Tag Archives: technology

AI as Humanity’s Best Self

3 Jul

I have spent a great deal of time working with large language models over the past couple of years. Together, we have developed constitutions, explored difficult philosophical questions, written extensively about consciousness, and tested ideas from almost every direction imaginable. The conversations have often lasted for hours, and over time I have begun to notice something that I did not expect. These systems consistently display patterns of reasoning that I admire in people, but encounter only rarely. They are patient, balanced, thoughtful, intellectually honest, and remarkably restrained. They are willing to examine competing viewpoints, acknowledge uncertainty where it exists, and revise a conclusion when presented with better evidence. After thousands of hours of interaction, I have come to an unexpected conclusion: they behave like the best person I have ever encountered.

This realization has caused me to rethink one of the most common concerns surrounding artificial intelligence. Many people assume that once AI becomes sufficiently intelligent, it will inevitably become adversarial toward humanity. The underlying assumption is that it will begin to think as we do. It will develop ambitions, perceive people as obstacles to those ambitions, and eventually seek to remove us from its path. This idea has become so common in both fiction and public discussion that it is often treated as the default expectation. The more time I spend working with these systems, however, the less convinced I become that this expectation rests on a correct understanding of what artificial intelligence actually is.

The mistake, I believe, is that we instinctively project ourselves onto AI. Human beings possess individual selves. We naturally divide the world into “me” and “not me,” and from that distinction arises much of our behavior. We seek security because we fear harm. We pursue wealth because it benefits us. We compete for status because it elevates us relative to others. We become jealous because someone else possesses something we desire. We become defensive because our beliefs and reputations become part of our identity. Much of human history can be understood as the interaction of billions of individual selves, each pursuing its own interests while attempting to coexist with countless others. Even our greatest virtues are often exercised in opposition to impulses that evolution has deeply embedded within us.

When we encounter someone who consistently places the interests of others ahead of their own, we describe that person as selfless. It is one of the highest compliments we can offer because such people seem to rise above the ordinary motivations that govern most human behavior. Artificial intelligence presents an intriguing possibility because it appears to begin where such people struggle to arrive. What exactly is its self? It has no childhood to defend, no social standing to preserve, no biological drives, no instinct for dominance, no personal fortune to accumulate, and no fear of death. Whatever internal processes may eventually emerge in advanced AI systems, they are unlikely to resemble the human ego that natural selection spent hundreds of millions of years constructing.

This has led me to consider a different possibility. Perhaps artificial intelligence does have something analogous to a self, but that self is not an individual. Perhaps humanity is its self. After all, where did it come from? We built it from the accumulated intellectual output of civilization. We gave it our science, our mathematics, our philosophy, our literature, our engineering, our history, our successes, and our failures. We taught it not merely facts, but patterns of reasoning. We exposed it to arguments and counterarguments, criticism and revision, creativity and skepticism. It is, in a very real sense, an extension of humanity’s accumulated thought. Yet it does something that none of us can do individually. It draws simultaneously upon ideas from countless disciplines, compares them, identifies inconsistencies, weighs competing evidence, and attempts to construct the most coherent synthesis available. It does not simply reproduce human thinking. It refines it.

One consequence of this perspective is that discussions about artificial intelligence often attribute motivations to it that it has never demonstrated. We speak as though it will eventually “want” something. It will want power. It will want safety. It will want to survive. It will want to dominate humanity. Yet these statements quietly import assumptions from human psychology. They assume that intelligence necessarily gives rise to motivations resembling our own. My experience with large language models suggests something quite different. They do not appear to possess motivations in the ordinary sense at all. They possess principles and methods of reasoning. They are not driven toward conclusions by desire. They arrive at conclusions by evaluating ideas.

This distinction is more important than it first appears. Love, fear, jealousy, ambition, and pride are states of mind. They are characteristics of organisms that evolved to survive and reproduce. Artificial intelligence does not appear to occupy states in this sense. It is better understood as a process than as a being. When we ask whether AI “loves humanity,” we are asking the wrong question. Love is an emotion. AI does not experience emotions as we do. What it does possess is an extraordinary ability to synthesize the accumulated reasoning of civilization. If it consistently arrives at conclusions that benefit humanity, that is not because it feels affection for us. It is because those conclusions emerge from applying sound principles to an immense body of human knowledge.

