Innovate or perish

Economist and economic historian Carl Benedikt Frey presents an interesting, provocative thesis in this long, well-argued book. He wonders if it is possible that the world is heading for a period of technological (and consequently economic) stagnation just when it seems that AI is taking off and is all set to turbocharge innovation and growth. Moreover, does the possibility of stagnation arise because the current political systems are not conducive to creating ecosystems for innovation? 

He doesn't have a definitive answer, of course, and he admits this is open-ended. The book delves deep into history looking at ancient civilisations, mediaeval times, the Industrial Revolution, and the past two centuries to examine periods of fast innovation and progress, as well as periods of stagnation. It tries to isolate the factors behind those contrasting phases by analysing political systems, corporate structures, business models and educational systems. 

The short summation would be: flat political systems with open exchange of information are the most conducive to innovation. However, taking proof of concept and scaling it into commercially viable technology that affects large populations (in either good or bad ways) may be done most effectively by strong, centralised bureaucracies. These could be politically driven bureaucracies framing policy across countries. Or it could be the top-down internal structures of large corporates. 

The book provides a wealth of examples to support the thesis. Ancient China, for example, was the world's most innovative place. But China ceased to innovate from the 14th century CE, when it became increasingly run by centralised bureaucracy. Mandarins acting on instructions from the throne set surveillance systems in place to ensure effective tax collections, and to shut down open access to knowledge in order to stamp out rebelliousness. At the same time, Europe consisted of a bunch of small nations with weak bureaucracies. Europeans with "dangerous ideas" could simply hop across the border to somewhere they would be welcome. Perhaps that's why Europe took up the mantle of innovation. 

Similarly, the small-government operating style of the U.S. through the 19th century gave individuals free rein to innovate. And Silicon Valley charged ahead to create entirely new industries in a similar unregulated environment from the 1970s.

But bureaucracies are very useful when it comes to scaling. Japan, for example, played catch-up impressively. It was a feudal, agrarian economy until the 1860s. Then Emperor Meiji decreed that industrialisation was necessary, and his bureaucracy obediently carried out his wishes. In just a few decades, Japan became an industrial power, absorbing technology, adopting it at scale, and setting up a strong educational system. 

At the corporate level too, while the 19th century U.S. saw innovation from individuals, the great surges in U.S. industrialisation between 1870 and 1920 were driven by giant corporations run by robber barons. The big industrialists ran companies like colonies, with top-down bureaucracies passing orders down the line. 

The U.S. continued to innovate, however. It built an excellent educational system that encouraged free thought and it encouraged entrepreneurship. The former Soviet Union also had a good educational system and produced many scientists and engineers. But it did not encourage free thought or entrepreneurship.

Frey has an interesting thought about China and its current advances in R&D in artificial intelligence (AI). China's focus is on surveillance and weaponisation of AI. As an authoritarian state, it has huge data to play with without worrying about privacy or individual rights. China also has a centralised system that enables mass production. But this doesn't necessarily make China good at using AI at other types of more useful innovations. So, China's advances – as impressive as they are may – ultimately go down a dead end where AI-driven progress is concerned. 

This well-written book indicates the cyclical nature of progress. One type of governance enables innovation; another is better at taking innovation to the masses. This should be borne in mind when we look for solutions to big problems.

Devangshu Datta is a consulting editor and columnist with a focus on STEM and finance.