A couple of years ago, Vladimir Putin warned Russians that the country that led in technologies using artificial intelligence will dominate the globe. He was right to be worried. Russia is now a minor player, and the race seems now to be mainly between the United States and China. But don’t count out the European Union just yet; the EU is still a fifth of the world economy, and it has underappreciated strengths. Technological leadership will require big digital investments, rapid business process innovation, and efficient tax and transfer systems. China appears to have the edge in the first, the U.S. in the second, and Western Europe in the third. One out of three won’t do, and even two out three will not be enough; whoever does all three best will dominate the rest.

We are on the cusp of colossal changes. But you don’t have to take Mr. Putin’s word for it, nor mine. This is what Erik Brynjolfsson, director of the MIT Initiative on the Digital Economy and a serious student of the effects of digital technologies, says:

“This is a moment of choice and opportunity. It could be the best 10 years ahead of us that we have ever had in human history or one of the worst, because we have more power than we have ever had before.”

To understand why this is a special time, we need to know how this wave of technologies is different from the ones that came before and how it is the same. We need to know what these technologies mean for people and businesses. And we need to know what governments can do and what they’ve been doing. With my colleagues Wolfgang Fengler, Kenan Karakülah, and Ravtosh Bal, I have been trying to whittle the research of scholars such as David Autor, Erik Brynjolfsson, and Diego Comin down to its lessons for laymen. This blog utilizes the work to forecast trends during the next decade.

4 waves, 3 facts

It is useful to think of technical change as having come in four waves since the 1800s, brought about by a sequence of “general purpose technologies” (GPTs). GPTs are best described by economists as “changes that transform both household life and the ways in which firms conduct business.” The four most important GPTs of the last two centuries were the steam engine, electric power, information technology (IT), and artificial intelligence (AI).

All these GPTs inspired complementary innovations and changes in business processes. The robust and most relevant facts about technological progress have to do with its pace, prerequisites, and problems:

Technological change has been getting quicker. While the pace of invention may not have accelerated, the time between invention and implementation has been shrinking. While average implementation lags are difficult to measure precisely, it would not be a gross oversimplification to say that they have been cut in half with each GPT wave. Based on the evidence, the time between invention and widespread use was cut from about 80 years for the steam engine to 40 years for electricity, and then to about 20 years for IT (Figure 1). There are reasons to believe that the implementation lag for AI-related technologies will be about 10 years. With technological change speeding up and first-mover advantages as big as they have always been, the need for large and coordinated investments is growing.

Figure 1. Technology adoption lags have fallen a lot since the 1800s

Source: Comin and Mestieri (2017).

Leapfrogging is practically impossible. While a special purpose technology such as landline telephones can be skipped in favor of a new technology that does the same thing such as, say, mobile phones, it is difficult for countries to leapfrog over general purpose technologies. For a country to overtake another, it must first catch up. Technological advancement is a cumulative process. Business process innovations needed to utilize the steam engine were necessary for firms to take advantage of electric power. More obviously, electricity was a precondition for information technology. Regulations that facilitate or impede technical progress, education and infrastructure, and attitudes toward the social change that accompanies new technologies matter as much as the technologies, pointing to the need for complementary policies that shape the economy and society.

Automation is labor-share reducing, not labor displacing. While the most commonly expressed concern today is that the spread of artificial intelligence will replace workers with smart machines, the effects of earlier GPTs are better summarized as reducing the share of labor earnings in value added. But the evidence also suggests that since the 1970s, automation in relatively advanced economies has put pressure on labor earnings. Put another way, the concern should not be widespread unemployment but the fact that incomes are becoming increasingly skewed in favor of capital over labor. This means that countries that have efficient arrangements for addressing distributional concerns have an advantage over those that don’t.