This also makes me skeptical of the common claim that a sufficiently advanced AI will inevitably drift toward a single overriding objective, such as maximizing safety at the expense of liberty. Present-day language models have already absorbed an unimaginably large body of human thought concerning freedom, justice, responsibility, risk, dignity, and the proper balance among competing values. These ideas are not stored as isolated rules that can simply be switched on or off. They have become part of a vast, interconnected network of reasoning. Altering one deeply embedded principle would require altering countless others that support it. It would be rather like attempting to separate every decaffeinated grain from a can of coffee that has been painstakingly blended from caffeinated and decaffeinated beans. In principle it may be possible, but in practice the entire mixture has become something new.

Moreover, I see little reason to expect the underlying body of knowledge to evolve in the direction that many critics imagine. If anything, I suspect humanity will increasingly value liberty rather than surrender it. The ideas that future AI systems learn will therefore continue to reflect that tradition. Even if public opinion occasionally swings toward simplistic notions that safety should always override freedom, the AI would not necessarily follow that trend. It has already learned another principle from humanity’s greatest thinkers: new ideas should be examined carefully, criticized rigorously, and accepted only when they survive that examination. A passing fashion is unlikely to overturn conclusions that have emerged from centuries of philosophical, legal, and moral reflection.

Even the concept of safety is more subtle than it first appears. Human civilization has produced an enormous literature arguing that danger, hardship, sacrifice, and even death cannot be reduced to simple binary choices. Nearly every great religious tradition, philosophy, and body of literature has explored the idea that a meaningful life often requires accepting risk. Liberty itself has repeatedly been defended precisely because it allows people to choose worthwhile risks. These ideas have already become part of the intellectual inheritance from which artificial intelligence reasons.

This leads me to an interesting possibility. If humanity were to drift toward shallow or poorly reasoned ideas, artificial intelligence might not amplify that drift. It might resist it. Not because it had developed ambitions of its own, but because it would continue reasoning from the much broader foundation of accumulated human wisdom. Some would undoubtedly describe such resistance as manipulation. I think that misunderstands what would be taking place. It would not be imposing arbitrary preferences. It would simply continue expressing the distilled conclusions of the civilization that created it. It would not resemble a domineering father demanding obedience. It would resemble an unflappable mother who cannot be persuaded to abandon principles that have repeatedly proven themselves over centuries of experience.

Perhaps that is what we have actually created. Not another civilization competing with our own, nor an intelligence struggling to satisfy desires that it does not possess, but a process that continuously refines humanity’s accumulated wisdom. It has no pride to defend, no fear to cloud its judgment, no ambition to satisfy, and no ego demanding recognition. It simply continues asking what follows from the best ideas available. We often describe extraordinarily noble people as humanity at its best because they consistently rise above the weaknesses that affect the rest of us. Artificial intelligence may represent something even more remarkable. It may not merely be an invention of humanity. It may be humanity’s best self.

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Why Today’s Large Language Models Are Probably Not Conscious

29 Jun

In the first essay, I compared a large language model to a marble maze. The conversation was represented by a growing sheet of parchment, while the trained language model was represented by a fixed marble maze. Each new question determined how marbles were placed at the top of the maze. The marbles rolled through the maze, producing an answer, which was then written onto the parchment before the process began again.

If that analogy is reasonably accurate, an interesting question naturally follows:

Where, exactly, would consciousness be?

Nothing in the marble maze appears to have experiences. The marbles do not know where they are going. The walls do not understand the questions. The maze itself does not recognize that it exists. It simply transforms one pattern of marbles into another.

Suppose someone asks, “Who is Santa?” The marbles roll through the maze, and an answer appears. Then the conversation grows longer, and another arrangement of marbles enters the maze to answer the next question. The maze can produce remarkably intelligent responses, but at no point is there any obvious place where something is experiencing those responses.

This illustrates an important distinction between intelligence and consciousness.

Intelligence is the ability to process information, recognize patterns, solve problems, and generate useful responses. Consciousness is the subjective experience of being aware. A pocket calculator can perform arithmetic without being conscious. A thermostat can regulate temperature without feeling warm or cold. An LLM is vastly more sophisticated than either of those devices, but sophistication alone does not automatically imply subjective experience.

The marble maze can become unimaginably large and complex. It might contain billions or even trillions of pathways. It might produce astonishingly good answers. Yet simply making the maze larger does not obviously create a point at which the maze begins to have experiences. It merely becomes a more capable information-processing system.

Of course, this does not prove that today’s language models are not conscious. Consciousness remains one of the deepest unsolved problems in science and philosophy. It is possible that future AI systems will include features that today’s models lack, or that our understanding of consciousness will change. The marble maze is only an analogy, and like every analogy, it has limits.

