This piece originally appeared in The Republic.
That technological sophistication and geopolitical prowess go together is undisputed, but how exactly are they related? A common answer treats the journey from technology to great-power status as a sprint: the race is to the swift, who pioneer the development of new technologies to surge ahead of other nations in a few leading industries. As political scientist Daniel Drezner summarizes it, “Historically, a great power has acquired hegemon status through a near-monopoly on innovation in leading sectors.”
This view, argues Jeffrey Ding in Technology and the Rise of Great Powers, is wrong. The relationship is more akin to a marathon, in which the race is to the patient and adaptive, who successfully incorporate new technologies throughout the economy. In opposition to the conventional “leading sectors” theory, Ding offers his “GPT diffusion” theory, according to which it is a nation’s widespread adoption of general-purpose technologies (GPTs), rather than the rapid development of a few prominent sectors enabled by new technologies, that drives the rise and fall of great powers. GPTs are those fundamental breakthrough technologies that have wide applicability across industries, the potential for continual refinement, and complementarities with other more specific technologies. Think of electricity or the steam engine—or today, artificial intelligence.
Ding, a political scientist at George Washington University, notes several differences between the leading sectors theory and the GPT diffusion theory. The former sees new technologies’ greatest impact in early stages, soon after invention; the latter sees technologies’ impact as gradually playing out over decades. The former sees a nation’s economic leadership as resulting from the establishment of a monopoly in a few core sectors; the latter emphasizes the widespread adoption of a GPT across many sectors. The former suggests supporting basic research and the cultivation of individual genius to achieve breakthrough discoveries; the latter highlights the importance of broad educational attainment, especially in engineering.
The question of which theory is correct is not of mere academic or historical interest, but ultimately a matter of the greatest significance on the world stage. If Ding is right, statesmen and policymakers seeking to maintain or boost their economic standing vis-à-vis other nations should focus less on “eureka moments” and the hype of scientific discovery, and more on “GPT skill infrastructure”—the broad base of education and institutions that can accelerate the economy-wide adoption of a GPT.
Determining which view is correct is partly a historical question, and perhaps the most persuasive parts of the book are Ding’s studies of the past three industrial revolutions. In the first industrial revolution, occurring in Britain from roughly 1780 to 1840, total factor productivity—the ultimate driver of economic growth—and industrial output didn’t begin their dramatic rise until decades after the emergence of such inventions as the spinning jenny and the water frame. Therefore, producing a brilliant inventor such as James Watt, pioneering a new device or technique, and plugging it into a few important industries such as cotton textiles or iron cannot account for Britain’s rise to industrial giant status. Instead, Ding argues, rising productivity and output came about more gradually through broad advances such as the factory system and mechanization and through upskilling the nation’s mechanical and engineering talent. Together, these allowed Britain to overtake France and the Netherlands as Europe’s greatest power.
Ding argues for a similar dynamic in the second industrial revolution, occurring in America from 1870 to 1914. The secret to America’s rise and its eventual overtaking of Britain and Germany was the gradual transformation of the whole economy through the adoption of interchangeable parts, electrification, chemicalization, and the internal combustion engine—not the initial invention and prioritization of particular industries such as steel and automobiles.
A chapter on the third industrial revolution, marked by Japan’s attempt to surpass America, is particularly effective for Ding’s argument because, unlike in the previous industrial revolutions, a great-power transition did not occur. In the 1980s, Japan was the leader in new information and communications technologies, and excelled in hot new sectors such as semiconductors, computer hardware, and consumer electronics. So why did Japan not become the next techno-hegemon? Ding’s GPT diffusion theory offers an answer: America was better able to incorporate computers widely into the workforce and thereby raise productivity, and we had the requisite skill infrastructure in the form of a broad talent base of software engineers and computer scientists. Japan knew how to innovate, but not how to capitalize on its own accomplishments, and so failed to achieve the great-power transition that so many expected, or feared, in the 1990s.
Technology and the Rise of Great Powers concludes with a discussion of the fourth industrial revolution and U.S.-China competition today. Here, it becomes clear that the stakes of solving the puzzle of tech innovation versus diffusion could not be higher. Ding argues that leading policymakers and technologists in both the United States and China have “learned the wrong lessons from previous industrial revolutions.” Both see the competition as a scramble to make the next great discovery before the other side does—after that, they believe the hardest part is over. Hence the frequent talk of an “AI arms race” and the emphasis on beating the other nation to the creation of artificial general intelligence.
But if Ding is even partly right, then focusing on increasing federal support for R&D, creating novel technologies, and pushing back the frontier of scientific discovery will not ultimately determine which superpower dominates the 21st century. Instead, “the key driver of a possible U.S.-China economic power transition will be the relative success of these nations in diffusing AI throughout their economies over many decades.” Achieving—or preventing—a great-power transition will be less a matter of being the first to produce the next shiny gizmo and more akin to Max Weber’s “slow boring of hard boards.” Technological dominance is, to borrow from the title of Michael Pillsbury’s book on U.S.-China competition, a “hundred-year marathon.” Technology and the Rise of Great Powers offers an important challenge to a prevalent model of technological leadership, and deserves its own diffusion throughout the conversations of American policymakers.
