Coming in for a Landing

Remarks at NatCon 2025

I delivered the remarks below at the National Conservatism conference in Washington, D.C., at a session entitled “Tech and the Future of the Family.” I wish to thank the organizers of the conference for hosting me, and my fellow panelists—Michael Toscano, Tim Estes, Clare Morrel, and Terry Schelling—for the excellent discussion. I hope to keep the conversation going.

I’m here to speak with you about technology and the future of the family. I feel I must speak to you about the future more broadly. For there is no institution in human history more intrinsically forward-looking than the family, no institution more deeply predicated on the notion that the future will be better than the present.

If we knew the future were to be bleak, it would not be worth living to see. Why would anyone go through the trouble of childrearing, of cultivating a young mind, if they did not believe the future would have anything to offer that child?

If we did not believe in a bright future, there would be little sense in building a family, or anything at all. The only purpose left would be procuring our daily fix of dopamine.

This, I think, is the fundamental sickness afflicting the Western world today: we have lost our belief that the future will be worth being a part of. Suicide of all sorts—the visceral, literal kind and the slow, civilizational kind—is being committed all around us. We see it in the abstract statistics, in the nihilistic social media and the other addictions of our people, in the endless self-flagellation of our chattering classes and media, and in the self-imposed deindustrialization in whose shadow we now live.

It is no wonder, then, that Western fertility has fallen off a cliff.

I cannot tell you comprehensively why this has happened. But one reason, I suspect, is that we live in a civilization that feels it has run out of ideas.

The scientific and industrial revolutions were the great starting guns of our contemporary civilization. The echoes of their blast have grown more distant by the decade. It was probably around the time they first became faint that we declared ourselves to be in a state of “postmodernity.” That was a long time ago. Are we post-post-modern now, or are we up to post-post-post modern?

Will our future will be fundamentally generative or whether it will be fundamentally decadent? Will our children spend their time adding more “posts” in front of “modern”? Or are we today in a state of “pre”… something—something our children will name? Something they will sculpt with their hands and minds?

To help me explain how we ended up at this fork in the road, I’d like to tell you a story. Like all stories, it is stylized. My story begins with Isaac Newton, Francis Bacon, and Rene Descartes, collectively the fathers of modern science. Together, they articulated the basic thesis in which nearly all science and technology is rooted: that nature, including the human body, is an assemblage of machines which can be understood, and even controlled, through rationalistic inquiry.

The scientific method they together formulated, and the radical goal of mastering nature, are not the focus of my critique. Instead, it is the idea of nature as a machine that I believe must be revisited.

One of the inventions that characterized this time period was the portable timekeeping device, eventually to be known as the pocket watch. These now-primitive timekeepers were essential to many of the experiments Newton himself performed; after all, it would have been hard to arrive at 9.8 meters per second with a sundial.

I imagine Newton there, watching the motion of falling bodies, wondering what it is that holds the stars together, and looking at his pocket watch. A machine. A complex machine, but one that, if you understand all its components, makes sense. A machine which can be picked apart, rationally interrogated, and comprehensively understood. What an astoundingly bold metaphor to extrapolate to our universe, and this Newton did.

Scientific inquiry, founded on the notion of nature as a machine, would prove to bear seemingly limitless fruit—inventions of all kind, prosperity aplenty, and a sense of endless opportunity. It is here from which the deist conception of God as a “clockmaker” comes. We equated nature to a manmade invention, and in so doing, we brought God down to our level. Now one of us, many felt they could dispense with him altogether, and dispense with him they did.

And our science continued apace. We built new theories, new abstractions. We discovered and taxonomized all the components of nature, and then the components of those components, and the components of those components, on and on, in fractal-like glory. We used those discoveries to invent new things—bigger, grander, more precise machines. We built new institutions and legal structures to accompany these machines. We organized ourselves in novel ways, most notably the modern business enterprise, to accommodate the newly enlarged scale of our ambition. Very often, we did so with the same attitude of Newtonian science: that the world is a machine we can understand and order rationally.

America was ever the pioneer. We took to the skies. We landed on the moon. We split the atom. We forged the transistor. We dreamed of a future with flying cars, abundant nuclear energy, and space travel—and that future seemed close at hand.

And then, rather suddenly, we slowed down.

Science ran into a wall of complexity. Things that were supposed to be near—nuclear fusion, the curing of diseases, and even artificial intelligence itself—proved far harder than they were supposed to. The resources devoted to science for the most part only grew, yet the practical fruit of the endeavor began to diminish. Increased specialization, fiercer competition, richer sophistication, much harder work—all for fewer gains. This is the dynamic that has dominated science for much of our lives.

An economist would say that the scientist’s labor productivity has stagnated, but I suspect something deeper is afoot here. We have reached the end of a scientific and technological paradigm that has persisted for centuries: that of nature as a machine.

You might not believe me that the end of this paradigm has anything to do with the future of the family. But consider this: the Newtonian, mechanistic view of the world undergirds much of our industrial society institutions: the world of urban street grids, static regulatory thresholds, fixed academic disciplines, social security numbers, standardized tests, and clinical trials that treat “disease” as discrete, Platonic objects.

Shocking amounts of the visible and invisible infrastructure around you flows from this mechanistic view of the world. And the manifest, repeated failures of that infrastructure in our lives today surely makes us question whether society is going downhill, and hence whether the future will be worth the trouble of creating a family.

We have lost the ability to explain the world around us to ourselves and to our children. In other words, we have lost the plot. We need a new story, a new model of the world, to replace the old.