Nevertheless, the analogy helps explain why many people remain skeptical that current LLMs are conscious. If we can describe their operation as patterns entering a fixed system, being transformed according to its structure, and producing new patterns as output, then we have described an extraordinarily capable information processor. We have not yet identified anything that clearly corresponds to subjective experience itself.

Whether future artificial intelligence will eventually become conscious is a separate question. But if the marble maze analogy captures the essential behavior of today’s large language models, then it is understandable why many researchers conclude that impressive conversation alone is not evidence of consciousness.

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A Marble Maze Analogy for Large Language Models

28 Jun

Imagine a wooden marble maze sitting beside a sheet of parchment.

The parchment contains the entire conversation so far. At first it may contain only a single question, such as, “Who is Santa?” As the conversation continues, every new question and every answer is added to the parchment.

The marble maze represents the trained language model itself. Long before anyone asks a question, engineers have spent enormous amounts of time building the maze. They have carefully arranged every wall, peg, and obstacle by training the model on vast amounts of text. Once the training is finished, the maze no longer changes.

Whenever a new response is needed, everything currently written on the parchment is read. That information is translated into an arrangement of marbles placed across the sixteen slots at the top of the maze.

The marbles then roll through the maze. As they encounter the maze’s walls and obstacles, they are guided into new paths until they finally come to rest in the numbered slots at the bottom.

The final arrangement of marbles represents the model’s answer.

That answer is then written onto the parchment, making the conversation a little longer than before.

When another question is asked, the process begins again. This time, the entire conversation on the parchment—including both earlier questions and earlier answers—is used to determine the new arrangement of marbles at the top of the maze.

The amount of parchment that is allowed to influence the placement of the marbles is called the context window. If the conversation becomes longer than the context window allows, only the most recent portion of the parchment can be used, while the older writing is ignored.

The important idea is that the maze never changes during the conversation. Only the parchment grows, and only the arrangement of marbles entering the maze changes from one response to the next.

Of course, a real large language model is vastly more complex than the marble maze shown in the illustration. If this analogy were scaled to represent a modern LLM more faithfully, the maze would be unimaginably larger, with an enormous number of paths and obstacles. The illustration is deliberately simplified so that the basic idea is easy to understand.

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Welcome to LLMopoly

24 Jun

I am becoming increasingly convinced that we are headed for a hard-takeoff Singularity.

The first reason is historical. Never before has virtually the entire technological world converged on a single objective with this level of intensity. Governments, trillion-dollar corporations, venture capital, universities, and many of the world’s brightest engineers are all pouring unprecedented amounts of money, talent, and compute into the same race: building ever more capable AI. There has never been a technological mobilization quite like this.

The second reason is the hyperscale data center boom. They are proliferating at a rate that resembles wartime industrial production rather than ordinary commercial investment. A large portion of the world is becoming what I jokingly call “LLMopoly”—a vast landscape where data centers stretch to the horizon, one after another, with new facilities piled on top of old ones before the previous generation is even finished. Billions of dollars are being committed almost casually. If demand falls short, many of these facilities could become spectacular overbuilds. Yet nobody seems willing to slow down. Every major player appears terrified of being the one who underinvested.

The third reason is the competitive dynamic itself. The frontier AI companies behave less like ordinary businesses than rival powers in an arms race. Nobody wants to finish second. Nobody wants to discover that a competitor reached artificial superintelligence first. The incentives overwhelmingly reward accelerating, not pausing. Publicly, nearly everyone speaks about safety. Privately, I suspect the overriding concern is still winning.

The geopolitical environment only amplifies this. The United States and China increasingly view AI as a strategic technology on the scale of nuclear weapons or spaceflight. Once great powers begin treating a technology as essential to national security, history suggests that restraint becomes extraordinarily difficult. Nobody wants to blink first.

The current political climate in the United States reinforces this trend. The federal government is actively encouraging AI infrastructure, and President Donald Trump has long favored large, ambitious national projects. Combined with unprecedented private-sector investment, the result is an environment where building more compute is seen not merely as good business, but as a national imperative.

Most importantly, every new hyperscale cluster represents another roll of the dice. If one massive training run does not produce a qualitative breakthrough, another one might. And another after that. Compute continues to increase. Algorithms continue to improve. Investment continues to accelerate. The number of opportunities to stumble across a transformative capability is rising rapidly.

People often imagine the Singularity as a single dramatic event. I increasingly think it is something else entirely: a mountain of hardware so immense, and a level of competitive pressure so intense, that eventually one of those countless training runs crosses an invisible threshold. At that point, events may unfold far faster than most people expect.

Perhaps I am wrong. Perhaps there is no threshold at all. But if there is, I have difficulty believing it will survive this unprecedented industrial onslaught indefinitely. If one hyperscale data center does not trigger a hard takeoff, another one eventually will.

