What About The Horses?

And other responses to "AGI Will Not Make Labor Worthless"

In a previous post, I argued that AGI would not make human labor worthless.

One of the most common responses was to ask about the horses. Technology resulted in mass unemployment and population collapse for horses even though they must have had some comparative advantage with more advanced engines. Why couldn’t the same happen to humans? For example, here’s Grant Slatton on X or Gwern in the comments.

There are also responses from Zvi Mowshowitz and Matthew Barnett that basically agree with the literal claim of my post (AGI will not make human labor worthless) but contend that AGI may well make human labor worth less than the cost of our subsistence.

The following framework explains why horses suffered complete replacement by more advanced technology and why humans are unlikely to face the same fate due to artificial intelligence.

• Humans and AIs Aren't Perfect Substitutes but Horses and Engines Were

• Technological Growth and Capital Accumulation Will Raise Human Labor Productivity; Horses Can't Use Technology or Capital

• Humans Own AIs and Will Spend the Productivity Gains on Goods and Services that Humans Can Produce

Humans and AIs Aren’t Perfect Substitutes But Horses and Engines Were

Matthew Barnett builds a basic Cobb-Douglas production function model where advanced AI labor is a perfect substitute for human labor. That way, billions of additional AI agents can be modeled as a simple increase in the labor supply.

This is bad news for human wages. If you increase labor supply without increasing capital stocks or improving technology, wages fall because each extra unit of labor becomes less valuable (e.g “too many cooks in the kitchen”).

A massive expansion in labor supply would increase the return to capital, so the capital stock would grow, eventually bringing wages back to their previous levels, but growth in capital may be slow compared to AI labor growth, thus still leaving wages depressed for a long time.

Additionally, it may be that there are decreasing returns to scale on labor and capital combined, perhaps because e.g all the goods spots for factories are taken up leaving only less productive ones, so that even when the capital stock does expand, wages are left at lower levels.

Matthew’s model assumes AI labor will be a perfect substitute for human labor, but this is not the case in fact. It’s important to clarify here what “perfect substitute” means. It doesn’t mean that AI can do all the tasks a human can do. Or even that an AI can do everything a human can do better or cheaper. For one factor to be a perfect substitute for the other, there needs to be a constant exchange rate between the two factors across all tasks.

If AI can do the work of 10 human software engineers then, if it is a perfect substitute for labor, it also has to do the work of 10 mechanics and 10 piano teachers and 10 economists. If AIs have differing productivity advantages across tasks e.g they’re worth 1,000 software engineers but they’re only twice as good as human economists (wishful thinking) then they aren’t perfect substitutes for human labor.

Another way to get intuition for this is that the labor economics literature finds that high-skilled humans aren’t perfect substitutes for low-skilled humans. They have an elasticity of substitution just under 2, whereas perfect substitutes have an infinite elasticity of substitution. An elasticity of 1 is the Cobb-Douglas case where high and low skilled labor would enter as separate, complementary factors like Labor and Capital in Matthew’s example.

So if a human with a college degree is not a perfect substitute for a human without one, it seems unlikely that AI would be a perfect substitute for human labor.

Einstein and a dumb human are much more similar than AIs are to humans

In a similar vein, Moravec’s Paradox points out that many things which are hard for us, like multiplying 10 digit numbers, are trivial for computers while things which are trivial for us, like moving around in physical space, are very difficult for AIs. AIs and humans have different relative productivities and thus are not perfect substitutes.

When humans and AIs are imperfect substitutes, this means that an increase in the supply of AI labor unambiguously raises the physical marginal product of human labor, i.e humans produce more stuff when there are more AIs around. This is due to specialization. Because there are differing relative productivities, an increase in the supply of AI labor means that an extra human in some tasks can free up more AIs to specialize in what they’re best at.

However, this does not mean that human wages rise. Humans will be able to produce more goods, but it may be that AI automation makes the goods that humans can produce so abundant that the prices fall by more than our productivity rises.

This helps explain what happened to horses when cars were invented. First, horses and engines were very close to perfect substitutes. It’s not the case that engines are 100x better than horses at transportation but only twice as good at plowing. Engines are pretty much just 100x better than horses at all of their tasks, so horses' physical productivity didn’t increase. Second, the automation from engines made food and transportation so abundant that the price of these goods fell and horse’s constant productivity was no longer enough to pay for their own maintenance.

Technological Growth and Capital Accumulation Will Raise Human Labor Productivity; Horses Can’t Use Technology or Capital

Rising physical marginal product is not enough to guarantee high wages in the face of an AI boom, but there are other forces that grow alongside AI progress that will raise human wages.

