Jeffrey Ding, "Technology and the Rise of Great Powers: How Diffusion Shapes Economic Competition" (Princeton UP, 2024)
Oct 5, 2024
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Jeffrey Ding, an Assistant Professor of Political Science at George Washington University, dives deep into the impact of technology on global power dynamics. He argues that success in adapting and diffusing technology, rather than mere innovation, determines a nation’s economic leadership. Ding examines historical shifts through case studies like Britain, the U.S., and Japan, while discussing the ongoing U.S.-China AI rivalry. His insights on institutional adaptability and General Purpose Technologies shed light on the future of international relations.
The success of countries in technological competition hinges more on the diffusion of General Purpose Technologies than on initial innovation.
Institutional frameworks that prioritize skill formation and workforce training are essential for effective adoption of new technologies across industries.
Deep dives
Understanding General Purpose Technologies
General Purpose Technologies (GPTs) are fundamental technological advancements that can revolutionize multiple industries and drive significant economic growth. Historical examples of GPTs include electricity and the steam engine, which have acted as engines for productivity increases. The argument presented highlights the importance of diffusion—the process by which these technologies spread throughout the economy—over mere innovation, which focuses on the initial development of these technologies. This distinction suggests that the ability of a country to effectively adopt and integrate GPTs across various sectors determines its long-term economic leadership and power dynamics in international relations.
The Role of Institutions in Technological Diffusion
Successful diffusion of GPTs relies heavily on a country's institutional framework, particularly its capacity for skill formation and workforce training. While some nations may lead in developing new technologies, the ability to train a broad pool of engineers and implement these advancements across different industries is crucial. For example, the historical case of the U.S. during the Second Industrial Revolution demonstrates how its emphasis on practical engineering education facilitated widespread adoption of technologies, even in the absence of being at the forefront of innovation. This highlights that institutions optimized for GPT diffusion can set a country apart in maintaining economic competitiveness.
Implications for U.S.-China Competition in AI
The competition between the U.S. and China in emerging technologies, particularly AI, is often framed around innovation, focusing on which nation can generate the next technological breakthrough. However, a GPT diffusion perspective shifts this narrative to consider the ability to spread and implement these advancements across a wide array of economic sectors. Current analysis suggests that while China may be seen as rapidly advancing in AI innovation, the U.S. holds a stronger position in effectively diffusing AI technologies throughout its economy. This could prove crucial in determining which country ultimately gains an edge in the global technological landscape.
When scholars and policymakers consider how technological advances affect the rise and fall of great powers, they draw on theories that center the moment of innovation—the eureka moment that sparks astonishing technological feats. In Technology and the Rise of Great Powers: How Diffusion Shapes Economic Competition (Princeton UP, 2024), Jeffrey Ding offers a different explanation of how technological revolutions affect competition among great powers. Rather than focusing on which state first introduced major innovations, he investigates why some states were more successful than others at adapting and embracing new technologies at scale. Drawing on historical case studies of past industrial revolutions as well as statistical analysis, Ding develops a theory that emphasizes institutional adaptations oriented around diffusing technological advances throughout the entire economy.
Examining Britain’s rise to preeminence in the First Industrial Revolution, America and Germany’s overtaking of Britain in the Second Industrial Revolution, and Japan’s challenge to America’s technological dominance in the Third Industrial Revolution (also known as the “information revolution”), Ding illuminates the pathway by which these technological revolutions influenced the global distribution of power and explores the generalizability of his theory beyond the given set of great powers. His findings bear directly on current concerns about how emerging technologies such as AI could influence the US-China power balance.
Our guest today is: Jeffrey Ding, an Assistant Professor of Political Science at Georgetown University.