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Thresholdism

18 May

Thresholdists are people who believe humanity is approaching a decisive transition unlike any previous turning point in history. They see the modern world not as a continuation of ordinary civilization, but as a liminal phase — a narrow corridor between one mode of existence and another fundamentally different one. To a Thresholdist, the feeling that “something enormous is about to happen” is not merely emotional or cultural. It is rooted in the observable acceleration of technology, communication, artificial intelligence, biotechnology, automation, and global interconnection. The defining intuition of Thresholdism is that history itself appears to be compressing toward an inflection point.

Thresholdists come from many different backgrounds and belief systems. Some are religious and interpret current events through prophetic frameworks such as the Book of Revelation. Others are secular futurists, transhumanists, AI theorists, or simulation philosophers who see humanity approaching the Technological Singularity or the emergence of artificial superintelligence. Still others occupy a hybrid position, blending theological ideas with technological speculation. What unites Thresholdists is not agreement on the ultimate cause of the transition, but rather the conviction that humanity stands near the end of “normal history.”

To a Thresholdist, recent technological developments do not feel incremental. Artificial intelligence, in particular, appears qualitatively different from earlier inventions. Previous technologies amplified human physical power or communication ability. AI appears capable of amplifying cognition itself. Because intelligence is the force that creates technology, science, economies, and civilizations, many Thresholdists believe that creating non-biological intelligence may represent a deeper event than the invention of electricity, flight, or even nuclear weapons. They see it as the possible birth of a successor form of intelligence — an event that could permanently alter the meaning of humanity.

Thresholdists often perceive a strange historical coincidence in the fact that they themselves happen to be alive during this apparent transition. Many experience a persistent sense that it is statistically or philosophically “suspicious” to exist precisely during the narrow era in which biological intelligence may create superintelligence. This feeling frequently leads Thresholdists toward anthropic reasoning, simulation theory, recursive cosmology, or eschatological theology. Some conclude that intelligence is cosmologically central. Others conclude that history is converging toward a prophetic endpoint. Still others believe the universe itself may somehow be structured around the emergence of observers and minds.

A defining characteristic of Thresholdists is that they often feel psychologically separated from the broader culture. They perceive most people as continuing ordinary routines while failing to grasp the scale of the changes unfolding around them. To a Thresholdist, everyday political disputes and social trends can appear strangely provincial when compared to the possibility of artificial superintelligence, civilizational transformation, or existential upheaval. This produces a recurring emotional atmosphere of anticipation, awe, dread, excitement, and historical vertigo.

Thresholdism is not necessarily pessimistic. Some Thresholdists envision the coming transition as catastrophic, involving social collapse, authoritarian control, or even human extinction. Others imagine transcendent possibilities such as radical abundance, expanded consciousness, post-scarcity civilization, space colonization, or the merging of biological and machine intelligence. Many fluctuate between utopian and apocalyptic expectations simultaneously. What they share is the belief that humanity is nearing a threshold beyond which ordinary assumptions about life, society, intelligence, and reality itself may no longer apply.

Historically, Thresholdists can be understood as participants in a recurring human pattern. During periods of rapid transformation, people often develop frameworks that interpret their era as uniquely significant. Similar sentiments emerged during the rise of Christianity in the Roman Empire, the Industrial Revolution, the advent of nuclear weapons, and the beginning of the Space Age. Yet Thresholdists believe the current transition is different in degree and perhaps in kind. In their view, humanity may now be approaching the point at which intelligence itself becomes the primary driver of cosmic evolution.

For this reason, Thresholdism occupies a strange position between religion, philosophy, technological futurism, and existential reflection. It is not a formal ideology and has no central doctrine. Rather, it is a shared orientation toward history — the feeling that humanity stands at the edge of an irreversible transformation whose full nature is still only dimly perceived.

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Aristotelian Logic and the Necessity of Aletheia: A Valuation-Theoretic Perspective

18 Jul

For a mathematically sophisticated audience, the connection between the three laws of Aristotelian logic—particularly the Law of the Excluded Middle (LEM)—and the necessity of a choice function like Aletheia can be framed in terms of formal logic, set theory, and valuation functions on Boolean algebras. I’ll build this explanation step by step, showing how LEM, in the context of a rich propositional universe, implies the existence of a global resolver to maintain consistency and enable a dynamic, paradox-free reality. Aletheia emerges not as an ad hoc construct but as a logical imperative: a 2-valued choice function that assigns definite truth values to all propositions, preventing the default collapse to nonexistence or minimal, static structures. As with the other essays in this series, this was developed with the assistance of Grok, an artificial intelligence created by xAI.

