Workers at the headquarters of Ruijin Technology Company in Jiaxian, in central China’s Henan Province. They identify objects in images to help artificial intelligence make sense of the world.

Dear Commons Community,

Conventional wisdom says that China and the United States are competing for A.I. supremacy and that China has certain advantages. The Chinese government broadly supports A.I. companies, financially and politically. Chinese start-ups made up one third of the global computer vision market in 2017, surpassing the United States. Chinese academic papers are cited more often in research papers. In a key policy announcement last year, the China government said that it expected the country to become the world leader in artificial intelligence by 2030.

Most importantly, this thinking goes, the Chinese government and companies enjoy access to mountains of data, thanks to weak privacy laws and enforcement. Beyond what Facebook, Google and Amazon have amassed, Chinese internet companies can get more because people there so heavily use their mobile phones to shop, pay for meals and buy movie tickets.

Still, many of those claims are iffy. Chinese papers and patents can be suspect. Government money may go to waste. It isn’t clear that the A.I. race is a zero sum game, in which the winner gets the spoils. Data is useless unless somebody can parse and catalog it.

According to an article in the New York Times, the ability to tag that data may be China’s true A.I. strength, the only one that the United States may not be able to match. In China, this new industry offers a glimpse of a future that the government has long promised: an economy built on technology rather than manufacturing.  Here is an exceerpt:

“Some of the most critical work in advancing China’s technology goals takes place in a former cement factory in the middle of the country’s heartland, far from the aspiring Silicon Valleys of Beijing and Shenzhen. An idled concrete mixer still stands in the middle of the courtyard. Boxes of melamine dinnerware are stacked in a warehouse next door.

Inside, Hou Xiameng runs a company that helps artificial intelligence make sense of the world. Two dozen young people go through photos and videos, labeling just about everything they see. That’s a car. That’s a traffic light. That’s bread, that’s milk, that’s chocolate. That’s what it looks like when a person walks.

“I used to think the machines are geniuses,” Ms. Hou, 24, said. “Now I know we’re the reason for their genius.”

In China, long the world’s factory floor, a new generation of low-wage workers is assembling the foundations of the future. Start-ups in smaller, cheaper cities have sprung up to apply labels to China’s huge trove of images and surveillance footage. If China is the Saudi Arabia of data, as one expert says, these businesses are the refineries, turning raw data into the fuel that can power China’s A.I. ambitions.

…

 “We’re the construction workers in the digital world. Our job is to lay one brick after another,” said Yi Yake, co-founder of a data labeling factory in Jiaxian, a city in central Henan province. “But we play an important role in A.I. Without us, they can’t build the skyscrapers.”

While A.I. engines are superfast learners and good at tackling complex calculations, they lack cognitive abilities that even the average 5-year-old possesses. Small children know that a furry brown cocker spaniel and a black Great Dane are both dogs. They can tell a Ford pickup from a Volkswagen Beetle, and yet they know both are cars.

A.I. has to be taught. It must digest vast amounts of tagged photos and videos before it realizes that a black cat and a white cat are both cats. This is where the data factories and their workers come in.

Taggers helped AInnovation, a Beijing-based A.I. company, fix its automated cashier system for a Chinese bakery chain. Users could put their pastry under a scanner and pay for it without help from a human. But nearly one-third of the time, the system had trouble telling muffins from doughnuts or pork buns thanks to store lighting and human movement, which made images more complex. Working with photos from the store’s interior, the taggers got the accuracy up to 99 percent, said Liang Rui, an AInnovation project manager.

“All the artificial intelligence is built on human labor,” Mr. Liang said.

AInnovation has fewer than 30 taggers, but a surge in labeling start-ups has made it easy to farm out the work. Once, Mr. Liang needed to get about 20,000 photos in a supermarket labeled in three days. Colleagues got it done with the help of data factories for only a couple thousand dollars.”

Chinese development of A.I. applications will receive a real boost from the data farms described in this article.  The United States has nothing comparable yet.

Tony

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