Government and Innovation, China-Style

Decades of attempts at Artificial Intelligence (AI) failed, until the advent of “neural networks”. That is basically an attempt to make computers “learn” the way our brains learn. For example, one feeds the system photos along with labels (cat, dog etc) and lets the computer find the patterns corresponding to each. Once ready, one then feeds it new photos that weren’t part of its training. This is the test – to see whether the patterns it noticed were correct or not.

 

That approach has yielded the AI we see today all around us – speech recognition (Alexa), image recognition (face unlock on your phone), driverless vehicles etc. While that’s very impressive, it is what is called “narrow AI” – limited to specific topics only. General purpose AI is still far away.

 

The Chinese venture capitalist and ex-Googler, ex-Microsoft, Kai-Fu Lee wrote an excellent book on the state of AI in China. While the US is Number 1, he says China is the clear Number 2 and closing in fast, even ahead in some areas.

 

China’s leap forward in AI was triggered by a 2014 government announcement that “mass entrepreneurship and mass innovation” was the next big thing and that the government would encourage and ease all attempts at it. In China, such an announcement doesn’t mean the center will pick the winners or dole out the money. Rather, it sets off a competition among the states and cities to attract entrepreneurs via ease of funding and tax breaks. In return, the states and cities hope that should the field succeed, their tax revenues would grow.

 

And this being China, they wouldn’t wait for a home-grown model of Silicon Valley to evolve naturally (or slowly). Instead, the government cleared out a part of Beijing to only host VC firms, startups, incubators and service providers – it was called the Avenue of the Entrepreneurs. As Lee says:

“This kind of top-down construction of an innovative ecosystem runs counter to Silicon Valley orthodoxy.”

 

A major effect of this move was that Chinese entrepreneurs didn’t have to tailor their pitches for funding to the “tastes of foreign VC’s”:

“They could build Chinese products to solve Chinese problems.”

This then proved to be a big reason for why the Chinese Internet is now nothing like the Western Internet – their products are tailored for the Chinese market. (The other reason for the bifurcation, of course, is the censorship net called the Great Firewall of China).

 

Most people have trouble understanding how knowledge or research can thrive under such a state-controlled setup. Lee explains why that’s not a problem:

“China’s system of governance… weigh heavily on public debate and research in the social sciences. But when it comes to research in the hard sciences, these issues are not as limiting as many outsiders presume.”

 

The West believes that the government shouldn’t dictate or control economics beyond a bare minimum. China, on the other hand, is OK with “brute-forcing the economic and technological upgrading” of the country. Neither approach is necessarily better – the economy is dynamic and unpredictable, and one can’t wait for government bureaucracies to respond. On the other hand, the private sector won’t think long term and may not be willing to make certain bets.

 

One can’t say which approach will prove better, but one thing is for sure – the West and China are betting on opposite approaches. For the first time in decades, the Western model and ideas on the path to economic prosperity has a very serious and increasingly successful challenger.

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