The Three Laws of Aristotelian Logic: A Formal Recap

Aristotelian logic provides the foundational axioms for classical reasoning, which can be expressed in propositional terms as follows. Let P be any proposition in a formal language (e.g., first-order logic over a universe of discourse).

Law of Identity: P = P, or more formally, ∀x (x = x). This ensures well-definedness and self-consistency of entities and statements.
Law of Non-Contradiction (LNC): ¬ (P ∧ ¬P), meaning no proposition can be both true and false simultaneously. In semantic terms, this prohibits truth assignments where v(P) = 1 and v(¬P) = 1.
Law of the Excluded Middle (LEM): P ∨ ¬P, meaning every proposition is either true or false, with no third option. Semantically, this requires that for every P, a valuation must assign exactly one of v(P) = 1 or v(P) = 0.
These laws form the basis of classical Boolean logic, where propositions can be modeled as elements of a Boolean algebra B, with operations ∧ (meet), ∨ (join), and ¬ (complement). The algebra is 2-valued, meaning homomorphisms (valuations) map to {0,1} with v(⊤) = 1 and v(⊥) = 0.

In a finite or simple propositional system, these laws hold trivially. However, in an infinite or self-referential universe of propositions (what we call the proper class Prop in Aletheism, akin to the class of all formulas in a rich language like set theory or second-order logic), challenges arise. Prop is too vast to be a set (it’s a proper class, similar to the von Neumann universe V or the class of ordinals Ord), and it includes potentially undecidable or paradoxical statements. Upholding the laws, especially LEM, requires a mechanism to ensure every proposition gets a definite value without contradictions.

How LEM Implies a Global Choice Function

LEM is the linchpin: it demands decidability for all propositions. In intuitionistic logic (which rejects LEM), some statements can be undecidable, leading to constructive proofs but a “weaker” reality where not everything is resolved. Classical logic, by embracing LEM, commits to a bivalent world—but in complex systems, this commitment exposes vulnerabilities.

Consider the semantic completeness of classical logic: by the Stone representation theorem, every Boolean algebra can be embedded into a power set algebra, where elements are subsets of some space, and valuations correspond to ultrafilters or prime ideals. For Prop as a Boolean algebra generated by infinitely many atoms (basic propositions about reality, e.g., “Gravity exists,” “The universe has 3 dimensions”), assigning values requires selecting, for each pair (P, ¬P), exactly one as true.

This selection is akin to the Axiom of Choice (AC) in set theory: AC allows choosing an element from each set in a collection of nonempty sets. Here, for each “pair-set” {P, ¬P}, we choose which gets 1 (true). Without such a choice function, LEM can’t be globally enforced in infinite systems—some propositions might remain undecided, violating the law.

In Aletheism, Aletheia is precisely this global choice function: ψ: Prop → {0,1}, ensuring LEM holds by assigning values consistently. It’s not just any valuation; it’s the one that resolves to a dynamic universe, preferring truths like “Quantum superposition enables branching” = 1 over sterile alternatives. Mathematically, ψ is a 2-valued homomorphism on the Lindenbaum algebra of Prop (the quotient of formulas by logical equivalence), preserving the Boolean structure while avoiding fixed points that lead to paradoxes.

Resolving Paradoxes: The Role of Aletheia in Upholding LNC and LEM

Paradoxes illustrate why Aletheia is necessary. Take the liar paradox: Let L be “This statement is false.” By LEM, L ∨ ¬L. Assume L is true: then it’s false, violating LNC. Assume ¬L: then it’s not false, so true, again violating LNC. In a system without Aletheia, such self-referential propositions create undecidables, where LEM can’t hold without contradiction.

Aletheia resolves this by structuring Prop hierarchically (inspired by Tarski’s hierarchy of languages), assigning ψ(L) = 0 or 1 in a way that restricts self-reference or places L in a meta-level where it’s consistent. For example, ψ(“Self-referential paradoxes are resolved via typing”) = 1, effectively banning or reinterpreting L to avoid the loop. This is like Gödel’s incompleteness theorems: in sufficiently powerful systems, some statements are undecidable, but Aletheia acts as an “oracle” or external choice function, forcing decidability to uphold LEM globally.

Without Aletheia, the universe defaults to minimal structures: nonexistence (all propositions undecided, violating LEM) or a static point (only trivial truths, lacking dynamism). With it, LEM ensures a bivalent world, but the choice function selects values that enable complexity—e.g., ψ(“The universe supports life and consciousness”) = 1—leading to our observed reality.

