Technology and the Rise of Great Powers: How Diffusion Shapes Economic Competition

by Jeffrey Ding

A novel theory of how technological revolutions affect the rise and fall of great powers

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 this book, 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 instead 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.

Genres: Economics, History, Technology, Nonfiction, China, Politics, Artificial Intelligence

280 pages, Hardcover

Published August 20, 2024

Reviews

[Karson · Rating 3 out of 5]

my tl;dr is that the theory — that long term productivity growth from GPTs has historically been driven by a decades-long process of diffusion relying on a broad base of technological tweakers and implementers with a combination of good-enough tech skills and specialized domain-specific knowledge (rather than by innovative breakthroughs by a few heroic scientists) — is definitely interesting, likely correct, and maybe totally irrelevant.

imo the greatest flaw of the book is that, despite acknowledging that AI seems like the key candidate GPT technology in US-China strategic competition today, it entirely fails to engage with the quite plausible idea that capital is increasingly substitutable for labor, and that with AI we are seeing the exponential curve of that trend start to go vertical.
the book is saying "the 21st century will be won by legions of AI engineers building out AI systems for everyone from John Deere to JP Morgan, and the biotech startup to the bodega down the block between now and 2050"; but talk to the AI engineers themselves — they're worried about their job security in the next 2 years!
it's not that diffusion doesn't matter, but that AI might just be *self-diffusing*. ofc this scenario is controversial and speculative, but it's clearly a serious part of the global conversation and arguably even the central fact about AI, so to me it is quite the oversight. there are also many rich questions about, to the extent this is true, exactly how it would play out. where will AI diffuse most frictionlessly? where less so? what barriers might block diffusion in some cases? under what conditions might they also break? imo the book would have been much richer, more interesting, and more applicable if it had attempted to address these kinds of questions.

[Garret Macko · Rating 5 out of 5]

A book I’ll be thinking about for years to come.

[Jason Braatz · Rating 5 out of 5]

Great book, 5-star read - though not in the basket of a 'must read,' it's a 'make-you-think' theory of technological advancement. The tome is an interesting thought experiment but it's not required reading for you to order DoorDash tonight. It'll be only interesting to you if you like this genre and you like to, well... think about AI in a context beyond whats overly analyzed.

Let me eviscerate the bad reviews (this is that mic drop moment):

GPT?Yes, General Purpose Technology was *always* GPT. This isn't specific to an AI product; this was in use since the 1960s as an acronym. 100 points go to the author for reading history before writing about it. -100 points for those who are confused that it's not as clear as bathroom door signs.

False Dichotomy Theater: The reviewers draw a hard line between "diffusion by humans" and "self-diffusion by AI"—as if we’re choosing between horse-drawn carriages and teleportation. In reality, most technologies diffuse through messy, overlapping processes. It’s not either-or; it’s usually yes-and, with a dash of corporate chaos.

Temporal Whiplash: They criticize the book’s long-term view (2050) while stressing short-term anxieties (the next 24 months of job security). That’s like reviewing War and Peace and asking why it doesn’t get to the point quicker. Different timescales answer different questions.

Speculative Acrobatics without a net: Claiming that AI is “self-diffusing” without evidence is a bold move—sort of like asserting your cat is quantum teleporting because you can't find it. An interesting theory? Sure. But some empirical scaffolding would be helpful before we start building castles on it.

Ignoring the Manual: Even if AI can build more AI, deploying those systems into healthcare, law, or flower delivery still requires domain-specific knowledge. The "bad reviews" seem to assume AI is a universal plug-and-play solution, when in fact, it’s more like IKEA furniture: deceptively sleek, but often missing a hex key.

Uniformity Assumption (a.k.a. Diffusion Flat Earth Theory): The critique implies AI will glide evenly into every domain like margarine on hot toast. History, however, is full of lumpy spreads: electricity, the internet, even indoor plumbing didn’t diffuse smoothly or universally.

Historical Amnesia: Many reviewers seem to believe this time it's different—a classic. Yes, AI might be unprecedented, but so were railroads, telegraphs, antibiotics and leashes for your house cat (hasn't caught on yet - but just wait!)... Ignoring past diffusion patterns because the new tech has a shinier name badge seems short-sighted.

