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廉价劳动力如何推动中国的人工智能雄心
How Cheap Labor Drives China’s A.I. Ambitions

来源:纽约时报    2018-11-26 06:18



        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.        向中国科技目标推进的一些最关键工作,在中国中部腹地的一座原水泥厂里进行着,与北京和深圳那些向往成为硅谷的地方相距十万八千里。工厂院内还摆着一台闲置的混凝土搅拌机。隔壁的一座仓库里堆着一箱箱密胺餐具。
        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.        院子里,侯夏梦经营着一家帮助人工智能理解世界的公司。24个年轻人在浏览照片和视频,标记他们看到的每样东西。这是一辆汽车,那是一个红绿灯。这是面包,这是牛奶,那是巧克力。这是一个人走路的样子。
        “I used to think the machines are geniuses,” Ms. Hou, 24, said. “Now I know we’re the reason for their genius.”        “我以前觉得机器很聪明,”24岁的侯夏梦说,“现在我知道,它所有的聪明都是我们给它的。”
        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.        在长期充当世界工厂的中国,新一代的低薪工人正在为未来奠定基础。在规模较小、成本较低的城市,创业公司如雨后春笋般涌现,他们在给中国海量的图像和监控录像添加标签。正如一位专家所说,如果把中国比做数据方面的沙特阿拉伯,那么这些公司就是炼油厂,它们将原始数据转化为可以为中国的人工智能雄心提供动力的燃料。
        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.        通常认为中国和美国正在争夺人工智能的霸主地位,而中国具有一定的优势。中国政府在财政和政策上广泛支持人工智能公司。2017年,全球计算机视觉市场中,中国创业公司占了三分之一,超过美国。中国的学术论文在研究论文中被引用的频率更高了。在去年的一份重要政策声明中,中国政府表示,预计到2030年,该国将成为人工智能领域的全球领导者。
        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.        更重要的是,这种想法认为,多亏了薄弱的隐私法律及其执行,中国政府和公司获得了堆积如山的数据。在Facebook、谷歌和亚马逊已经积累的数据之外,中国互联网公司能获得更多,因为那里的人们太常用他们的手机购物、支付餐费,以及购买电影票。
        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.        然而这些说法中的许多是存疑的。中国的论文和专利可能存在问题。政府的钱可能会被浪费掉。目前还不清楚人工智能竞赛是否会是一场赢者通吃的零和博弈。除非有人能够分析和归类,否则数据是无用的。
        But 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.        但标记这些数据的能力,可能是中国真正的人工智能实力,也可能是美国唯一无法匹敌的力量。在中国,这个新兴产业提供了一个政府长期承诺的未来的一瞥:一个建立在科技而非制造业基础上的经济。
        “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.”        “我们这些人属于数据行业里的建筑工人。我们做的事就是垒砖头,一块一块地垒,”中部省份河南郏县一家数据标签工厂的联合创始人伊亚科说,“但我们在人工智能中扮演着重要角色,没有我们,他们无法建造摩天大楼。”
        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.        虽然人工智能机器是超快的学习者,擅长处理复杂的运算,但它们缺乏就连5岁的孩子都具备的认知能力。小孩子们都知道棕色的可卡犬和黑色的大丹犬都是狗。它们可以分辨一辆福特皮卡和一辆大众甲壳虫,但还无法了解二者都是汽车。
        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.        人工智能需要被教导。它必须消化大量带有标签的照片和视频,然后才能意识到,黑猫和白猫都是猫。这就是数据工厂及其工作人员起作用的地方。
        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.        标记帮助北京的人工智能公司AInnovation完善其为一家中国面包连锁企业提供的自动收银系统。用户可以将糕点放在扫描仪下,在没有人类帮助的情况下付费。但有三分之一的时候,由于商店照明和人体运动,图像变得更加复杂,系统无法分辨玛芬蛋糕、甜甜圈或叉烧包。AInnovation项目经理梁睿表示,标记在使用商店内部照片的情况下,准确度高达99%。
        “All the artificial intelligence is built on human labor,” Mr. Liang said.        “有多少人工就有多少智能,”梁睿说。
        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.        AInnovation有不到30个标记员,但标签初创公司的激增使得把工作外包出去变得很容易。有一次,梁睿为超市做标签,需要在三天内拍摄大约20000张照片。同事们在数据工厂的帮助下,只花几千美元就完成了工作。
        “We’re the assembly lines 10 years ago,” said Mr. Yi, the co-founder of the data factory in Henan.        “我们就是10年前流水线上的工人,”河南那家数据工厂的联合创始人伊亚科说。
        The data factories are popping up in areas far from the biggest cities, often in relatively remote areas where both labor and office space are cheap. Many of the data factory workers are the kinds of people who once worked on assembly lines and construction sites in those big cities. But work is drying up, wage growth has slowed and many Chinese people prefer to live closer to home.        数据工厂开始在远离大城市的地区涌现,通常是在相对偏远的地区,劳动力和办公空间都很便宜。许多数据工厂的工人都曾在大城市的流水线和建筑工地工作。但是那些工作正在枯竭,工资增长放缓,而且许多中国人更喜欢住在离家较近的地方。
        Mr. Yi, 36, was out of a job and trying to get other ventures going with elementary school classmates when someone mentioned A.I. tagging. After online searches, he decided it wasn’t super technical but needed cheap labor, something Henan has in abundance.        36岁的伊亚科失业后听说了人工智能标记,那时他试图和小学同学一起做别的公司。在网上搜索后,他认为这项工作技术性不强,只需要廉价劳动力,而这正是河南不缺少的。
