How Progress Ends

Technology, Innovation, and the Fate of Nations

By Carl Benedikt Frey

Category: Technology & the Future | Reading Duration: 19 min | Rating: 4.3/5 (28 ratings)

About the Book

How Progress Ends (2025) traces the fragile balance between chaos and order that drives technological advancement. It examines why this balance breaks down and how both America and China now risk the stagnation that comes when incumbents block disruptive innovation. Nations rise when they match the right system to the moment – and fall when they don't.

Who Should Read This?

Historians exploring the long-term drivers of national economic destinies
Policymakers crafting strategies for national innovation and industrial growth
Business leaders navigating technological disruption and corporate stagnation

What’s in it for me? Discover why great civilizations fail – and underdogs win.

You’ve likely grown up with the idea that progress is an inevitable, upward march of human ingenuity. Yet history shows a different pattern: great civilizations suddenly falter, and unexpected upstarts change everything. This follows a deep logic about how societies organize themselves for innovation, and how institutions that create prosperity can also become seeds of stagnation. In this Blink, we’ll uncover a powerful framework for understanding this cycle of rise and fall.

We’ll move beyond simple debates of free markets versus state control to reveal the two competing engines of progress – the chaotic engine of discovery and the disciplined engine of production – and see how getting the balance right is the ultimate challenge of any society. By the end, you’ll see history as a dynamic system, not a series of events. This will equip you with a new lens to analyze the technological race between today’s superpowers – and to understand the subtle forces that could determine whether our own era is one of continued advancement or the beginning of a great stagnation.

Chapter 1: A tale of two systems

Progress feels inevitable when you’re living through it, but history tells a different story. Look closer and you’ll see something more fragile – a process full of contradictions, sudden breakthroughs, and decades of nothing happening at all. The secret lies in recognizing that progress runs on two completely different engines that often work against each other. The first engine is exploration.

This runs on chaos – the messy, unpredictable world where new ideas emerge from nowhere. Picture thousands of experiments happening simultaneously: independent inventors in garages, university researchers following hunches, small startups betting everything on ideas that seem absurd. Most will fail. That's the point. This system sacrifices efficiency today for the possibility of doing things radically better tomorrow. The second engine is exploitation.

This runs on control, and it's where proven ideas get perfected and scaled. Think massive factories, sprawling corporations, and state industrial plans. Here, discipline replaces experimentation. The goal shifts from finding something new to making something known available to everyone, as cheaply as possible. Static efficiency becomes everything: squeeze maximum output from existing resources, optimize every process, eliminate waste. The story of the mRNA vaccine shows both engines in action, and the friction between them.

We start with Katalin Karikó, a Hungarian biochemist whose research into mRNA was so unconventional she couldn’t get government grants. Her own colleagues thought she was wasting her time. The University of Pennsylvania denied her tenure. But she kept going anyway, convinced mRNA held therapeutic potential everyone else was missing. Her breakthrough came through pure chance – meeting immunologist Drew Weissman at a photocopier led to a collaboration that solved the fundamental problem preventing mRNA from working in human bodies. Even after their discovery, almost nobody cared.

Years passed before another scientist, Derrick Rossi, stumbled across their paper and recognized its value. He helped launch Moderna to commercialize the technology. You couldn’t have planned this trajectory if you tried. That’s how exploration works – through accidents, persistence, and countless dead ends. Then COVID arrived, and suddenly the game changed completely. Small innovators like BioNTech launched focused projects to develop mRNA vaccine candidates within weeks.

But they needed industrial giants like Pfizer for testing, manufacturing, and distribution. Government programs like Operation Warp Speed coordinated the massive effort. The same chaotic process that created mRNA technology would have been catastrophic here. You needed hierarchy, discipline, and centralized control to save lives.

And here's where nations succeed or fail: managing the transition between these two modes. The very system that scales known technologies would have crushed Karikó's unorthodox research before it began. Powerful incumbents who've perfected exploitation have every reason to resist the creative destruction that new technologies bring. When they succeed – blocking competition or capturing regulators – progress stops.

Chapter 2: A fork in history

Exploration and exploitation – these are the two engines of progress. Entire civilizations will rise and fall based on which of the two engines they favor, and when. The story of China and Europe shows this playing out across centuries, with empires gaining and losing their edge as they shift between discovery and control. For most of recorded history, China dominated the technological frontier.

By the eleventh century, the Song dynasty’s capital Kaifeng featured a water-powered astronomical clock of breathtaking complexity. Chinese engineers had been casting iron since 200 BCE – Europeans wouldn’t figure this out for another 1,600 years. But the same centralized strength that made China so effective at scaling and refining slowly became a prison. The imperial system prioritized stability above all else, and stability meant controlling the chaotic forces of discovery. The civil service examination became the main path to wealth and prestige, channeling brilliant minds into studying Confucian classics to become bureaucrats. A Chinese Galileo would have spent his genius on administration.

