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.
很多人认为，世界即将迎来第四次工业革命——这一次，机器可以完成很多由人类负责的工作，甚至比人类做得更好。未来的世界可以实现更高的效率，享受更廉价的服务，但失业也将变得更加普遍。 It raises a troubling question for all of us – when will a machine be able to do my
job?
电力宽带这便引发了一个令人不安的问题——机器什么时候能够取代你的工作？
There are no certain answers, but some of the world's top artificial intelligence researchers are trying to find out.
目前还没有确切答案，但一些全球顶尖的人工智能研究人员希望到答案。 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.
牛津大学人类未来研究院 ( Future of Humanity Institute )助理研究员卡特佳·格蕾丝( Katja
Grace )与来自人工智能影响项目 (AI Impacts )和机器智能研究院 ( Machine Intelligence Research Institute )的同事，对 352 名科学家展开了调查，用他们的答案来预测机器还要多久能在各种任务上超越人类。
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 Deep
Mind and Zoubin Ghahramani, director of Uber's AI
labs.
他们联系了很多全球顶尖的机器学习专家，其中包括 Facebook 人工智能研究总监严·勒坤
Yann LeCun )、谷歌 DeepMind 的穆斯塔法·苏莱曼( Mustafa Suleyman )和 Uber 人
出口贸易结构工智能实验室的左斌·加赫拉玛尼( Zoubin Ghahramani )。llr
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.tcl电话机维修
好消息是，很多人的工作在未来一段时间内可能都是安全的。研究人员预计，机器有 50% 的概率能在未来 120 年取代所有人的工作。
"One of the biggest surprises was the overall lateness of the predictions," says Grace. "I expected the amazing progress in machine learning in recent years, plus the fact that we were only talking to machine learning researchers, to make the estimates earlier."
“最令人意外的是，这些预测的时点都很晚，”格蕾丝说。“我原本预计，由于机器学习最近几年进步神速，加上我们的调查对象都是机器学习研究人员，所以时点应该早一点。”
So what does this mean for the coming years and decades? 那么，这对未来几年、几十年究竟意味着什么？
In-creasing unemployment? 失业增加？
The survey suggest 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.
这项调查表明，到 2021 年，机器可以把洗好的衣服叠起来。所以，如果你在洗衣店工作，是不是就该投降了？恐怕不是。
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.
能叠衣服的机器已经存在：加州大学伯克利分校的机器人学家已经开发了一种能够熟练叠好毛巾、牛仔裤和 T 恤衫的机器人。
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.
动平衡试验但必须承认，要让机器人捡起、查看、叠好一件衣服， 2010 年大约要花 19 分钟，但到2012 年，只需要 6 分多钟就能叠好一条牛仔裤和一件 T 恤衫。但最令人惊讶的或许在于，机器人可以完成袜子配对这种乏味的工作。
But despite this progress, it could be some time before robots like this are able to replace humans.
然而，尽管取得了这种进步，这样的机器人想要真正取代人类仍然需要一段时间。
"I am a bit sceptical 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.
我对某些需要实际操作的任务被机器取代的时间表持怀疑态度。
工智能教授杰里米·怀亚特( Jeremy Wyatt )说。 "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."
“在实验室里是一回事，但要让机器人在现实世界中比人类做得更好却是另一回事。
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
太极十二拍
machine. T asks that don't involve physical manipulation are easier to teach. 对机器来说， 在现实世界中操纵物体是一个无比复杂的任务， 需要搞清楚操作的对
象， 了解如何在一个随机变化的环境中进行操作。不需要实际操作的任务反而更容易掌握。 Robot mobility – things like self-driving cars and autonomous deliveries
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."
怀亚特认为，机器人的移动性——包括无人驾驶汽车和自动化配送等——大概就像
纪 90 年代初的互联网。“四处移动东西可能还要再等 10 年。”
Your friendly robot assistant 机器人好助手
While towel folders are safe for now, perhaps there is reason for truck drivers and 伯明翰大学机器人和人
还要
are
20 世
豫公网安备41160202000603
站长QQ:729038198
关于我们
投诉建议