Artificial Manipulation

Humans already know what to do. They just don't feel like it.

Artificial intelligence promises to make intelligence cheap and abundant. This is a big deal. It will help us diagnose diseases, design materials, write code, manage logistics, tutor children, and automate many tasks that once required expensive human expertise.

But cheap intelligence does not solve humanity’s basic problem.

The basic problem is not a lack of intelligence. In many cases, we already know what to do. We know how to reduce traffic. We know how to improve public health. We know how to build more housing. We know how to make organizations more efficient. We know how to prevent many avoidable disasters.

The problem is that knowing what to do is not the same as getting people to do it.

Human civilization is not limited only by intelligence. It is limited by coordination, trust, legitimacy, incentives, and consent. AI may help with some of these. But in many cases, it will intensify the underlying challenge.

Consider autonomous vehicles.

If every car became “super-intelligent,” traffic would not disappear. Each vehicle might drive better than a human. It might brake faster, choose routes more efficiently, avoid accidents, and react to its surroundings with perfect attention. But if each car is still optimizing for its own passenger, traffic remains a coordination problem.

Every vehicle wants to move forward. Every passenger wants the fastest route. Every local optimization creates effects elsewhere. A car that cuts through a side street may save its passenger three minutes while slowing down an entire neighborhood. A vehicle that inches forward at an intersection may behave rationally from its own perspective while contributing to gridlock for everyone else.

Traffic is not caused merely by drivers' lack of intelligence. It is caused by too many agents pursuing overlapping goals in shared space.

Now imagine a different system. All cars are connected. Their movements are coordinated. A central or distributed traffic intelligence assigns speed, spacing, routes, and right-of-way. Some cars are made to slow down even when they could go faster. Some passengers are routed away from the shortest path. Some trips are delayed so the whole system can flow better.

That might actually solve traffic. But would humans accept it?

The key improvement would not come from making every vehicle smarter. It would come from making every vehicle submit to a larger coordination system. The intelligence matters, but getting humans to submit to it matters more.

Autonomous vehicles illustrate a dynamic that recurs in many other human affairs. We already have enough intelligence to solve many of our stated problems. What we lack is agreement on who gets to decide, who has to sacrifice, who gets priority, and what happens to those who refuse. AI does not eliminate those questions. It sharpens them.

Most humans do not want to be optimized. They want to be respected, consulted, flattered, protected, or left alone. They want better outcomes, but not necessarily the discipline required to produce them. They want less traffic, but not to be told when they can drive. They want cheaper housing, but not always in their neighborhood. They want better public health and education, but not always the rules that make it possible. They want more efficient organizations, but not the loss of status, autonomy, or ambiguity that efficiency often requires.

This is why the promise of AI is both thrilling and terrifying. Its real advantage may not be that it knows more than we do. Its advantage may be that it can coordinate, persuade, monitor, and enforce behavior at a scale no human institution ever could.

Does that sound like a nightmare or a dream?

It depends on who controls the system, whose preferences count, whose sacrifices are considered acceptable, and what happens to those who refuse.

AI may make intelligence abundant. But the scarce resource is consensus.

Have a great week.

Best,

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P.S.

I discussed human intelligence and coordination in my recent podcast with Jacob Shapiro. You can find the full conversation on Spotify, Apple Podcasts, YouTube, and other platforms.

Timour Kosters just published a piece about what AI-powered coordination could look like in practice. Money quote:

The internet made it easier for people to find one another, signal their preferences, and form temporary swarms. But it did not make it much easier to govern, compromise, allocate sacrifice, or act together over time. AI agents may help. They may give groups better memory, better interfaces, and better follow-through.

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