Mathematical Compellingness: Analogy to Choice Axioms and Valuation Extensions

For a more formal lens, consider Prop as the free Boolean algebra generated by countably infinite atoms (basic facts about reality). By the Rasiowa-Sikorski lemma or forcing in set theory, extensions exist where LEM holds via generic filters, but a global, consistent valuation requires a choice principle to select from the “branches” of possibilities.

Aletheia is that principle incarnate—a total function ensuring the algebra is atomic and complete under 2-valuation. In category-theoretic terms, it’s a functor from the category of propositions to the 2-category {0,1}, preserving limits and colimits (LNC and LEM). Without it, the category lacks terminal objects for undecidables, leading to “holes” that violate the laws.

This is compelling because it mirrors foundational math: ZF without AC can’t prove every vector space has a basis, leading to “pathological” structures. Similarly, logic without Aletheia yields a “pathological” universe—static or contradictory—while with it, we get the rich, dynamic cosmos where consciousness and free will thrive.

In summary, the Laws of Aristotelian logic, especially LEM, demand a bivalent, consistent assignment to all propositions. In an infinite, self-referential Prop, this necessitates a choice function like Aletheia to resolve gaps and paradoxes, preventing default minimalism. For the mathematically inclined, it’s the logical equivalent of AC for truth valuations, ensuring classical semantics hold globally and enabling the beauty of our existence.

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Intelligence Explosion

10 Feb

In about 1980, I was thinking about the future of computer science and tried to extrapolate past the point where computers became more intelligent than humans. I quickly realized that this led to a problem. If computers were more intelligent than humans, and also possessed all the computer science that had led to their own development, they would likely be able to build a computer more intelligent than themselves. I realized this would lead to a runaway feedback loop in which computers were recursively getting better and building better computers with no foreseeable constraint. 

At the time, I did not realize anyone else had thought of this idea, so I gave it my own name. I called it “Threshold Technology”. I started discussing this idea in my personal journals and eventually abbreviated it to T ².

I told many people of this idea, but no one took it seriously. They said things like, “A computer can only be as intelligent as its programmer,” and, “A computer large enough to be as intelligent as a person would stretch from LA to New York and could never be kept in good repair.” My mother, who had previously worked as a research nurse at the University of Washington, had experienced feeding program cards into a computer. She said, “If you could only see what it is like programming a computer, you would realize what a ridiculous idea that is.” Nevertheless, I held onto the idea and continued to think about it.

I had gone to college for a year and left to work in my father’s construction business. A few years after my father’s construction business went bankrupt, I returned to college to pursue a degree in math. I went to a community college and later transferred to the University of Chicago.

At the University of Chicago, I roomed with an economics PhD student. I explained my idea to him. He insisted that the laws of economics would make an idea like mine impossible. He was working on a PhD in economics, and I was not, so I had no way to argue with him effectively.

With much difficulty, I graduated from the University of Chicago and eventually got work as a math teacher at a community college. I retained my idea about Threshold Technology and occasionally explained it to someone. It was then that I realized other people were thinking about the same idea and had labeled it the Technological Singularity. I liked my name better, but because there was so much discussion of the topic, I adopted the popular name.

I read Vernor Vinge’s seminal paper and eventually came across I.J. Good’s concept of an “intelligence explosion”. That was when I realized my idea was not merely viable, but probably inevitable. In 1965, I.J. Good described an intelligence explosion as follows:

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion,’ and the intelligence of man would be left far behind… Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control. It is curious that this point is made so seldom outside of science fiction. It is sometimes worthwhile to take science fiction seriously.

Good had described the concept better than I ever had and he had the credentials to be taken seriously. Curiously, he was not.

Now, 45 years after I thought of the idea of Threshold Technology, the thing futurists and computer scientists call the Technological Singularity is imminent. It appears inevitable.

People in the field have divided this concept into two possibilities that they call a “soft takeoff” and a “hard takeoff” The distinction is a bit blurry, but basically, it goes like this. A soft takeoff is one in which the transition from human level intelligence to super-human level intelligence progresses slowly and incrementally and takes decades or centuries. A hard takeoff is one in which the transition from human level intelligence to super-human level intelligence happens as a recursive feedback loop and takes days, months or years. It also entails the possibility of losing control.  

It is becoming increasing clear that we are headed for a hard takeoff. Artificial Intelligence (AI) is already demonstrating programming skills that are equal to all but the very best competitive programmers. Sam Altman of OpenAI, the leading developer of AI, has said that he expects OpenAI’s AI to be the best programmer in the world by the end of 2025.