There are well-developed schools of thought to take the place of the mechanistic persuasion. What is needed is a philosophy, a worldview, rooted in the understanding of holistic systems and processes—the study of the relation of all the parts of a system to one another, rather than the obsessive focus on understanding each part in isolation. Such a course would not even be “interdisciplinary”: it might even cast the idea of discrete “disciplines” aside entirely.

In the academy, some of these ideas are referred to as “complex systems theory” or “nonlinear dynamics,” and these fields have much to teach us. But in truth, many of the core ideas go back through the centuries to ancient times.

The revolution approaching is not an upheaval: it resembles, instead, the revolution of a wheel—a restoration.

There is perhaps no invention that epitomizes the mechanistic era better than the microscope. What we need for the new school of thought is a new lens, a new way of seeing the world. I submit to you that one of these is artificial intelligence.

Consider the problem in biomedicine of protein folding, or predicting what shape a protein will take based on its genetic sequence. Because proteins are the output of genes, and because their shape dictates their function, solving this problem was thought to be a key step on the way toward a biomedical renaissance.

The problem is that there does not appear to be a human-interpretable set of mathematical or scientific rules by which proteins take their shape. So protein structures had to be solved manually, one by one, with each taking years. By 2021, humans had solved roughly 185,000 protein structures.

In July of that year, Google DeepMind released a statistical model called AlphaFold, which predicted the structure of 350,000 proteins—more than all of humanity combined. A year later, it predicted 200 million.

AlphaFold was based on something called deep learning, which is fundamentally an approach to statistics drawn from an eclectic mix of philosophical, scientific, and mathematical traditions. Deep learning is at the heart of everything that we today call “AI.” It is not new: deep learning was substantively theorized, and even put to primitive use, in the 1980s, before many of us in this room today were born.

AlphaFold did not work because it was explicitly programmed with some great scientific theory or mathematical insight about the nature of protein folding. Instead, it employed a basic formula that will now be familiar: a simple mathematical architecture, data, and compute. From this, and essentially this alone, was born a machine that learned something fundamental about the nature of protein structures.

Neither we nor the machine can quite say what that fundamental learning is. Famously, we ourselves only dimly understand how these deep neural networks work. AlphaFold did not solve the protein folding problem. We are no closer today to establishing theories or rules for how proteins find their structure. I do not believe such theories exist. Just as a superstar quarterback need not have mastery over the equations of physics, a well-trained neural network captures the mystery without ever quite defining it.

In this sense, AlphaFold can be seen as humanity throwing in the towel on its centuries-long effort to observe, taxonomize, theorize, and master the mechanistic universe. Not a renunciation of our past efforts, but an admission that we have taken the metaphor of nature as a machine to its limit. Yet this is not defeat—no, it is a beginning. With deep learning, we accepted the mystery, we dove into it, and once we did we discovered so much more than we could when we denied the mystery in the first place.

One by one, intractable problem after intractable problem has fallen to deep neural networks: recognition of objects in images, complex games, DNA and RNA sequences, proteins, the weather, the plasma in a nuclear fusion reactor, and of course, language itself.

The models trained to predict language are likely to lead the way, though they will not be the only actors on the stage. For it is in language that the seed of human ingenuity lies. And so it is in a deep neural network trained predominantly on language where transformative artificial intelligence is likely to be found. I believe it is our human destiny to find this invention. After all, who is it that made silicon among the most abundant materials beneath our feet, and who is it who told us “in the beginning was the word”?

The powers these tools will in the fullness of time confer on humans will awe us. They will require novel institutions, novel forms of human organization, novel abstractions, and novel legal structures to conserve our cherished ordered liberty. The path ahead is narrow, the transition will be bumpy, and our work will take decades.

I believe humans will use deep neural networks to gain newfound mastery over nature, delivering a new era of prosperity, vitality, and health. I hope that AI will end the drive for specialization, heralding a return of the liberal arts and the renaissance man. And I believe that we can build a more humane world—a re-humanized world. For our new lens, our intelligent machines, learn patterns rather than imposing blueprints. Would you rather be understood as people by machines, or continue to be understood as cogs, as mere clockwork, by the aging systems of high modernism?

The future will mean saying hello to the new, but it will also sometimes mean saying farewell, even when we do not want to. We must not forget that the American feeling is one of youthful boldness and hunger for the future. And yet we must avoid approaching this era with the moral and ethical vacancy that characterizes contemporary liberalism. To paraphrase President Coolidge, we should not hesitate to be as revolutionary as science, nor as reactionary as the multiplication table.

Make no mistake: the bright future I envision is fragile. A tiny error could send us down a deeply wrong path. For we will have to build atop the institutions, habits, and infrastructure of old, and just like our mechanistic conception of nature, many of them, too, are showing their age.

I am reminded of one of the great, wild enterprises of our day: the SpaceX Starship. On a test flight this past weekend, the company sent its rocket into orbit for the first time and then brought it back down to Earth. The plan is to land the rocket as a leaf falls to the ground, in a sense gliding down from space, through the atmosphere, back to terra firma.

But as the vehicle hurdles toward earth through thick atmosphere at tens of thousands of kilometers per hour, it becomes so hot that plasma forms around it. On this most recent flight, the flaps that are the vehicle’s only chance at making it down in one piece caught fire. Yet Starship made it back, just a little bit on fire.

Our flaps, too, are likely to catch flame as we navigate to the bright future. It will be the duty of our children to build the new world, but the least we can do is keep the ship steady, just a little aflame, coming in for a landing.

Let that be their inheritance. Let that be our legacy.

Thank you.