Merchants and foreign trade were viewed with suspicion. The Ming dynasty went so far as to ban ocean-going ships, letting their magnificent fleets rot in harbors. China chose control over discovery and entered centuries of stagnation. Now shift your attention to Europe, where something radically different was happening. The collapse of the Roman Empire might look like catastrophe, but it gave Europe an unexpected gift: permanent political fragmentation. No single emperor could enforce orthodoxy across hundreds of rival states, cities, and principalities.

This chaos created something China lacked – a competitive marketplace for ideas. An innovator whose dangerous idea got them exiled from one territory could find refuge next door. The constant movement of people and ideas spawned the Republic of Letters, an intellectual network that transcended borders and laid groundwork for the Scientific Revolution. Yet fragmentation alone couldn’t spark the Industrial Revolution. Europe had its own forces of resistance: craft guilds that fought new technologies threatening their livelihoods. The breakthrough came in England, which managed to do something unique: combine Europe’s decentralized innovation culture with a powerful unified Parliament.

After the Glorious Revolution of 1688, Parliament grew strong enough to override the local guild interests that were blocking progress. When machine-breaking riots erupted, the British state sided with innovators, making the destruction of machinery a capital offense. This ability to suppress the forces of the past in favor of the future allowed the factory system to take root. Industrial Britain thrived, because it knew when to switch between the modes of exploration and exploitation, protecting the messy work of discovery from the very systems that will eventually perfect and scale those discoveries.

Chapter 3: Closing the gap

So Britain combined exploration with exploitation to spark the Industrial Revolution. The nations that followed could see the future – it was already running in British factories. We can see exactly how the catch-up playbook works by taking a look at Prussia. In 1806, Napoleon’s armies crushed the Prussian military at Jena-Auerstadt, exposing deep institutional rot.

This humiliation sparked something extraordinary: the Stein-Hardenberg Reforms, a revolution from above. Reform-minded civil servants used state authority to systematically clear the path for modern industry. They abolished feudal privileges and restrictive craft guilds. They created world-leading technical schools and research universities to produce skilled engineers. They coordinated railway construction to build a unified national market. This “organized capitalism” produced giant, vertically integrated corporations in steel, chemicals, and electricity.

Prussia even encouraged industrial cartels – seeing them as tools to achieve the massive scale needed to challenge British rivals. And by century's end, the unified German state had surpassed Britain in many key industries. Halfway around the world, Japan played out a strikingly similar story. For centuries, Japan had sealed itself off under the Tokugawa Shogunate. Then Commodore Perry’s American gunboats arrived in 1853, delivering the same kind of shock Napoleon had brought to Prussia. Japan’s vulnerability was exposed, triggering the Meiji Restoration in 1868 – a swift campaign to modernize and avoid suffering the same humiliation as China, which had been forced into unequal treaties and lost influence across its own territory after losing the Opium Wars.

Japan’s new elite, the samurai-bureaucrats, looked directly to Germany for their model. They centralized the state, dismantled feudalism, and directed a national industrialization campaign. The government facilitated massive technology transfer from the West and nurtured powerful industrial conglomerates, the zaibatsu, to coordinate investment and production across the economy. Remember how we talked about China’s failure to balance exploration and exploitation? These catch-up nations faced the opposite situation. They knew exactly what technologies to pursue – the exploration had already been done.

Their challenge was pure exploitation, and for that, a powerful, meritocratic state became an immense asset. The state could override vested interests protecting the old order. It could mobilize national resources toward the singular goal of industrial modernization. This catch-up model became the blueprint for the post-World War II "Golden Age," where nations across the world used state power to rapidly industrialize by copying proven technologies. During the Golden Age, the focus was pure exploitation – perfecting mass production of cars, refrigerators, steel, and chemicals that the US had pioneered. Coordinated state planning, powerful unions, and massive corporations worked in tandem to spread prosperity.

For three decades, this system delivered extraordinary results, lifting living standards across the developed world. But exploitation only works when you know what to exploit. When the technological frontier shifts to something fundamentally new, entire systems can become obsolete overnight.

Chapter 4: The American frontier

The stable world of the post-war assembly line started crumbling in the 1970s. The mass production engine that had churned out cars and refrigerators hit diminishing returns. Oil shocks dealt the final blow, plunging Western industries into stagflation. The old playbook was dead.

A new technological paradigm was emerging – the computer – and it demanded something completely different. It was time to return to messy, decentralized exploration. The rigid, top-down systems that had defined the Golden Age were spectacularly unprepared. Japan stumbled. Its keiretsu conglomerates – the post-war successors to the zaibatsu – had perfected collaborative exploitation, manufacturing hardware with unmatched quality. But this insular, hierarchical system was too rigid for software and open networks.