Technological progress is probably the most important of these forces. Technological progress raises labor productivity. This is why farmers still make plenty of money even though the price of food has plummeted; technology allows them to produce so much more. And this is why horses didn’t fare as well; they can’t drive a tractor. AI will result in many technological advancements which make human labor more productive, just as tractors and airplanes and printers did in the past.

Capital accumulation will also raise wages. As I said in the previous section, capital accumulation eventually equalizes wages even when human labor faces competition from a perfect substitute. AI labor isn’t a perfect substitute for human labor, but both AI labor and human labor will be complementary to capital. An expansion in the AI labor supply will incentivize more investment into capital raising both human and AI productivities.

I pointed out in the second half of my original post that human wages have grown even as the effective supply of human labor has ballooned, cutting against the prediction of Matthew’s most basic Cobb-Douglas model. I claimed originally that this was due to comparative advantage between high and low-skilled humans, but that isn’t the main part of this story.

It’s mostly about technological progress and capital accumulation outpacing the growth in human labor supply. These moved fast enough that wages grew even though everyone was faced with competition from truly perfect substitutes (other humans). Thus, we should expect even better results when technological progress accelerates and we only have competition from partial substitutes.

Matthew agrees with this point in his piece “the introduction of AGI into the economy could drive innovation at an even faster pace—more than compensating for any negative impact the technology will have on wages.”

Humans Own AIs and Will Spend the Productivity Gains on Goods and Services That Humans can Produce

The previous two effects increased wages by raising the marginal productivity of human labor, but there are also positive wage effects coming from increased demand for products that humans can make.

AI automation will raise the aggregate productivity of the economy and thus the aggregate income of the economy. The owners of AIs, other means of production, and the consumers of cheap AI products will be the residual claimants of this extra income so the question is: what will they spend their money on?

If the income flows towards goods and services that humans can produce and especially those goods and services that humans have a comparative advantage in, then that extra demand will buoy the price of those goods and thus the wages of the people that produce them.

This didn’t happen for horses. The extra aggregate income from mechanized farming and transportation mostly flowed to consumer goods or other services that horses could not provide.

Humans have a big advantage in versatility and adaptability that will allow them to participate in the production of the goods and services that this new demand will flow to. Humans will be able to step up into many more levels of abstraction as AIs automate all of the tasks we used to do, just as we’ve done in the past. Once Deep Research automates grad students we can all be Raj Chetty, running a research lab or else we’ll all be CEOs running AI-staffed firms. We can invent new technologies, techniques, and tasks that let us profitably fit in to production processes that involve super-fast AIs just like we do with super-fast assembly line robots, Amazon warehouse drones, or more traditional supercomputers.

There are also Baumol's cost disease reasons that most of the extra money will flow to the least automated goods rather than the near-free AI services. Google automated many research tasks away and has massively increased the productivity of anyone on a computer but nobody spends a large percentage of those income gains on Google. Instead, we spend it on tipping servers at restaurants and healthcare.

Finally, human self-bias and zero-sum status seeking are likely to sustain an industry of “hand-made” luxury goods and services. There may also be significant legal barriers to AI participation in certain industries. To admit some intellectual malpractice, my bottom line is a future world where humans retain legitimate economic value beyond these parochial biases and legal protections, but I do think these factors will help raise human wages.

What Could Still Go Wrong? What Would Make This Argument Fail?

The argument is plausible and supported by history but it’s not a mathematical deduction. The key elements are relative productivity differences, technological improvements that increase labor productivity, and increased income generating demand for goods and services produced by humans.

So if AIs “raw intelligence” stagnated for some reason and we simultaneously made massive strides in robotics, that would be worrying because it would close that relative productivity gap and bring AIs closer to perfect substitutes with humans. A worst case scenario for humans would thus involve reasonably expensive robots of human-like intelligence which would substitute for many human jobs but not add much to other technological growth nor generate huge income gains. That seems like a possible future but not a likely one and not the future that most AI proponents have in mind.

We might also worry if AIs invent some task or good or service that can’t be produced by humans, can’t competed away to a low marginal cost, and can consume a large fraction of everyone’s income. Something like this might siphon away any wage benefits we get from the increased incomes from automation. One way this could happen is if everyone lived most of their lives in a virtual reality world and there were AI-produced status goods that occupied everyone’s desires. Our material needs would be satiated and other forms of additional consumption would take place in a virtual environment where AIs dominate. Again, this seems possible, but neither of these scenarios are close to the destitution by default scenarios that others imagine.

Higher wages are not always and everywhere guaranteed, but humans are not likely to face the same fate as horses. We are far from perfect substitutes for AIs which means we can specialize and trade with them, raising our productivity as the AI labor force multiplies. We can take advantage of technological growth and capital accumulation to raise our productivity further. We'll continue inventing new ways to profitably integrate with automated production processes as we have in the past. And we control the abundant wealth that AI automation will create and will funnel it into human pursuits.