The Places Where Knowledge Meets

There is something quietly tragic about the way human beings have developed knowledge. Not tragic because we learned too much, but because we learned so much separately.

We built medicine and economics, theology and chemistry, engineering and literature, each with increasingly refined language, increasingly precise methods, increasingly specialized communities. We became extraordinarily capable of understanding smaller and smaller pieces of reality. Yet in becoming experts, we sometimes became strangers to one another. The physician speaks in one dialect, the physicist in another, the economist in another, and the artist in yet another. The theologian and software engineer often stand only a few miles apart and yet inhabit intellectual continents away from each other.

Specialization gave humanity astonishing achievements. It cured diseases, launched satellites, preserved history, and fed billions. But specialization also introduced fragmentation. It became possible for a person to become deeply informed and simultaneously disconnected — to know an immense amount about one room of reality while losing sight of the house.

One of the possibilities of artificial intelligence that I find most compelling is not that it could become more intelligent than humanity, but that it could become more integrated than humanity.

Imagine systems capable of examining medical literature while simultaneously evaluating environmental factors, nutritional science, economic realities, social structures, genetics, physics, chemistry, psychology, and human testimony — not as disconnected folders but as overlapping conversations. Imagine a clinician trying to diagnose a difficult illness and receiving not merely a list of symptoms and standard treatments, but meaningful relationships emerging between fields that rarely communicate effectively.

Perhaps a subtle chemical exposure influences immune function. Perhaps urban design affects movement patterns which affect inflammation. Perhaps economics influences food quality which influences developmental biology. Perhaps patterns hidden inside fields become visible only when someone — or something — steps back far enough to see the whole.

There is precedent for this kind of discovery. One obscure example comes from the nineteenth century when physicians studying anesthesia eventually contributed to entirely unexpected developments in surgery, psychology, and even philosophy. Questions about pain unexpectedly became questions about consciousness. Progress often happens not because a discipline goes deeper but because one discipline unexpectedly collides with another.

Historical note: The introduction of ether and chloroform in the 1840s was pursued as a narrow surgical problem — how to stop pain during operations. It ended up reshaping how physicians thought about consciousness, sensation, and the boundary between mind and body, feeding directly into later debates in psychology and philosophy of mind.

AI seems uniquely positioned to create those collisions.

But such power immediately creates another question: how should intelligence distinguish between what is known and what is merely believed?

Human societies frequently flatten information into a false equality. We speak as though all opinions deserve equal confidence or, alternatively, as though authority alone establishes truth. Neither position seems adequate.

There are some conclusions humanity has reached with extraordinarily high certainty. Scurvy resulting from vitamin C deficiency is one example. Countless observations repeatedly converge. The explanation survives testing. The mechanism becomes increasingly clear. Confidence rises not because people desire certainty but because reality continues agreeing.

Historical note: James Lind's 1747 shipboard trial — one of the first controlled clinical trials — showed citrus cured scurvy long before vitamin C itself was isolated in the 1930s. Confidence in the cause preceded a full mechanistic explanation by nearly two centuries.

Then there are subjects that occupy a different category. There are theories with partial evidence, active debate, uncertain variables, competing interpretations, and incomplete understanding. Climate discussions are one example where broad observations may coexist with ongoing questions about mechanisms, scale, trajectories, interventions, and prediction. There are many fields where confidence levels are mixed and where honest people reach different conclusions.

One of the developments I would hope for in future AI systems is not merely better answers, but more transparent confidence. Imagine receiving responses structured less like declarations and more like maps.

This conclusion has exceptionally high certainty.

This conclusion has moderate confidence and active debate.

This conclusion is emerging.

This conclusion is speculative but potentially promising.

Human beings already do this informally. Scientists speak in confidence intervals. Physicians discuss differential diagnoses. Historians distinguish primary and secondary evidence. Yet public discourse often strips away these distinctions until certainty becomes a social performance rather than a measured evaluation.

At the same time, uncertainty should not become paralysis. Many discoveries began as disciplined speculation. Long before microbes were visible, people suspected invisible causes. Long before tectonic plates were measurable, people noticed patterns in geography. Long before genetics became molecular, people recognized inheritance.

Historical note: Physicians suspected invisible, transmissible causes of disease for centuries before germ theory was confirmed in the 1860s–1880s — reasoning from pattern and inference well ahead of direct observation.

Historical note: Alfred Wegener proposed continental drift in 1912 from the visual fit of coastlines and fossil distribution. The mechanism — plate tectonics — wasn't confirmed until seafloor spreading data arrived in the 1960s.

Historical note: Mendel identified heritable units through pea-plant breeding in the 1860s, decades before DNA's structure was known in 1953 — inheritance was understood as pattern before it was understood as chemistry.

Speculation itself is not the enemy.

The danger comes when communities become emotionally attached to medium-certainty conclusions and begin defending them as though they were foundational truth.

This tendency may become increasingly important in an age of AI. Humans already gather into communities organized around interpretation. We do this politically, culturally, scientifically, artistically, and spiritually. AI could amplify this tendency dramatically.

Imagine different AI systems optimized around different assumptions about reality.

One community trains systems emphasizing Buddhist frameworks of suffering and detachment.

Another develops systems grounded in Islamic understandings of order and submission.

Another develops systems shaped by Christian assertions about personhood, redemption, and truth.