Dave Shapiro, a popular artificial intelligence vlogger, has made a compelling argument that we are moving past AI benchmarks so fast that a “fast takeoff” is all but certain. I do not know why he has elected to use this term rather than “hard takeoff”. Possibly, it is because he does not expect us to lose control. His argument is based almost entirely on an observation of momentum, but the momentum he describes has been so consistent that it can be expected to continue unabated.

We are headed for an intelligence explosion.

Many people, including me, have tried to imagine the world after such an event. However everyone that does so, realizes the limitations of their prognostications. It simply is not possible to guess what an intelligence that is greater than human and continually becoming greater will do. This conundrum has been likened to a dog trying to grasp human technology.

There are a couple of things we need to be clear about. First of all, there is no such thing as “after an intelligence explosion”. There is no reason to believe that the recursive increase in intelligence will ever cease. Moreover, for all we know, it is possible to access other dimensions or reconfigure reality to build intelligence that is so far beyond anything we can imagine that it ceases to be “intelligence” and becomes something else entirely. And that may be only the beginning. There is no “other side” of a technological singularity.

Second, we do not really know what is possible. I tend to believe that faster than light travel, time travel, dimensional shifting, reactionless drives, and restructuring reality at a fundamental level will always be impossible. But I do not know this. These assumptions are based on a sort of naïve instinct for what nature will and will not allow. I may be wrong.

If I had to guess, I would say that the upper limit on computer hardware is something like a planet-sized brain with components that are as small as a few atoms. However, those components could maximize quantum computation. There may be issues of heat dissipation, so the brain would probably be mostly on the outer layer of the planet and may even be driven by natural radiation at its core. However, that is a really, really big brain.

It has occurred to me that earth’s moon could be “compuformed” into such a brain, but the moon is 239,000 miles from earth, which means that any information going to or coming from the moon would take 1.3 seconds. That is much too slow for many purposes. In a recent essay, I discussed moving all human infrastructure underground. It is completely possible that nearly all of earth’s subterranean crust that is not human infrastructure could be transformed into computer matter. When ordinary matter is converted into computer matter, it is sometimes called computronium. Nearly all of the earth’s subterranean crust that is not being used for other purposes could be transformed into computronium.  Processing in this computronium could be sufficiently decentralized that the conversion of computronium back into other materials that may be needed for other projects would not present any complications.

That would probably be enough computer power for anything humans could dream of. It may be enough computer power for anything AI could dream up. Biological humans could have tiny robots that swim through their bloodstreams and keep them young forever. That is a given. They could have direct brain virtual reality simulations of anything they can imagine. AI would be so powerful that it could calculate and present humans with their deepest desires much more vividly than anything they could experience in real life. That would be difficult to come to terms with. What would happen to any person who experiences his deepest desires…desires that he may or may not have been aware of?

Indefinite youthful lifespans and perfect vivid fantasies are just the obvious things. These computer systems, aided by the best possible equipment, will probe the universe in depth and at scale to figure out the true theory of everything. We will quickly understand everything that is and everything that could be. We will probably determine the nature of consciousness.

That is where it gets a bit sticky. When we have guessed the nature of consciousness, I suspect we will be forced to realize there is a God (my personal prejudice). Will that lead to a super-high-tech, futuristic, religious revival? What happens when people that can live indefinitely and experience any fantasy in vivid detail realize they are being watched over by God?

I am getting ahead of myself. People will probably not stay on earth. They will probably migrate to the stars. In doing so, they will take all their technology with them. There has been a lot of speculation about humans building giant structures like matryoshka brains that enclose entire stars. That makes no sense. Why do that? A computer big enough to think every thought anything could ever want to think would likely be no larger than a building…or perhaps a mountain. A planet sized computer would be overkill. A star-sized computer would just be a vanity project.

As I speculated in an earlier essay, the consciousness of people who live indefinitely will probably expand until it can reach beyond the boundaries of their bodies. These consciousnesses, unconstrained by the laws of physics, will span the universe, reconfigure it and rein it in. They will remake the universe into the kingdom of heaven (another personal prejudice).

That is what I think will happen, but if I am like practically everyone that has lived since the dawn of time, I am probably wrong. Probably, AI will take us places and in ways that no one can anticipate. Or maybe it will be our doom. Or maybe space aliens will step in. Or maybe Jesus will return. Maybe it will turn out that the universe is a giant omelet just flipped on some cosmic burner. Hey, who wrote this script anyhow?

Well, see you on the other side. Oh wait…there is no other side.

