双语 | 机器人会导致我们失业？看完这篇我不怕了！【附人工智能相关译法】

“我姓人，名叫人工智能。我1956年出生在美国，经历过三次波折。我的成长过程非常坎坷，每次似乎我做出什么东西，世界就骂我骗子，骂了两次，现在我终于出头了。”

这是今年3月3日，李开复在“2017年投资界百人论坛”的演讲开场，而演讲主题是“我不是李开复，我是人工智能”。在演讲中，李开复还说：

“人工智能不只是要取代人类，还要远远超过人类”。

这似乎不是危言耸听，自上世纪50年代人工智能概念提出，到“深蓝”打败国际象棋大师、AlphaGo连胜人类围棋高手，人工智能的发展令人瞠目结舌。如今，人工智能其实已经无所不在，打开你的手机，每个APP里面都是人工智能——淘宝推荐的产品都是你想买的；美团每道菜都是你想吃的；滴滴总能派一个最好的司机给你……每个APP背后都是深度学习或者算法。

面对这样强大的人工智能，很多人开始担忧自己的未来，我的工作是否会被替代，我会不会因为AI而失业？人工智能研究领域的顶级专家正在试图给出答案……

The world is widely considered to be on the cusp of a fourth industrial revolution – one where machines will be able to do many of the jobs currently performed by humans, and perhaps even do them better. It is a future that promises greater efficiency and cheaper services, but one that also could herald widespread job losses.

人们普遍认为，世界正处于第四次工业革命的风口浪尖——机器将能够承担人类目前所做的许多工作，甚至比人类做得更好。未来的社会会更加高效，服务也更加廉价，但这也可能预示着大范围的失业。

It raises a troubling question for all of us – when will a machine be able to do my job?

一个令所有人不安的问题应运而生了——机器何时能替代我的工作？

There are no certain answers, but some of the world’s top artificial intelligence researchers are trying to find out.

这个问题并没有确切的答案，但一些世界顶级的人工智能研究员正试图找出答案。

Katja Grace, a research associate at the University of Oxford’s Future of Humanity Institute, and her colleagues from the AI Impacts project and the Machine Intelligence Research Institute, have surveyed 352 scientists and compiled their answers into predictions about how long it may take for machines to outperform humans on various tasks.

凯特亚•格蕾丝是牛津大学人类未来研究所的助理研究员，她与来自人工智能影响项目和机器智能研究所的同事，对352名科研人员进行了调研并汇总了结果，以此来预测机器在不同的工作中超越人类所需的时间。

人工智能在工作上的表现何时会超越人类？

When will AI outperform humans at work?

Many of the world’s leading experts on machine learning were among those they contacted, including Yann LeCun, director of AI research at Facebook, Mustafa Suleyman from Google’s DeepMind and Zoubin Ghahramani, director of Uber’s AI labs.

在调研中，他们接触到了许多世界领先的机器学习专家，其中包括脸书人工智能研究主管扬•勒丘恩，谷歌DeepMind创始人穆斯塔法•苏莱曼以及优步人工智能实验室主管Zoubin Ghahramani。

The good news is that many of us will probably be safe in our jobs for some time to come. The researchers predict there is a 50% chance that machines will be capable of taking over all human jobs in 120 years.

好消息是，我们中的大部分人暂时都不会丢饭碗。研究人员预测，在未来120年内，机器有50%的可能性会取代人类所有工作。

So what does this mean for the coming years and decades?

所以，对于未来几年甚至几十年，这意味着什么呢？

Increasing unemployment?

增加失业？

The survey suggests machines could also be folding laundry by 2021. So, if you work at a laundromat, is it time to throw in the towel? Perhaps not.

调查显示，到2021年机器就可以叠盥洗的衣物，这样的话，如果你在自助洗衣店工作，到时候会不会甘拜下风呢？或许并不会。

Machines that can fold clothes do already exist: roboticists at the University of California, Berkeley, have already developed a robot that can neatly fold towels, jeans and T-shirts.

