AI at Your Side: Reading Classic Papers in Economics I: Why Prices Know More Than We Do: Hayek in the Age of AI

Before anything else, look at a pencil.

Milton Friedman, borrowing from Leonard Read’s 1958 essay I, Pencil, used to hold one up and make a simple point: nobody knows how to make it. Not really. The wood, the graphite, the rubber, the metal — each part comes from a different place, through chains of production no single mind could reconstruct. Thousands of people cooperate to produce it, and no one is in charge.

That simple observation is the starting point of Friedrich Hayek’s 1945 paper, The Use of Knowledge in Society. It is one of the most cited and least understood papers in economics.

The slogan is familiar: knowledge is dispersed, prices transmit information, markets coordinate.

The problem is that slogans are cheap. Understanding is not.

Hayek’s real move is subtler and more uncomfortable. Instead of solving the problem of allocating resources given “the data,” he questions the premise that such data exist in any centralized, usable form. The relevant knowledge in an economy is fragmented, local, often tacit, and constantly changing. It lives in the heads of individuals, embedded in context, frequently not even articulable. In Hayek’s own words, it exists “solely as the dispersed bits of incomplete and frequently contradictory knowledge which all the separate individuals possess.”

That is the problem.

Once you see it that way, prices are no longer just a clearing device. They are a communication system. Their function is not to tell us everything, but to tell us enough.

A coffee shop owner does not need to know whether a drought hit Brazil or a port shut down. She only needs to know that coffee has become more expensive. That signal is sufficient for her to adjust. Multiply that across thousands of decisions, and coordination emerges, not because anyone understands the whole, but because no one needs to.

This is Hayek’s claim: markets work not because they are efficient in some abstract sense because they use knowledge that cannot be centralized.

At this point, the standard comparison with central planning becomes almost trivial. The issue is not whether planners are intelligent. It is whether they can access, aggregate, and update the relevant knowledge fast enough. In many cases, the deeper question is whether that knowledge can be collected at all.

And here is where most readings of Hayek go wrong.

Hayek’s actual claim is harder than “markets are perfect.” Any alternative institution must be judged by its ability to use dispersed knowledge. That is a much higher bar.

You see the force of this immediately when prices are prevented from doing their job.

Take rent control. The intention is straightforward: make housing more affordable. But the instrument interferes with the signal. A rising rent is not just a burden — it is information. It tells us that demand exceeds supply.

Suppress the price, and you suppress the message.

The empirical literature is remarkably consistent on this. Rebecca Diamond, Tim McQuade, and Franklin Qian (2019) show that San Francisco’s rent control expansion led landlords to withdraw a significant fraction of rental units, ultimately pushing rents up. David Autor, Christopher Palmer, and Parag Pathak (2014) find that removing rent control in Cambridge increased property values broadly, including for units never controlled. Edward Glaeser and Erzo Luttmer (2003) show that rent control generates massive misallocation: people occupy the wrong apartments in the wrong places.

The findings are mechanical, and they replicate. The same pattern shows up across San Francisco, Cambridge, and New York, in studies separated by methods and by decades. When the price system is muted, coordination breaks down.

None of this implies that distribution does not matter. It implies that distribution should be addressed with instruments that do not destroy the informational role of prices. Transfers, not price controls. One instrument per objective.

Now, the interesting question, and the reason to revisit Hayek today, is whether AI changes any of this.

There is a tempting view: Hayek’s argument was a product of limited data and weak computation. Today, we collect information at massive scale and process it in real time. Perhaps the problem of dispersed knowledge has simply shrunk.

Hayek’s problem was never just computational. It was epistemic. It concerns what information exists in the first place, and in what form.

Much of the relevant knowledge in an economy is generated only in action. It is local, contextual, and often fleeting. A shopkeeper noticing a shift in demand, an engineer improvising a substitution, a worker adjusting effort in response to incentives: these are not always recorded, and when they are, they are often recorded too late.

AI can aggregate observed data extraordinarily well. What it cannot do, at least not in any general way, is replace the process through which much of that knowledge is created.

So the boundary shifts. In some domains, coordination can be more centralized than before. In others, Hayek’s argument becomes even stronger. What emerges is a hybrid economy, with different coordination mechanisms operating in parallel and the boundary between centralization and decentralization shifting case by case.

That is the real update.