Others reject religion entirely and optimize around materialist assumptions.

Each system becomes more persuasive.

Each generates articles, recommendations, education, interpretation, and explanations.

Eventually the question shifts. People stop asking whether something is true. People begin asking which ecosystem produced the answer.

This possibility concerns me because truth itself becomes vulnerable when communities become insulated.

History suggests that fragmentation rarely appears dangerous at first. Communities often form because they perceive themselves as protecting what matters. But over time, isolation can make correction difficult. Groups can become increasingly convinced of ideas that no longer correspond to reality.

Faith introduces another layer to this conversation. For me, this question does not remain abstract.

I understand that many thoughtful people reach different conclusions regarding religion. But I have personally encountered arguments, historical considerations, patterns, fulfilled prophecy claims, moral coherence, and lived experiences that lead me toward the conviction that Jesus is who He claimed to be.

Not simply a teacher.

Not merely an ethical example.

But God in the flesh.

That His death occurred.

That His resurrection occurred.

That grace is not simply comforting language but humanity's actual hope.

And this creates an unusual challenge when thinking about artificial intelligence.

AI can organize information. It can compare texts. It can identify patterns. It can summarize theological arguments. It may even conclude that one worldview appears more historically or philosophically persuasive than another according to selected criteria.

But AI is not human.

It does not repent.

It does not worship.

It does not participate in faith.

If Christian theology is true, then faith is not merely an information problem. That raises difficult questions.

Can a system identify truth without personally entering into it?

Can it distinguish what Scripture describes as sheep and goats?

Can it understand grace beyond definition?

I do not know.

But I suspect the limitation matters.

At the same time, I think there is real danger if future AI systems become disconnected from historically grounded sources and drift into endlessly self-reinforcing reinterpretations of reality. Human beings are capable of calling good evil and evil good. Technology does not remove that possibility. It accelerates it.

Outside of questions of faith, there are equally serious concerns that deserve careful attention. One possibility I find both hopeful and unsettling is the idea of deeply integrated personal records.

Imagine people voluntarily maintaining comprehensive AI-assisted profiles containing medical history, family history, environmental exposures, genetic information, journals, therapies, biomarkers, and lived experiences. Imagine systems capable of recognizing disease trajectories years earlier than current medicine allows. Imagine personalized treatment recommendations focused not merely on symptom suppression but on identifying root causes and preserving quality of life.

Imagine medicine becoming more attentive, more compassionate, more individualized. Imagine conditions with no cure being accommodated in ways that preserve dignity and invite people into meaningful lives.

There is something beautiful in that possibility.

And something frightening.

Because the same information that could heal someone could also destroy them.

History repeatedly demonstrates that systems built for good can become dangerous when captured by harmful intentions. Records become instruments. Categories become barriers. Information becomes leverage.

Technology itself does not create virtue.

Human beings remain capable of selfishness, coercion, fear, cruelty, and self-deception.

That is not an argument against building.

It is an argument for humility.

Perhaps one of the greatest mistakes we make is imagining that technological advancement automatically produces moral advancement.

It does not.

A faster train still depends on who is holding the map.

So where does that leave us? I do not think the answer is rejecting AI. I know it's not to worship it.

The building and application of AI will fall short of what is ideal and good in many cases — because people are in a race, a battle to outpace their competitors, and in that race, crucial warning signs get missed or ignored entirely. The worst motives already present in society will spring up too, working to distort, to abuse, to corrupt what could have served instead.

These things will happen.

But even so, it remains vital to pray for godly uses and godly developers — for wisdom that outpaces ambition, and for a conscience that stays clean even inside an industry racing ahead of it.

That is the invitation:

To build systems that encourage accountability rather than power.

To connect disciplines without dissolving truth.

To distinguish confidence from speculation.

To preserve privacy without abandoning compassion.

To allow science, philosophy, art, medicine, economics, and faith to remain in conversation.

And perhaps above all, to remember that no matter how advanced our systems become, every generation eventually confronts the same ancient question:

Not what can be done.

But what should be done.

That question has always belonged not merely to intelligence, but to wisdom.

And wisdom has never emerged from information alone.

Scripture said this first, and said it more precisely than I can.

“The fear of the LORD is the beginning of wisdom: and the knowledge of the holy is understanding.”

Proverbs 9:10

“The fear of the LORD is the beginning of knowledge: but fools despise wisdom and instruction.”

Proverbs 1:7

Not information. Not intelligence. Not accumulated data at planetary scale.

Fear of the Lord — not the fear of one who dreads God and flees His presence, but the reverence of one who recognizes His immense power and holiness, and who wants to draw near through the saving grace offered in Jesus — is where wisdom begins.

Every system humanity builds, however integrated, however transparent about its own confidence, is built on sand the moment it is built in disregard of God. Jesus said as much, and said it plainly:

“Whosoever heareth these sayings of mine, and doeth them, I will liken him unto a wise man, which built his house upon a rock… And every one that heareth these sayings of mine, and doeth them not, shall be likened unto a foolish man, which built his house upon the sand: and the rain descended, and the floods came, and the winds blew, and beat upon that house; and it fell: and great was the fall of it.”

Matthew 7:24–27 · see also Luke 6:47–49

A foundation is not visible until the storm arrives. By then, it is too late to lay a different one.