其实会叠衣服的机器已经问世。加州大学机器人学家伯克利研发出了一款能够将毛巾、牛仔裤和T恤叠得十分整齐的机器人。

Admittedly, it took the robot nearly 19 minutes to pick up, inspect and fold a single towel in 2010, but by 2012, it could fold a pair of jeans in five minutes and a T-shirt in a little over six minutes. Perhaps most excitingly, though, the robot can even take on the tedious task of pairing socks.

虽然2010年时机器人拿起一条毛巾，审视一遍然后将其叠好需要花费19分钟，可是到了2012年，它用5分钟就能叠好一条牛仔裤，叠好一件T恤的时间也就6分钟多一点儿。也许最让人振奋的是，机器人甚至能胜任给袜子配对的乏味工作。

But despite this progress, it could be some time before robots like this are able to replace humans.

尽管取得了如此进展，这样的机器人要想取代人类仍需时日。

“I am a bit skeptical of some of the timelines given for tasks that involve physical manipulation, says Jeremy Wyatt, professor of robotics and artificial intelligence at the University of Birmingham.

伯明翰大学机器人学和人工智能教授杰里米•怀亚特表示：“我对机器取代人工的有些时间节点略表怀疑。”

“It is one thing doing it in the lab, and quite another having a robot that can do a job reliably in the real world better than a human.”

“在实验室里操作是一回事，研制出能在现实世界靠谱地做一项工作并超越人类的机器人完全是另外一回事。”

Manipulating physical objects in the real world – figuring out what to manipulate, and how, in a random, changing environment – is an incredibly complex job for a machine. Tasks that don’t involve physical manipulation are easier to teach.

在随机多变的现实环境下操作实体对象，确定操作的内容和方式，对机器来说着实复杂。不需要物理操作的任务更容易训练。

Robot mobility – things like self-driving cars and autonomous deliveries – are probably at the stage the internet was in the early 1990s, Wyatt says. “Moving things around in the world is probably 10 years further behind that.”

机器人的机动性，比如自动驾驶汽车和自动配送等，所处的水平可能只相当于上世纪90年代初的互联网。怀亚特说：“要在全世界实现自动移动技术可能还要再晚10年。”

Your friendly robot assistant

友好的机器人助手

While towel folders are safe for now, perhaps there is reason for truck drivers and retailers to consider their roles over the coming two decades. The researchers predict that AI could be driving trucks by 2027 and doing retail jobs by 2031.

既然会叠毛巾的机器目前来看问题不大，或许卡车司机和零售从业者该想想他们在接下来20年的出路了。研究人员预测到2017年人工智能将能够驾驶卡车，到2031年可以从事零售工作。

The stereotypical retail assistant job – a friendly human to help you find a pair of jeans in a shop, and tell you how they look – is a role that requires complex physical and communication skills, and is probably safe for the moment.

传统的零售辅助工作是一个友好的销售员在店里帮你找到一条牛仔裤，为你讲解它穿在身上是什么样子。这种工作需要复杂的物理和沟通技巧，可能暂时不会受到威胁。

But as more people shop online, AI in the form of bots and algorithms may be replacing other roles in retail far earlier than we might think, says Wyatt. “Look at how many transactions we now do online that are largely automated – it is a significant proportion. And they are already using a reasonable amount of AI.”

怀亚特表示，随着越来越多的人进行网购，以机器人和算法形式出现的人工智能或许会取代零售环节的其他角色，而且远早于我们所认为的时间。“看看现在我们在网上进行的交易有多少基本上是自动完成的，显然大部分都是，人工智能在其中得到了大量应用。”

Fear not, fellow humans

不要害怕，人类同胞

Perhaps the hardest jobs for machines to perform are those that take years of training for humans to excel at. These often involve intuitive decision making, complex physical environments or abstract thinking – all things computers struggle with.

可能对于机器来说，最难掌握的往往是人类经由长年的训练所精通的技能。这些技能常常包括直觉决策，复杂的现实环境或抽象思维，这些都是计算机所不擅长的。

The experts predict robots will not be taking over as surgeons until around 2053, while it could take 43 years before machines are competing with mathematicians for space in top academic journals.

