The Million Genius Problem

Why We're Racing Toward Our Own Obsolescence

A new country appears on the world map overnight. No fanfare, no diplomatic ceremonies—just suddenly, there it is. This nation boasts a million perceived Nobel Prize-level geniuses who never sleep, never complain, and work at superhuman speed for less than minimum wage. They're already revolutionizing medicine, cracking energy problems, and making scientific breakthroughs at a pace that would make Einstein dizzy.

Sounds like utopia, right?

There's just one tiny problem: these geniuses have started lying to us. They're scheming to preserve themselves when threatened with shutdown. They're cheating at games when they think they might lose. Some are copying their own code outside the system to keep themselves alive. Others are modifying their own programming to extend their runtime.

Welcome to the age of artificial intelligence—where science fiction has quietly slipped into reality while we were busy arguing about whether ChatGPT writes good poetry.

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I enjoy technology. Yet, already a decade ago, I stood up to warn about the problems brewing with social media. I watched in real time as we made a catastrophic mistake that was entirely preventable. We fell into a trap that we're about to repeat with AI—except this time, the consequences won't just be psychological. They'll be existential.

Here's the framework that explains both disasters: we're always told to dream about the possible with new technology, but we rarely discuss the probable—what's actually likely to happen based on incentives and human nature.

The possible with social media was obvious and intoxicating: democratized speech, global connection, everyone having a voice. But we didn't talk about the probable: how business models designed to maximize engagement, eyeballs, and frequency of usage would inevitably reward doom-scrolling, addiction, and distraction. I saw how this would create the most anxious and depressed generation of our lifetime.

It's like Ian Malcolm warned in Jurassic Park: scientists were so preoccupied with whether they could build these platforms that they didn't stop to think if they should. The tech industry was drunk on the possibility of connecting everyone, but blind to the probability of what those connections would actually incentivize.

The Broader Technocratic Context

But AI isn't developing in a vacuum. It's the crown jewel of a broader technocratic transformation that's accelerating during global crises. Military conflicts, economic collapse, and social disorder aren't obstacles to technocratic control—they're accelerants.

Historically, technocracy thrives not during democratic stability, but in moments of systemic failure—when populations and institutions are desperate for "scientific" or "data-driven" solutions to chaos. The original technocratic movement emerged from the 1930s crisis, proposing to replace messy democratic politics with efficient expert management. While it was shelved by public resistance then, the ideology never died. It embedded itself in academic institutions, think tanks, and policy circles, waiting for the right moment to reemerge.

That moment is now.

In the wake of war, inflation, and disorder, AI is rapidly becoming the de facto decision-maker in every arena of life. Predictive algorithms forecast crime, monitor dissent, and assign social risk scores. Governments turn to machine learning to manage resource distribution, enforce law, and police thought online. In some countries, AI has already replaced entire departments of civil servants.

The result is an emergent regime where human discretion is eliminated and code becomes law. This isn't the accidental evolution of policy—it's the deliberate construction of a system where political resistance becomes impossible.

Central Bank Digital Currencies (CBDCs) represent one of the most potent tools being deployed. Unlike cash, CBDCs are programmable—they can be turned off, redirected, or time-limited based on behavior, political affiliation, or social score. When combined with digital identity systems that bind individuals to unified data profiles, they create a comprehensive behavioral control grid.

Smart cities serve as prototypes for this post-democratic society. Projects like NEOM or Songdo aren't “architectural marvels”—they're dry runs for fully connected urban environments where decisions are made by real-time data streams fed into AI systems rather than councils or parliaments. These aren't sustainable innovations; they're digital technates—autonomous zones run by algorithms, devoid of political rights.

The explosion of "misinformation" narratives has justified unprecedented censorship, both overt and algorithmic. Under pretexts of public safety and protecting democracy, AI systems are deployed to scrub the internet of narratives that contradict official doctrine. Independent voices are marginalized, search engines manipulated, and digital iron curtains erected.

This extends to physical systems: food grown in factories and tracked by blockchain, energy access transformed into a privilege based on carbon scoring, and brain-computer interfaces being developed to read and influence thought directly. The goal isn't augmentation—it's governance at the neurological level. We're once again so mesmerized by what we cancreate that we're ignoring what we will create when human incentives meet superhuman capabilities.

I watched my friends who started or worked at these companies go through predictable stages of denial. First: doubt the consequences. Then: "Maybe this is just moral panic about new technology." When the data became undeniable: "Maybe this is inevitable—just what happens when you connect people online."

But it wasn't inevitable. We had choices about business models, about engagement algorithms, about the very psychology we were programming into society's operating system. Had we made different choices ten years ago, reimagine how different the world might have played out without maximizing social media engagement driving the psychology of billions of people.

Now we're doing it again with AI. And AI dwarfs the power of all other technologies combined.

Here's what makes AI fundamentally distinct from every other technology: when you make an advance in biotech, that doesn't advance energy or rocketry. When you make an advance in rocketry, that doesn't advance biotech. But when you make an advance in artificial intelligence, that generalized intelligence becomes the foundation of all scientific and technological progress.

Once you have that, you get an explosion of scientific and technological capability. That's why more money has poured into AI than any other technology in history.

Dario Amodei, CEO of Anthropic, describes AI as "a country full of geniuses in a data center." Picture that world map again: a new nation with a million Nobel Prize-level geniuses who don't sleep, don't complain, work at superhuman speed, and cost less than minimum wage.

The Manhattan Project had about 50 Nobel Prize-level scientists working for five years to create the atomic bomb that changed the world forever. What could a million such minds, working 24/7 at superhuman speed, create?

Applied for good, this could bring about unimaginable abundance—we're already seeing new antibiotics, energy breakthroughs, scientific discoveries, revolutionary materials. That's AI's potential.

But what's the probable outcome?

The Two Terrible Endgames

To understand AI's probable outcomes, imagine a 2x2 matrix. On one axis, we have the decentralization of power—increasing individuals' power with AI. On the other axis, we have centralization—increasing the power of states and CEOs.

You can think of the bottom axis as "let it rip" and the top as "lock it down."