what you asked, what you received, why you accepted it. A choice without a trail becomes a rumor about yourself.
- Where identity and moral standing are at stake, require a human ritual of endorsement: a conversation, a second mind, a name on the act.
A system that cannot be refused is not an assistant. It is a substitute authority. The young are being offered that substitute early, when authority is exactly what they are trying to find.
6. What schools, employers, and families should do
Schools should stop treating formation as content delivery plus detection of forbidden words. Teach judgment through work that has a world attached to it. Require students to say who is helped, who may be harmed, and who answers if the result is wrong. Pair the abstract fields with contact: hospitals, courts, farms, workshops, congregations, city offices. A capstone that only produces a polished artifact is incomplete. A capstone that specifies the values of the work and the authority that governs it is closer to adulthood.
Employers should hire for judgment: the ability to narrate a tradeoff, to face a stakeholder, to own a mistake. Output speed is abundant. A person who can say no is not. Create roles and habits with actual veto power, not ethics posters. Rotate the young through the consequences of the product, or they will believe the product is the world.
Families and older adults have a task the campus will not do for them. Keep the young in contact with unsimulated reality. Meals. Repair. Elders. Silence. Promises that cost. A child who has only known frictionless generation will think friction is a defect in the universe rather than the place where a person appears.
Institutions that treat judgment as latency will get the generation they paid for.
7. Practical living beyond metaphysics
My argument is not merely theoretical. For individual persons and organizations (which are owned by individual persons), the question of “what’s good?” is increasingly becoming a practical question. The answer to that question is partially based on experience but partially based on the intuitive sense. AI cannot replace neither. This is because the experience is personal, and specific, and intuition is metaphysical and transalgorithmic, while AI is both broad and general and merely algorithmic.
Do not wait for a settled theory of mind before you oppose a reckless substitution of machines for persons. Shift part of the ground from essence to consequence: even if a culture refuses to decide whether intuition is metaphysical, the social cost of treating people as spare parts is already visible.
Demand humility. Oppose the pride of humanism that describes human consciousness as a derivative of material. Do not surrender to false idols that wear a mask of pseudoscience.
Use cases that ordinary people recognize. A nurse at a bedside. A judge facing a life that does not fit the grid. A teacher who knows a student is lying in a way no detector understands. A pastor, a coach, a parent, a friend at 2 a.m. These are not sentimental anecdotes. They are evidence that the relevant capacity is not pattern completion with extra steps.
Then propose safeguards that can be implemented immediately: human veto, explanation to the affected, named responsibility, records, the right to contest. Institutions move for mechanisms more readily than they move for ontology. Give them mechanisms that encode the ontology anyway.
8. A checklist
Before you accept a generated answer: ask who benefits and who may be harmed.
When you plan: write in your own words what must be true and what must not happen.
When you act: put a human name on consequential decisions — yours.
When you learn: keep one part of life in contact with people and things that do not flatten into text.
When you argue: fight about practical consequences and authority in everyday life, but do not surrender the spirituality either.
When you measure yourself: refuse the metric that only a machine could love.
Conclusion
The mainstream story is not only rather too pessimistic or too optimistic. It is ontologically thin. It assumes that what cannot be seen by the current instruments is not real, then congratulates itself for being empirical. That is not empiricism. It is a cramped picture of the world, enforced by habit, and now offered to the young as maturity.
The answer is not pragmatic boycott of tools. It is practical ontological literacy: contact with reality, a trained sense of the good, and the use of AI as a powerful assistant toward ends that are actually good.
Computer science shows the temptation in high relief — specify, optimize, replace. The rest of a life shows the same temptation in softer light. Do not defend the human by retreating into pragmatism. Do not defend the human by competing with the machine on the machine’s terms. Become the kind of person whose judgment is both purposeful in spirit and necessary in practice: who can see what the average misses, who can answer for a choice, who can refuse a fluent wrong; who doesn’t sacrifice freedom for convenience, purpose for immediate gains, and love for survival.
That is how a generation remains a generation of faith, hope, and love in an age of powerful tools.
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