There is also a deeper misunderstanding worth clearing up.

Students often misread Hayek’s argument as requiring prices to be “right.” All it requires is that prices convey information.

The stronger version of the claim goes one step further, and this is where the argument becomes non-trivial. Prices do not need to be general equilibrium prices to generate coordination. They only need to move in the right direction and be locally informative.

Think of the economy as a process, not a solution. At any point in time, prices are “wrong” in the sense that they do not clear all markets simultaneously. But they still contain signals about relative scarcity. When a price rises, even if it overshoots, it pushes behavior in the correct direction: it induces substitution away from the good, encourages supply responses, and triggers search for alternatives. These adjustments do not require that the price be exactly right, only that it not be completely disconnected from underlying conditions.

In that sense, prices work like gradients rather than solutions. They guide decentralized adjustments without requiring global consistency at every moment. In this Hayekian sense, efficiency is the property of a process that uses dispersed information to move the system in the right direction over time.

This is exactly the same logic behind the efficient-markets intuition in finance. Efficiency does not mean prices are always correct. It means that there is no systematic free arbitrage. Prices can be volatile, even wrong in levels, and still perform their informational role.

That distinction matters. It is why the presence of bubbles does not invalidate Hayek any more than it invalidates finance theory.

And it also clarifies why suppressing price movements is so damaging. We never had a perfectly correct signal. What we lose, when prices are suppressed, is the direction of adjustment itself.

So where does this leave us?

Hayek’s insight is not that markets are optimal. It is that coordination in a complex economy depends on institutions that can make use of dispersed knowledge. Prices happen to be extraordinarily effective at doing this.

The problem persists. AI becomes one more participant in the system that handles it.

How to Read This Series

This is the first of a series of thirty papers to be read alongside the book AI at Your Side: The Student’s Guide to Smarter Learning, by Sebastian Galiani and Raul A. Sosa, forthcoming at Oxford University Press. The goal is to read each one slowly and carefully, in the way these classics deserve to be read, rather than rush through a syllabus.

Each paper will be approached in the same way: as something to work through, step by step.

The worst way to read Hayek today is to ask an AI for a summary. You will get a polished version of something you already knew, and mistake the fluency for understanding.

The only way to understand a paper like this is to reconstruct the argument yourself, apply it, and push against it.

AI can help, but only if it is used as a sparring partner.

That is the discipline this series is trying to build.

Exercises

1. Reconstruction (no AI).
   In your own words, explain why Hayek thinks the “data” of the economy do not exist in a centralized form. Be precise. Avoid slogans.

2. Prices without equilibrium.
   Consider a market where demand suddenly increases and prices rise sharply, overshooting the eventual equilibrium.
   What information is still conveyed by the price change?
   What adjustments does it trigger?
   In what sense can this still be “efficient” in Hayek’s sense?

3. Application.
   Take both policies: rent control and housing vouchers.
   Using Hayek’s framework, describe what information each policy preserves or destroys, and predict the behavioral responses.

4. AI challenge.
   Ask an AI: “Does large-scale data and machine learning invalidate Hayek’s argument about dispersed knowledge?”
   Then write a one-paragraph rebuttal to its answer.

References

David H. Autor, Christopher J. Palmer, and Parag A. Pathak (2014). “Housing Market Spillovers: Evidence from the End of Rent Control in Cambridge, Massachusetts.” Journal of Political Economy 122(3): 661–717.

Rebecca Diamond, Tim McQuade, and Franklin Qian (2019). “The Effects of Rent Control Expansion on Tenants, Landlords, and Inequality: Evidence from San Francisco.” American Economic Review 109(9): 3365–3394.

Milton Friedman (1980). “The Power of the Market.” Free to Choose, Episode 1. PBS.

Edward L. Glaeser and Erzo F. P. Luttmer (2003). “The Misallocation of Housing under Rent Control.” American Economic Review 93(4): 1027–1046.

Friedrich A. Hayek (1945). “The Use of Knowledge in Society.” American Economic Review 35(4): 519–530.

Leonard E. Read (1958). “I, Pencil: My Family Tree as Told to Leonard E. Read.” The Freeman, December 1958.

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*** Disclaimer: I used ChatGPT-5.2. as an editorial and language-refinement tool. The ideas and arguments are entirely my own, and I take full responsibility for them.