AI has potential to unleash massive growth and development on a never-before-seen global scale. Standards of living 1000x the Status Quo

But some researchers think this is only the beginning — that AI won’t just make a few techies wildly rich, the way social networking, smartphones, and personal computers did before. Believers in a growth explosion argue that AI is set to make society much, much richer by causing economic growth at a scale it has never experienced before. In 2020, the AI researcher Ajeya Cotra at grant maker Open Philanthropy released a report arguing that AI powerful enough to drive a surge in economic growth to 20 to 30 percent a year is coming, and more likely than not will emerge before 2100. The following year, her colleague Tom Davidson conducted a more in-depth investigation of the potential for AI to supercharge growth and concluded that per capita economic growth rates as high as 30 percent a year resulting from AI are plausible this century. This is an extremely “big if true” claim. Since good record-keeping began shortly after World War II, the US has averaged 3.2 percent economic growth per year. Since 2000, growth has been much more anemic, averaging 2.2 percent. Per capita growth — which is affected by population changes as well as economic ones — has been lower still. Nowhere before in history — not in England during the Industrial Revolution, not in Japan during its “income doubling” period in the 1960s, not in China in recent decades — has sustained growth on the scale of 20 to 30 percent per year happened. To put that number into perspective, 30 percent growth implies that the economy would double in size every 2.5 years or so. (Based on current growth levels, the US economy won’t double for 35 years.) It gets even more impressive when you take a longer view. Northwestern economist Ben Jones has noted the typical American today is about 100 times richer than humans were when economic growth began and we were all living at the edge of starvation. In a system of 30 percent growth per capita, in 25 years we’d be 1,000 times richer than we are now. Imagine everything humans have achieved since the days when we lived in caves: wheels, writing, bronze and iron smelting, pyramids and the Great Wall, ocean-traversing ships, mechanical reaping, railroads, telegraphy, electricity, photography, film, recorded music, laundry machines, television, the internet, cellphones. Now imagine accomplishing 10 times all that — in just a quarter century. This is a very, very, very strange world we’re contemplating. It’s strange enough that it’s fair to wonder whether it’s even possible. Personally, 30 percent growth is so far outside human experience to date that I have trouble even imagining what it might look like. AI could be just another useful technology, akin to a washing machine. In this view, it makes our lives a little better, like most technological improvements. But AI could also be something else entirely that would upend the assumptions we’ve used to understand the world around us for centuries. The basic case for a growth explosion In his 2021 report, Davidson lays out three general arguments for why such a dramatic explosion in economic growth might be possible. The first argument is historic. In an earlier report for Open Philanthropy, researcher David Roodman looked at the trajectory of the world economy in the very, very long run — all the way back to 10,000 BCE. He concluded that the pattern of economic growth, examined through this very wide lens, is superexponential. Exponential growth means the economy grows by a steady, compounding rate every year — 2 or 3 percent, say — like interest in your savings account. Superexponential growth means that the growth rate is increasing over time. That, Roodman concludes, is what has in fact happened. Roodman emphasizes that you should take this with several grains of salt. It’s not like we have good data on what the world economy was like in 10,000 BCE. But we do know, with a high degree of confidence, that economic growth was very slow for a very long time and then accelerated a great deal with the onset of the Industrial Revolution. That fits a superexponential story. And a superexponential story makes future increases in the rate of economic growth look very plausible. “Some people have the prior of ‘This is crazy’” when thinking about superexponential growth, Davidson told me in an interview. “And other people have the prior of ‘This has happened throughout history.’” Davidson’s second argument relies on a popular set of theories within economics for why growth has accelerated over the very long run. The short answer these theories give is that population growth enabled economic growth to speed up. “A long time ago, the world population was relatively small and the productivity of this population at producing ideas was extremely low,” Stanford economist Chad Jones explains in a 2001 paper. “Once an idea was discovered, however, consumption and fertility rose, producing a rise in population growth. More people were then available to find new ideas, and the next new idea was discovered more quickly.” Or, as Davidson summarizes: “more ideas → better farming techniques (or other innovations) → more food → more people → more ideas → ...” That feedback loop leads not just to economic growth but to accelerating economic growth. This type of theory also explains why growth has slowed down in rich countries compared to where it was in the 19th century. In a process known as the “demographic transition,” people in richer countries tend to choose, for a variety of reasons, to have fewer children. This breaks the feedback loop because more ideas leading to more food no longer necessarily leads to more people. But now, imagine that researchers are able to build two-legged robots, with hands and arms and everything, capable of performing both any physical task a human can and anything on a computer a human can. We’re talking full Blade Runner or Battlestar Galactica here (hopefully minus the rebellion). We would be able to build these robots in a much shorter time than the decades it takes to birth, raise, and educate a human worker, and at less expense. So we’d achieve much faster population growth (or at least growth in the population of working robots) and bring back the feedback loop that caused economic growth to accelerate a few centuries ago. The fast-growing population of robots would be able to come up with, and implement, enough economically useful ideas to get the economy going faster and faster and faster. The third argument for transformative growth is based on the conventional model that economists use to study growth in the medium to long run. The classic way of looking at economic growth is sometimes called the Solow-Swan model, after Robert Solow and Trevor Swan, who wrote separate papers developing it in 1956. (Solow died recently, in December 2023.) In this model, the size of the economy — the amount of goods and services being produced in a given year — depends on the amount of labor, the amount of capital, and a measure of productivity. Capital here specifically means tools and property that can be used to make stuff: machines in factories, ovens and dishwashers at restaurants, trademarks and patents that represent ideas you can use to make stuff. One of the most important aspects of this model is that there are diminishing returns to additional labor and additional capital. That’s because you need both to do anything useful. If you have a coffee shop with five baristas and no espresso machines, the first espresso machine is going to make them vastly more productive. But the 200th machine will do nothing because five baristas can’t run 200 machines simultaneously. Similarly, if you have 200 machines and no baristas, the first barista you hire is going to be enormously valuable. The 1,000th will be useless. Put human-level AI into this model and a bunch of things can happen that make superexponential growth look likely. AI could, for instance, make returns to capital constant, rather than diminishing. That’s because you can always invest in capital (namely, robots or other AI) instead of labor and get the same effect as if you’d hired someone. You can buy a robo-barista instead, and make all those espresso machines hum. That makes the labor component of growth literally irrelevant. Growth will explode. (Good.) But because demand for human labor will plunge to zero, most of humanity will be jobless and likely not share in that growth. (Bad.) Economists Philip Trammell and Anton Korinek have reviewed some 25 ways of plugging AI into this standard model, as well as more recent “endogenous” models that treat technical change differently. Many of these approaches result in a prediction of superexponential growth. Advanced AI could automate research, fueling accelerating growth in productivity. It could increase the rate of return on investment in capital by making capital more useful (you have great robots now!), which spurs people to save more, which leads to more investment in capital, and so on. The exact mechanism varies based on the model and scenario, but it’s not hard to get the models to spit out a substantial acceleration in economic growth. The models, of course, are just models, and inserting AI puts them “out of sample”: They’re designed for scenarios like the present, where human-level automation does not exist. But they’re also not just models: They express coherent stories and processes through which explosive growth could happen. It’s not hard to see how automating research, for instance, could lead to technology improving rapidly, with massive economic consequences. “There is no shortage of mechanisms through which advances in automation could have transformative growth consequences,” Trammell and Korinek conclude, “once we allow ourselves to look for them.”