2018年经济学人 自由交流:数字无产者(1)（在线收听）

Finance and Economics

财经

Free Exchange: The digital proletariat

自由交流：数字无产者

Economists propose a radical solution to the problems posed by artificial intelligence.

针对因人工智能而造成的各种问题, 经济学家提出一项激进的建议。

You have multiple jobs, whether you know it or not.

不管知道与否，人们身兼多项工作。

Most begin first thing in the morning, when you pick up your phone and begin generating the data that make up Silicon Valley's most important resource.

大多数人是在早晨拿起手机并开始生产构成硅谷最重要资源的数据时开始第一项工作的。

That, at least, is how we ought to think about the role of data-creation in the economy, according to a fascinating new economics paper.

据一篇引人入胜的新经济学论文，这至少是我们应当怎么去思考数据创造在经济中的角色的方式。

We are all digital labourers, helping make possible the fortunes generated by firms like Google and Facebook, the authors argue.

作者指出，我们全是数据劳动力，致使由谷歌和脸书等公司所创造的财富成为可能。

If the economy is to function properly in the future—and if a crisis of technological unemployment is to be avoided—we must take account of this, and change the relationship between big internet companies and their users.

如果经济要想在未来正常地运转——如果一场技术性失业要想得以避免——我们必须对此有所重视，并改变大型互联网公司与其用户之间的这种关系。

Artificial intelligence (AI) is getting better all the time, and stands poised to transform a host of industries, say the authors (Imanol Arrieta Ibarra and Diego Jimenez Hernandez, of Stanford University, Leonard Goff, of Columbia University, and Jaron Lanier and Glen Weyl, of Microsoft).

这篇论文的作者们（斯坦福大学的 Imanol Arrieta Ibarra 和 Diego Jimenez Hernandez，哥伦比亚大学的 Leonard Goff 和 微软公司的 Jaron Lanier and Glen Weyl）写道，人工智能(AI)一直都在完善之中并将彻底改变一些行业。

But, in order to learn to drive a car or recognise a face, the algorithms that make clever machines tick must usually be trained on massive amounts of data.

但是，为了学习开车或是识别人脸，让聪明机器运行的算法必须通常接受海量数据的培训。

Internet firms gather these data from users every time they click on a Google search result, say, or issue a command to Alexa.

互联网公司从用户对谷歌搜索结果的每一次点击或是向Alexa发出的每一个指令中那里收集这些数据。