The negative effects that industrial revolutions unleash on human society always stem from an overestimation and abuse of the power of new technologies. It has never been more important to heed this point than today. Big data and artificial intelligence are bringing forth a new industrial revolution, and the blind worship of these innovations is already on full display in some quarters.
In early September, Russian President Vladimir Putin said that the development of artificial intelligence technology has created “huge and unpredictable new opportunities and threats.” He went on to declare that, “Whoever leads this field will rule the world.” In the Russian leader’s eyes, AI is not only a major strategic opportunity, but the key to his country’s survival.
China is also keen to lead the way in AI. On July 8, the State Council issued a “New Generation Artificial Intelligence Development Plan.” Promoting the development of the AI sector is of course a very good idea, but the crucial question is how best to accomplish this goal. Is it, as some have suggested, through state planning? To that question, we can answer with great certainty: the planned approach will not work. Those who use the planning method can only follow in the footsteps of others, which implies lagging behind.
In the history of mankind, all technological revolutions — all moments of revolutionary innovation — have emerged from the market and from entrepreneurs acting on private initiative. They are the final result of a survival-of-the-fittest competition.
In the debate about AI, some prominent figures have also asserted that artificial intelligence could be capable of producing a new form of planned economy. One example they cite is the financial sector, an important application field for AI. If investment decisions can be made by machines, isn’t this a kind of planned economy?
The boundaries of the planned economy have therefore re-emerged as an important and fundamental question for the future.
Before answering this question, however, the first thing I would emphasize is that China’s biggest problems are systemic, and should not be thought of as an assortment of technical issues that can be fixed individually. Ultimately, it is not important whether China is a global leader in this or that industry. The important thing is whether the national economy as a whole is doing well.
Last year, a survey by McKinsey found that China’s labor productivity is between 15 and 30 percent of the OECD average. This means that China is still several times less productive than the developed nations of the world. There is a general backwardness in China’s economy that dwarfs the progress made in a few cutting-edge fields.
Labor productivity is low, but at the same time labor costs are very high. In 2016, unit labor costs in China were higher than in the United States and Western Europe, according to analysis by the Economist Intelligence Unit. An Oxford Economics survey conducted the same year found that China’s labor costs were only 4 percent lower than in the United States. In other words, if we are looking purely at labor costs, it is now about as expensive to make a product in China as in the United States. This is strange.
If labor costs are so high, does this mean that Chinese workers are earning too much money? No. China’s household income accounts for a smaller percentage of GDP than in many other countries.
Labor costs are high; workers don’t get much money; and enterprises bear a lot of the costs without getting much either. How can all this be true? The answer is that the government is taking all that money for itself. The Chinese government’s income is among the highest in the world, and this causes workers and enterprises to bear huge institutional costs.
Systemic issues like these are the ones we need to solve. We can focus on fixing technical issues in the Chinese economy, such as upgrading traditional industries by integrating new, cutting-edge technologies, and these efforts are sure to produce positive results. But they cannot solve the wider economic problems we face.
What’s more, industrial upgrading has the potential to create negative as well as positive effects.
When people mistakenly believe that the latest scientific and technical breakthroughs surpass all the knowledge accumulated by humanity over thousands of years, they sometimes rush to replace the socio-economic systems produced in recent centuries, which often leads to disastrous results. A consensus has been reached that the emergence of big data and artificial intelligence are leading to another industrial revolution. But when discussing where these changes will lead us, we need to look calmly at the many negative lessons from past industrial revolutions: in particular our tendency to overestimate and abuse the power of new technologies. Industrial revolutions are not always positive in all respects and we must be wary of the possible dangers involved.
One of the worst lessons from previous industrial revolutions is the creation of state-ownership dominated central planning systems. This idea first surfaced during the first two industrial revolutions. At that time, some ultra-left intellectuals mistakenly believed that human beings had acquired the ability to understand everything, and that they therefore had the ability to control all aspects of society.
The mistaken belief that the social planner is able to know what is good for everyone, can take care of everyone’s welfare, and can plan for every technological change, all production needs, and everything else: This is the underlying idea that led to central planning. Because there had never been an industrial revolution before in human history, some intellectuals overestimated their own power, and this led them to abuse it. At its height, one-third of the world’s population lived in state-owned and centrally-planned economies.
Another common problem arising from the hubris of intellectuals is environmental destruction. There are two clear examples of this. The first is huge water conservancy projects. People think that they have the ability to plan our rivers, lakes and land. They build dams to make huge artificial lakes. Then, when this produces catastrophic consequences, they realize that there are a lot of things they don’t know. Even if a government with huge resources and power has good intentions, it can still cause disasters.
A second example is climate change, a problem that did not exist before the industrial revolution, and the cause is the same — people mistakenly believing that they are smarter than they are. When Hurricane Irma swept through the Caribbean, with wind speeds reaching roughly 300 kilometers per hour, 95 percent of the buildings on some islands were completely flattened. This natural disaster was manmade, caused by people who believed that we could concentrate all resources on solving society’s problems. But in the process, so much carbon was emitted from fossil fuels that the climate has been destabilized. These old lessons are still far from being fully absorbed, even as the big data and AI revolution looms. Some scientists have issued warnings, but most focus on ethical issues like the possibility of using robots in warfare. I want to emphasize another problem, that of the system and the relationship between the market and the central plan.
Some governments and large, monopolistic companies may try to use their mastery of big data to control society, to replace the market — to use technological progress against society. It would bring disaster. We must rather make sure that this industrial revolution truly benefits mankind.
This article was first published on Caixin Global, and has been republished with their permission. The article can be found on their website here.
(Header image: Science Source/VCG)