When we are amazed by the magic of a new software application, like ChatGPT, we should not be impressed by the machine, nor by the specific firm that offers the product, but by the enormous array of human brains that have been connected so that they can accomplish complex tasks together.

Brian Chau is writing a series of detailed posts arguing that the innovation curve for artificial intelligence may be tapering off, not accelerating. The curve may be s-shaped, starting with a long period of slow progress, followed by rapid breakthroughs that are now largely over, with another period of slow growth ahead.

Although his evidence seems robust, I cannot assess his thesis. What struck me as I read his analysis was the vast amount of coordinated human effort that produces something like ChatGPT.

AI requires hardware–not just the big servers that run the model, but also the components that connect to it, including my laptop, and its power cord, and the generator that supplies it with electricity. All hardware requires design, manufacture, raw materials, and transportation.

AI also involves software of many kinds, which requires vast amounts of human work. People need appropriate educations and training to do all the relevant tasks, from mining minerals to writing code. Information must be created and circulated, including information that is free and public rather than proprietary. And a whole range of businesses and other organizations (e.g., engineering schools) must be financed, managed, marketed, staffed, etc.

Prices play important roles in all of this. They are signals that create incentives. For instance, there is a market price for the kinds of data-processing required by AI, and as that price rises, people see that they can make money providing the service. But prices hardly ever suffice for coordinating large and complex systems.

For one thing, you can’t interpret a price signal without a lot of information. For instance, the starting salary of computer science majors is projected to fall by 4 percent this year. That is a price signal, but it’s confusing without more context. A prospective major would need to know what is causing this short-term shift in the average price of this category of labor.

Even when the message of a price signal is clear, you can’t act on it unless you have substantive knowledge of the topic. I am aware that certain kinds of software are in high demand, but I don’t know how to write modern code, so I couldn’t take advantage of the price (even if I wanted to). Many people who do know how to code were taught that skill, and teaching is a different form of communication from prices (even though most teachers are paid, and schools and colleges have market aspects).

Whether the results of all this human coordination are beneficial is a different question …

See also the design choice to make ChatGPT sound like a human ; the difference between human and artificial intelligence: relationships; artificial intelligence and problems of collective action.