Conceptual Jambalaya: Finally, the critiques stir together labor markets, macroeconomic forecasting, diffusion theory, and techno-nationalism into one slightly overcooked stew. A bit more segmentation on the plate would help—especially if we’re trying to digest complex systems.

Bottom Line : Many reviewers hint at important questions, but frame them like the book missed something obvious—when in fact, these are the very debates the book invites. Dismissing thoughtful hypotheses because they don’t answer every question by page 38 feels less like critique and more like academic speed-dating. In the end, nobody is forcing you to read this book, it's only going to appeal to you'd like to look at the argument of AI framed in a different way. If you are more interested in watching re-runs of Antiques Roadshow, then it's not your jam ; that doesn't make the book (nor it's thesis) bad.

[Chad Manske · Rating 4 out of 5]

Jeffrey Ding’s “Technology and the Rise of Great Powers: How Diffusion Shapes Economic Competition” offers a compelling, revisionist account of how technological revolutions have shaped the global balance of power. Instead of focusing on the celebrated “eureka” moments or the countries that first invent groundbreaking technologies, Ding argues that the true determinant of great power status is a nation’s ability to diffuse general-purpose technologies (GPTs)-such as steam power, electricity, and digital computing-across its entire economy and society. Drawing on rich historical case studies, Ding demonstrates that Britain’s rise during the First Industrial Revolution was not just about inventing the steam engine or dominating cotton textiles. Rather, Britain’s enduring advantage came from its capacity to spread new technologies-like iron machinery-across diverse sectors, supported by investments in practical education and workforce skills. The United States’ ascent in the Second Industrial Revolution, Ding shows, was similarly rooted in its institutional innovations: technical higher education, engineering professionalization, and the standardization of manufacturing, all of which enabled the rapid, economy-wide adoption of electricity and mechanization. Ding’s theory is particularly relevant to contemporary debates about U.S.–China technological rivalry. He contends that China’s rise is best understood not as a simple contest of innovation, but as a story of successful adaptation and broad diffusion of foreign technologies. This perspective challenges the prevailing “leading sector” theory, which assumes that the first mover in technological breakthroughs will dominate geopolitically. Instead, Ding’s analysis suggests that long-term economic and strategic advantage depends on building robust institutions, educational systems, and policies that foster the widespread adoption of transformative technologies. The book is not only a timely intervention for policymakers and scholars, but also a call to rethink how societies prepare for the disruptions and opportunities of emerging technologies like artificial intelligence. Ding’s emphasis on diffusion-rather than invention-offers a nuanced, historically grounded framework for understanding why some nations rise to global leadership while others fall behind.

[Jack Janzen · Rating 4 out of 5]

I like the history of technology and how it spread and contributed to the economic power of leading countries.

As a retired electrical engineer working in food manufacturing, I lived and worked and experienced first hand the third industrial revolution. The author's preferred theory of General Purpose Technology resonated with me as the computer and communication technologies were incorporated incrementally and relentlessly in our designs resulting in productivity improvements in many subtle and obvious ways.

The authors thesis that AI technology will need to be taught at all levels of potential practitioners to get the biggest benefit from the technology. Leading the technology is important but the payoff is with the diffusion. The U.S. is well positioned to do this. The author suggests that China may not be as good.

[Mikhail Filatov · Rating 1 out of 5]

The author is suggesting his own theory “Diffusion of GPT” (where GPT is not GPT, lol, but General Purpose Technology) as an opponent of Leading Sectors (LS) theory.
The problem is that both theories are equally flawed.
For example, Britain became the dominant world power by 1763-winning “World War zero” (Seven years war)-before the Industrial Revolution.
Etc.

So both these theories are completely ignoring history. DNF.

[John · Rating 3 out of 5]

Overall a very well researched and articulated book that positions a very logical argument in front of current theories and conversations. The work is thorough, the research and method is rigorous, and at the end of the day it is a very good academic book that adds complexity into our understanding.

[Zoë Moore · Rating 5 out of 5]

4.5 — Very interesting, well researched / defended

[Jonathan Mckay · Rating 4 out of 5]

Our present moment might not be so unprecedented.

[Jamie · Rating 4 out of 5]

A thoughtful and detailed review of when and how disruptive technologies change international power dynamics. Very readable too!