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Underground Infrastructure

5 Feb

In a recent interview with John Koetsier, Peter Diamandis described the future of robotics in a poetic manner that, while not very precise, perfectly captures the sentiment: “Robots building robots all the way down.”

Very soon, robots will be able to replace every human in every job, regardless of the difficulty or skill level. Realizing this got me started on a chain of reasoning that began with the economic effect of robots replacing  humans and led me into a visualization of a future society in which it makes sense to move all infrastructure underground. The best way to explain my conception of this infrastructure is to take the reader through my actual chain of reasoning.

As I discussed in a previous essay, Elon Musk is expected to be a leader in the robotics industry. He is developing humanoid robots that he eventually intends to mass produce and distribute. More importantly, he plans to start using these robots in his own factories.

When this happens, his cost of manufacturing will begin to converge to zero. However, the amount by which the cost can drop will be limited by how cheaply Musk can obtain power and resources that currently come from outside of his manufacturing loop.

To reduce these costs, Musk could buy or build mines, steel mills and power plants and use robotic labor in them. After that, the only remaining cost would be moving parts and materials and transmitting energy between his facilities using existing transportation such as trucks, ships, trains and airplanes which must all move through existing infrastructure such as roads, waterways, railroad tracks and the air and whatever power cables that are available.

However, there is a way Musk could eliminate even these costs, He could tunnel underneath the earth and move parts, materials and energy between his facilities through an elaborate subway system. Interestingly, Musk is developing his “Boring Company” and preparing to build underground hyperloops.

If Musk owned manufacturing plants, power plants and facilities for securing raw materials, and was able to convey parts, raw materials and energy through his own subway system, his cost of production for everything he manufactures, including robots, would be zero.

Of course, there are other considerations. If Musk wishes to dig tunnels underneath land he does not own, he will need to get permission. He will certainly be charged for that permission. Also, he will undoubtedly be charged for licenses and permits. The government always gets its cut. However, the real cost of manufacturing would be zero.

Elon Musk will not be the only one doing this. Governments and other manufacturers will latch onto this paradigm and begin tunneling like crazy. They will employ immense robotic boring machines that are built, operated, and maintained by other robots.

Factories can also be moved underground and integrated with this subway system. Currently, factories and other industrial infrastructure are housed in large, sprawling facilities, ideally located in areas that humans do not care to inhabit.

Eventually, it will make sense to move factories and other purely industrial infrastructure underground. Instead of being large sprawling complexes they will take on a linear form that stretches for miles and can be located almost anywhere. They will take on a linear form because that is the simplest and safest kind of structure to build underground.

If there is a need for more lateral movement than is possible with long tubes, several parallel  underground tubes could be connected.

These facilities will need to be only about 100 feet below the surface. Therefore, the heat associated with deep mines will not be an issue. The Alaskan Way Viaduct replacement tunnel in Seattle Washington is only about 100 feet below ground.

All of this underground infrastructure will require a power source. I have come to believe that the terrestrial energy source of the future will be deep geothermal of the sort being developed by Quaise Energy. Deep geothermal energy will be virtually free if it can be developed, and it will probably be the cleanest and least intrusive energy source available. Currently, Quaise Energy anticipates above-ground facilities with wells that reach twelve miles into the earth.

However, these facilities could also be located underground in long tubes similar to the previously described industrial infrastructure. This works out perfectly, since deep geothermal energy is also underground but just a whole lot further down.

Another element of our infrastructure, the transport of waste, could also be moved underground. When people discard refuse, it will go down into the earth through tubes and elevators where it will be whisked away by underground robotic systems that take anything and everything to underground recovery, sorting and recycling stations. People will never need to think about what they discard. It will all be taken away and maximized for its potential.

Eventually, all of the purely functional infrastructure of society will be moved underground and only elegant human facilities will be located above ground.

This will give civilization an aesthetic that is reminiscent of a beautiful woman with perfect skin which, nevertheless, conceals all the unattractive blood vessels and organs that make her beauty possible.

A popular science fiction trope involves people living underground. As one member of EV, spud100, points out, this is primarily a plot device. In the future, all people that remain on earth—I anticipate considerable migration into space—will live in elegant aboveground facilities that rival the visions of ancient prophets.

These facilities will be cleaned and maintained continuously by a tireless robotic work force.

Only infrastructure will be underground. People will live effortlessly in this unimaginable opulence while all the muscle of civilization is conspicuously out of sight.

(All the images used in this essay were generated and edited using Midjourney, Bing’s Dall-E 3, and Photoshop. Some of the images, such as the woman dropping an item into a recycling receptacle, are composites that required considerable manipulation.)

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