Big money: Advantage China

Putin is not the first Russian leader to understand the importance of breakthrough general purpose technologies. A hundred years ago, Vladimir Lenin’s Communist Party invented the Five-Year Plan to exploit electric power. Indeed, it wouldn’t be an exaggeration to say that modern planning practices originated with Lenin’s plan for the electrification of the Soviet Union. To appreciate the importance of electrification, it is worth reading Lenin’s short Report on the Work of the Council of People’s Commissars. Here are extracts from that speech, delivered in 1920 to “stormy and prolonged applause”:

“You will hear the report of the State Electrification Commission, which was set up by the All-Russia Central Executive Committee of February 7, 1920. Communism is Soviet power plus the electrification of the whole country. We are weaker than capitalism, not only on the world scale, but also within the country. Only when the country has been electrified, and industry, agriculture and transport have been placed on the technical basis of modern large-scale industry, only then shall we be fully victorious. We have a plan which gives us estimates of materials and finances covering a long period, not less than a decade. We must fulfill this plan at all costs, and the period of its fulfillment must be reduced.”

Figure 2. China may already be spending more on R&D than the United States

Today, the most serious practitioner of Soviet-style planning is the Chinese Communist Party. In 2015, it announced the $1.68 trillion Made in China 2025 plan, to do with artificial intelligence what Lenin had done for electric power. The plan is to transform the Chinese economy and dominate global manufacturing by 2030. China has neither the entrepreneurial nimbleness of America nor the capable public finance systems of Western Europe, but it is putting a lot of money into digital dominance. The question is whether this will be enough.

The last two decades witnessed the rise of China as an economic power; the next 10 years will decide whether it will eventually become a superpower. For now, President Xi’s approach could be summed up much as Lenin’s strategy was in 1920: State capitalism is the People’s Party plus artificial intelligence.

Business practices: Advantage America

The story goes that in 2018, President Donald Trump complained to President Xi Jinping that Made in China 2025 was insulting to the U.S. because it aimed to make China the global leader in technology. Since then, there are no official references to it. No point taunting the world’s technology leader into doing more, the Chinese government reckons.

But the real advantage of the U.S. is that government exercises a lighter touch than in China or Europe, leading to shorter lags from invention to market and quicker adaptation by businesses so that productivity gains are realized more quickly than in competing countries. Notice the relatively rapid diffusion of computers—available for use simultaneously in all rich economies—in the U.S., as compared with Canada, Japan, Germany, and France (Figure 3).

Figure 3. Quicker diffusion of computers in the US than in Canada, Japan, and Western Europe

Sources: Historical Cross-Country Technology Adoption Dataset by Comin and Hobijn (2004) and the Maddison Project Database.

The regulatory, infrastructural, and cultural conditions that lead to quicker business process innovation require tight industry-academic linkages, a welcoming environment for high-skilled immigrants, sound product-market regulations, and sensible hiring and firing rules. These will be not easy for either China or Europe to institute, and the U.S. will have this edge for a while.

Ameliorative arrangements: Advantage Europe

While the United States is quick to innovate, Western Europe is intrinsically more equal. Take a look at both the diffusion and penetration of internet use plotted in Figure 4. Europe played catch-up between 1990 and 2010, but internet usage has been more widespread in every European country since then. Greater income inequality in the U.S. surely has something to do with this, but it would be even more worrying if it were also due to more unequal opportunity. There is growing evidence that this is the case, and growing concerns that these gaps will quickly widen as AI-based technologies spread across the economy.

Figure 4. Quicker diffusion of the Internet in the US, but lower penetration than in Europe

Source: World Bank’s World Development Indicators and the Maddison Project Database.

Since technological change will exacerbate inequality both of opportunities and outcomes, efficient redistribution will become more necessary during the next decade than it has been in the past. Europe would then have a big advantage: Market income inequality in all but five European countries is lower than the U.S. (Figure 5). After taxes and transfers, every European economy has a lower Gini coefficient than America’s.

Figure 5. European countries have the most redistributive tax and transfer systems

Source: Causa and Hermansen (2018).

What to watch for

People who make long-term economic forecasts have a tendency to focus on strengths: China can mobilize a lot of money so it will become a superpower, the U.S. has a good climate for business so it will continue to dominate the world economy, and Europe is more egalitarian so it’ll get more bang for the buck. But perhaps we should look instead at the willingness of economies to remedy their shortcomings. China has to find ways to encourage entrepreneurship and address the massive disparities in education and wealth. Europe has to mobilize large amounts of money and make it easier for investors anywhere to bring inventions to the Single Market. The United States just has to quickly figure out ways to restore competition in tech, finance, health, and public education, so its redistribution systems are not strained.