It could perfect existing products but couldn’t create the ecosystem of disruptive startups needed to lead a revolution. The Computer Revolution became an American story, but the surprise was where exactly it happened. The established corporate giants on Boston’s Route 128, with their hierarchical structures and military contracts, missed it entirely. It was Silicon Valley that won, through a culture that would have horrified Japan or Germany: engineers constantly job-hopping, sharing knowledge in local pubs, leaving established firms to found startups. California’s ban on non-compete agreements kept ideas flowing freely between companies. The US’s commitment to challenging monopolies proved equally vital.

Breaking up AT&T and the legal war against IBM created competitive space for Microsoft to emerge. It ensured the internet would develop as a decentralized network rather than a closed corporate system. Today, this cycle of progress faces new threats of stagnation. The world’s two leading economies, the US and China, are showing troubling signs. China under Xi Jinping is reversing the decentralized experimentation that powered its economic miracle. The Communist Party is re-centralizing authority, cracking down on dynamic private companies, and deploying artificial intelligence for surveillance and social control rather than open exploration.

History repeats – another dynasty choosing the stability of the cage over the chaos of discovery. The US faces its own threat. A handful of tech corporations have amassed enormous economic and political influence. They lobby for favorable regulation, acquire potential rivals, and stifle the creative destruction that once made the US an innovation engine.

The historical lesson is clear: progress is fragile, never permanent. It requires constant vigilance against the forces that would trade tomorrow’s breakthroughs for today’s stability. The struggle between exploration and exploitation continues, and its outcome continues to shape civilizations.

Chapter 5: The great unravelling

The superpowers we’ve been tracking – China and the US – are facing institutional sclerosis. Yet artificial intelligence promises to rewrite the rules. You might think AI will solve everything – let China achieve the Soviet dream of perfect planning, or help American incumbents innovate out of stagnation. But AI has fundamental limits.

Why? Because most human knowledge is tacit and sensory, learned through physical interaction rather than language. A large language model may have consumed the entire internet, but a four-year-old has processed vastly more data through their senses alone. Current AI excels at codifying and recombining what’s already known, but struggles with the unwritten, intuitive knowledge behind true creativity. This brings us to the core problem. Today’s AI, particularly large language models, are powerful tools of exploitation rather than exploration.

They identify statistical patterns in human-created content. They write Shakespeare-style sonnets because Shakespeare already existed in their training data. They cannot invent fundamentally new literary forms that break learned patterns. Imagine a large language model in 1633, trained on every book ever written. Ask it if the Earth revolves around the Sun, and it would confidently say no. It couldn't produce Galileo's revolutionary insight, which came from challenging existing knowledge rather than averaging it.

The greatest obstacle to future progress lies in institutional flexibility rather than computational power. Technological dynamism requires what Joseph Schumpeter called creative destruction – new innovations and companies displacing old ones. This process is socially and politically difficult. It demands societies accept disruption and calls for political systems that protect competition over incumbent interests. Sustained democratic progress depends on the widespread belief that technological gains will be broadly shared, creating better opportunities for those displaced. Today, public faith in that belief is eroding, as large corporations focus on automating existing tasks while startups face growing barriers to entry.

Technology, even AI, cannot cure flawed institutions. Societies prioritizing present comfort over future potential will use their best tools to reinforce the status quo. Think back through everything we’ve explored – from China’s stagnation to Silicon Valley’s dynamism. The pattern holds: progress hinges less on machine brilliance and more on a collective willingness to clear paths for disruptive, unpredictable human invention. The future depends on whether we choose the cage of stability or the chaos of discovery.

Final summary

In this Blink to How Progress Ends by Carl Benedikt Frey, you’ve learned that sustained technological progress is not inevitable but depends on a society’s ability to switch between two conflicting systems: the decentralized exploration needed to invent the future and the centralized exploitation needed to perfect the present. This historical dynamic explains why early technological leader China stagnated under a rigid bureaucracy, while fragmented Europe became the cradle of the Industrial Revolution. It shows how latecomers like Prussia and Japan used powerful states to rapidly catch up by copying existing technologies, a model that fueled the global “Golden Age” after World War II, as nations mass-produced innovations pioneered in the decentralized US. Today, this engine of progress is sputtering.

As both the US and China drift toward systems that protect powerful incumbents and stifle competition, they risk creating the very institutional sclerosis that has ended progress time and again throughout history. Okay, that’s it for this Blink. We hope you enjoyed it. If you can, please take the time to leave us a rating – we always appreciate your feedback. See you in the next Blink.

About the Author

Carl Benedikt Frey is an economic historian based in Oxford. His work centres on the relationship between technology, economic development, and the future of work. He is Associate Professor of AI & Work at the Oxford Internet Institute, University of Oxford, and is also the author of The Technology Trap.