        In March, Mr. Yi and his friends set up Ruijin Technology, which rents offices the size of two professional basketball courts in an industrial park for $21,000 a year. It was previously the park’s Communist Party committee’s event space, so the ceiling lights are covered with red hammers and sickles.        三月,伊亚科和朋友们成立了睿金科技,该公司以每年2.1万美元的价格在工业园区租用了两个专业篮球场。它以前是园区党委会的活动空间,吊顶灯上覆盖着红色的镰刀锤子图案。
        Ruijin, which means smart gold, now employs 300 workers but plans to expand to 1,000 after the Chinese New Year holiday, when many migrant workers come home.        睿金的意思是智慧黄金,它现在雇佣了300名工人,但计划在春节假期后扩大到1000人,春节期间,很多农民工会回家乡。
        Unlike workers and business around the world, Mr. Yi isn’t worried that A.I. will take his job.        与世界各地的工人和企业不同,伊亚科并不担心人工智能会取代他的工作。
        “The machines aren’t smart enough to teach themselves yet,” he said.        “机器还没有聪明到自己教自己的程度,”他说。
        Hiring is a bigger worry.        招聘是一个更大的麻烦。
        Ruijin’s pay of $400 to $500 a month is higher than average in Jiaxian. Some potential job candidates worry that they don’t know anything about A.I. Others find the work boring.        睿金每月400至500美元的薪酬高于郏县的平均水平。一些潜在的求职者担心自己对人工智能一无所知。也有人觉得这项工作很无聊。
        Jin Weixiang, 19, said he would quit Ruijin after the Chinese New Year and go to sell furniture in a physical store in southern city Guangzhou.        19岁的靳炜祥表示,他将在春节后离开睿金,到南方城市广州一家实体店卖家具。
        “I’m a people’s person,” said Mr. Jin. “I’m doing labeling for the money.”        “我喜欢和人打交道,”靳炜祥说。“做标注就是挣点钱。”
        But for some former migrant workers, the job is better than working on assembly lines.        但对于一些以前的农民工来说,这项工作比在流水线上工作要好。
        “It was the same work, same movement, day after day,” said Yi Zhenzhen, a 28-year-old Ruijin employee who once worked at an electronic component company. “Now I have to use my brain a little bit.”        “工厂里每天是一样的活,一样的动作,天天都一样,”曾在一家电子元件公司工作的睿金员工、28岁的伊真真说。“现在得稍微动动脑子。”
        Most of the time, customers don’t tell these data factories what the task is for. Some are obvious. Labeling traffic lights, road signs and pedestrians are usually for autonomous driving. Labeling many types of camellia flowers could be for search engines.        大多数情况下,客户不会告诉数据工厂,他们的工作是用来做什么的。有些是显而易见的。比如标记交通信号灯、道路标志和行人,它们通常用于自动驾驶。标记许多类型的山茶花可能是给搜索引擎用的。
        Once Ruijin was given the task of labeling the images of millions of human mouths. Mr. Yi said he wasn’t sure what it was for. Maybe facial recognition?        有一次,睿金得到一个任务,为数百万个人类的口部图像做标记。伊亚科说他不确定这是用来做什么的。也许是面部识别?
        Roughly 300 miles to the north, in the Hebei city of Nangongshi, Hou Xiameng runs her data factory out of her in-laws’ former cement factory. Her first job out of college was labeling faces for Megvii, the Chinese facial recognition company with a $2 billion valuation that’s most famous for its technology platform called Face++. To this day, some facial recognition systems recognize her before they do her friends because, she says, “my face is in the original database.”        大约向北300英里的河北南宫市,侯夏梦经营着一家数据工厂,由她婆家拥有的一间旧水泥厂改建而来。她在大学毕业后的第一份工作是给旷视科技做面部标记,这是一家价值20亿美元的中国面部识别公司,其最著名的技术平台名为Face++。到目前,一些面部识别系统可以比识别她的朋友更快地识别她,她说这是因为“我的脸在原始数据库里。”
        But life in Beijing was too tough and expensive. She and her then-fiancé, Zhao Yacheng, decided to move back to their hometown and start a data factory. Ms. Hou’s parents would pay for computers and desks. They are renovating the warehouse next door to hire 80 more people.        但北京的生活太过艰难而且昂贵。她和当时的未婚夫赵亚成决定搬回家乡做数据工厂。她的父母可以出电脑和办公桌的费用。他们正在翻新隔壁的仓库,再雇用80多名员工。
        Like Mr. Yi, Ms. Hou doesn’t spend time thinking about the implications of her work. Are they contributing to a surveillance state and a dystopian future that machines will control human?        像伊亚科一样,侯夏梦并没有花时间思考自己的工作所带来的影响。它们是否有助于国家的监视,以及机器控制人类的反乌托邦未来?
        “Cameras make me feel safe,” she said. “We’re in control of the machines for now.”        “摄像头让我感觉安全,”她说。“最起码现在是我们在控制机器。”
                
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