Mainstream talks about AI run on an unexamined premise. They treat 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 much of the so-called religious society, 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.
But analogy is not identity. Semblance is not essence. And mimicking is different from being. A machine can feel like a mind or look like a person but still be just a machine. 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. AI is one sharp illustration, because that is where the assumption is most proudly taught. But it is not the boundary of the problem.
I am not against AI in terms of its functionality as a tool. I am against the popular perception of AI; I am against the AI propaganda and the mainstream reception of it. In case you think I am just a Luddite, and that I should be “open-minded” about technology, my whole career has been built on technology, being a patent attorney and tech-business consultant a part of that. On AI more specifically, I speak as someone who has consumed over 10 billion tokens in coding alone when a vast majority of people today haven’t consumed more than 10 million tokens mostly just doing AI chatting.
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. Human 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 merely an empirical claim. It is a false ontological claim: if a realm is not captured by present instruments or formal systems, it does not exist, or it does not matter; and if two existences are empirically equivalent, they are ontologically equivalent. And this is why the fallacy has an existential threat to humanity.
And this is why we must resist.
2. One resistance with two aspects
A generation that does not know the truth beyond materialism (and the truth of beyond-material) 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 more “objective” 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. That capacity is transalgorithmic. The label is less important than the fact: judgment is not leftover computation. It is the thing computation cannot be.
The resistance has the following two aspects.
The spiritual and metaphysical[1]. Human intuition and moral judgment are ontologically distinct from algorithmic computation. Root the purpose of human existence in spirituality, and make a claim in metaphysics and the philosophy of mind. Life must be lived with an eternal purpose; and the machine-human distinctionIt should be made as such.
(Note 1: Due to the limited scope of this essay, I put the two together, knowing that the keen-minded will see the essential difference between them.)
The practical. Whether or not the official culture ever concedes, 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 spiritual and the metaphysical critically reexamine the intellectual foundation of mainstream AI optimism. The practical way of living builds habits, friendships, skills, and institutions that preserve human value even while the spiritual and philosophical fight continues. The second does not replace the first. It prevents the first from becoming an alibi for passivity.
We must refuse the fallacious 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, code, measure, optimize, and ship. Those are real skills. When these skills are increasingly automated using AI, the efficiency and productivity is improved, which is a good thing, because the human is behind it and is being augmented. But when the augmentation is perceived as a substitution, and the substitutor is perceived as an ontological replacement, they become destructive. 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 aspiration or decoration; it has never been. With the rise of AI augmented with satanic materialistic worldview, faith will more directly determine whether one stands or falls after all the life’s 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. Use AI as a tool, not an anthropomorphic advisor
Intuition and moral judgment are transalgorithmic. But AI still has enormous instrumental power. The error is not using the tool. The error is letting the tool define the purpose, the good, and the self.
First and foremost, as long as possible, consciously and intentionally use AI as a tool, instead of an anthropomorphic advisor. When you mentally and psychologically treat AI as human, even if unintentionally, it inevitably becomes your rival or even your “priest” who leads you to a false god to alter your humanity and to enslave you.
Use it to create software that that has well-defined functionality and purpose and gives you deterministic results. This ensures the software objectively serves the clear purpose defined by you. This is fundamentally and functionally different from chatting with AI and also very different from using AI agents to perform broadly and loosely defined functions. You do not need to learn any computer codes to create software now. All you need is your true human agency, your understanding of the purpose and functionality, and your ability to review and judge, to see what is good, and to instruct.
Use it in a decentralized environment. When AI agents are used, always prefer such agents that are coordinated and under control by the definitive software you created (or created for you by a third party whose economic interest is based on providing utility alone, not in mining your data and your life) and use data you provide or define. This is your digital sovereignty. You cannot afford losing it. For most people, this is still not realistic at the present time, but it will be.
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 can replace neither. This is because the experience is personal and specific, while AI is broad and general; and intuition is spiritual and transalgorithmic, while AI is merely algorithmic.
Demand both dignity and 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.
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 acknowledge that human intuition is spiritual and transalgorithmic, it must accept the unique and intrinsic value of human experiences and acknowledge that the social cost of treating people as spare parts is already visible and increasingly unacceptable.
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 ask AI a question: be very clear in your mind what is factual and what is an opinion.
- 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.
- When you measure yourself: refuse the metric that treats human like a machine.
- Where you interact with the world of AI: refuse the notion or sentiment that a machine is like human.
Conclusion
The mainstream story about AI is worse than being just incorrect (either too pessimistic or too optimistic, depending on your point of view). It is ontologically wrong. It is spirit-withering and soul-corrupting materialism. It is a cramped picture of life, inspired by an invisible enemy and enforced by compromises, and now offered to the young as reality and an inescapable future.
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 tool toward ends that are actually good.
Do not defend humanity by retreating into pragmatism. Do not defend humanity by competing with the machine on the machine’s terms. Develop sound judgment that is both purposeful in spirit and necessary in practice: one who can see beyond the material realm, who can answer for a hard choice, who can refuse a fluent wrong. Yes, become someone who doesn’t sacrifice freedom for convenience, doesn’t distort purpose for immediate gains, and doesn’t fail to love facing hardship.
That is how this last generation can remain in truth, faith, hope, and love in an age of powerful tools.
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