据专家估计，机器人将在2053年左右取代外科医生，而与数学家匹敌，在顶级学术期刊上占有一席之地则需要43年的时间。

They also predict AI computers could be churning out New York Times bestselling novels by 2049.

专家还预测，到2049年，人工智能计算机还能大量创作出《纽约时报》最佳畅销小说。

In reality, machines are already dipping their digital fingers into this field too.

在现实中，机器也已经在数字科技方面涉足到这些领域。

Google has been training its AI on romantic novels and news articles in an attempt to help it write more creatively, and an AI bot called Benjamin can write short sci-fi film scripts – even if they don’t entirely make sense. Then there is the work of Automated Insights, which has created algorithms that churn out millions of personalised news, finance and sports articles for companies like Reuters and the Associated Press.

一直以来，谷歌都在训练人工智能写言情小说和新闻报道，以助于写出最有创意的内容。一个名叫本杰明的人工智能机器人已经写出了一篇短篇科幻电影剧本，虽然有点前言不搭后语。此外，Automated Insights公司（译者注：一家由美联社及其他投资者提供融资的科技公司）也已经发明了一种算法，为路透社和美联社等公司提供数百万篇个性化新闻、金融和体育报道。

Adam Smith, chief operating officer at Automated Insights, says this technology is intended to complement, rather than replace, human expertise. “Automated journalism is creating content that would not have existed before, but humans still need to add context to those stories.”

Automated Insights公司首席运营官亚当·斯密表示，这项技术旨在对人工技能加以辅助，而不是取代人类的专业技能。“自动化的新闻报道创造了以前不存在的内容，但是人类仍然需要对这些内容加以丰富。”

These stories, however, are produced according to a formula, where information is pulled out of large data sets and plugged in to templates. Producing bestselling fiction – rich in word play and with compelling twists in narrative – is still probably three decades away. Attempts by to use machines to play with language in creative ways usually result in nonsense.

但是，人工智能机器人创作的小说是根据一个公式而生成的，在这个公式中，信息从大数据集中提取出来并插入到模板中去。但人工智能创作出语言丰富且故事情节引人入胜的畅销小说，可能还需要三年的时间。而利用机器写出创造性语言的这种方式，往往会导致毫无意义的结果。

The challenge will be getting AI to produce material that is acceptable to our human tastes, says Wyatt. says “We find anything that is even slightly below human-level performance to be unacceptable. Take chatbots – they are not that far from human level performance… but we are so sensitive to any imperfections that they often seem laughably bad.”

对此，怀亚特表示，人工智能面临的挑战将是让机器人生产出符合人类口味的产品。他还表示，“我们发现，人们对于任何稍微低于人类水平的性能都难以接受。”比如聊天机器人，它离人类的水平其实已经非常接近了…但是我们却常常对一些不完美之处吹毛求疵，显得它们的性能很差。

Grace believes the survey should serve as a reminder that the world is on the cusp of radical change: “I don’t think there are any tasks humans can do that AI will be technically unable to carry out.”

格蕾丝认为，这项调查应该让人们认识到，世界正处在巨大变革的风口浪尖。她表示，“我不觉得人类有任何技能是人工智能在技术上实现不了的。”

But she believes some roles may never be replaced by machines. A minister in a church, for example, might never be replaced by a robot if the churchgoers want a person to be in the role.

但她也相信人工智能不能完全取代人类的所有工作。比如教堂里的牧师，如果做礼拜的人需要人来承担这个角色，牧师就永远不会被机器人取代。

“There will still be tasks that can only be conducted by a human because we will care that they are,” she says.

“有些事情只能由人类来做，因为我们只想让人类来做这些事。”她说。

人工智能相关译词：

machine learning  机器学习
physical manipulation  物理操作
robotics  机器人学
chatbot  聊天机器人
self-driving  自动驾驶
algorithm  算法
formula  公式
large data sets  大数据集
template  模板；属性单元
intuitive decision making  直觉决策
abstract thinking  抽象思维

英文来源：BBC 

编译：Janet、阿狸、Yoyo

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