There’s a big debate about whether AGI is actually possible (or moral, or a good idea) but I want to put that all aside for a moment. For the sake of argument, imagine that:
Computers will soon match—and exceed—the mental abilities of human beings across the board. In the same way that no human player can beat the best chess AIs, no human being will be smarter than the best AGIs. Deployment of AGIs will be ubiquitous and unconstrained by software limitations—in the same way that the vast majority of Americans have access to smartphones and web browsers today, the vast majority of Americans will have access to AGIs in the future. Efforts to legally safeguard employment in the face of AGI will all fail—no laws will be passed to ensure that, for example, your driver, lawyer, cook, doctor, or financial advisor must be a human being. AGIs and machines will be legally interchangeable with human workers across all occupations and sectors.
I believe global human employment would rise, not fall, with the development of AGI—as it has with all innovations and automation beforehand. There would be a massive reallocation of workers across sectors and companies, a destabilization of many industries, and a host of short-term losers, but on net, the effects would be extremely positive for economic output, growth, and employment.
Even in this scenario, which I have intentionally made as extreme as possible,
But I also want to constrain and contextualize the hype a little bit. The innovations in AI are tremendous and exciting, but I don’t yet believe they represent “the next industrial revolution” so much as the continuation of innovation and automation at the same pace it’s held since the start of the second industrial revolution in the 1870s. The car, the airplane, nuclear fission, the fax machine, the computer, the internet, smartphones—none of these technologies represented a permanent rise in the growth rate of global productivity, just further steps on the relatively constant rate of productivity growth that began just after America’s civil war.
America’s economy, like many in the world, has wallowed in an era of relative stagnation that began after the 2008 recession
and that stagnation is a large part of the reason why for the first time in modern history nearly half of Americans don’t earn more than their parents.
Humans Are Not Horses
Humans, however, aren’t like horses, for a few key reasons. The first is that the economy is just a social construct to produce the goods and services that humans deem valuable.
Second, humans are autonomous beings that demand items and independently produce items for their own benefit—left on their own, the majority of horses would just frolic in fields. The majority of humans are independently driven to produce far, far beyond what is necessary for basic survival.
These points are key—the economy is just a social construct to produce what humans find valuable, and humans autonomously choose to work when it benefits them.
The third key point is that there is no upper limit to the amount of value humans can derive from the economy.
The people reading this are statistically likely to be high-income American workers, among the richest people in history—if they wanted to, they could work 5-10 hours per week and still take home 2-3x more than the current median global income, which is many times higher than historical global income levels. They choose to keep working because they derive benefits from the extra income that affords them high-end cars, large houses, advanced medical care, international vacations, and more.
It’s also worth remembering that machines already have technologically exceeded human capabilities across a number of dimensions without causing structural unemployment. Try benching the 4,000lbs that a forklift can pick up if you want, it won’t end well. The key industries most subject to physical automation, like manufacturing, have seen steep declines in employment even as output massively increased.
However, and this is key, aggregate employment rose dramatically even as manufacturing employment fell.
That was propelled by the rapid increase in service-sector employment—cooks, teachers doctors, computer technicians, retail workers, lawyers, accountants, etc—from just about 60% of workers at the end of World War II to more than 90% of workers today.
Automation, in this case, did not eliminate the need for work but rather increased the complexity and quantity of production while changing the comparative advantages of human labor and machine “labor.” In other words, productivity growth does not reduce employment—it increases consumption and allows workers to move into more productive tasks, without eliminating jobs in aggregate. As a mental model, you can imagine it as a logistics supply chain—Automation of clothing manufacturing will increase demand for semiconductors, semiconductor manufacturers will need more designers, and those designers will need teachers, professors, and daycare providers to achieve their work, so employment in the service sector rises to support and enable advanced production in the manufacturing sector. As the output level and complexity of the economy increases, workers specialize further and further into narrower occupations but don’t stop working—and in fact tend to earn and consume more. Or for a more poignant and current example, automation of image generation will likely enable an increase in the production and consumption of more complex media—movies, video games, VR experiences, etc.
The key point is that some comparative advantage—the difference in relative costs, not absolute costs—must definitionally exist between human and machine labor.
Even in a situation where humans are less productive per hour worked than machines across all tasks, it increases economic output for humans and machines to specialize in the areas they are relatively most productive in and “trade” for the same reason it makes sense for countries or people who are less productive across the board to still work and trade with those who have an absolute advantage.
Moravec's paradox—what humans would call “higher reasoning” actually requires far less computational power than the sensory, motor, and perception skills that most able-bodied people take for granted.
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