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每日英语新闻|双语阅读 | 你的工作还有多久会被机器取代?


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每日英语新闻|双语阅读 | 你的工作还有多久会被机器取代?
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【每日英语新闻|双语阅读 | 你的工作还有多久会被机器取代?】

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上 。 在第四次工业革命中 ， 机器将能够完成许多目前由人类完成的工作 ， 甚至可能做得更好 。 这是一个效率更高、服务更便宜的未来 ， 但也预示着广泛的失业 。
It raises a troubling question for all of us – when will a machine be able to do my job?
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找到答案 。
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 DeepMind and Zoubin Ghahramani, director of Uber's AI labs.
他们联系了许多世界领先的机器学习专家 ， 包括Facebook人工智能研究主任扬·勒库(Yann LeCun)、谷歌旗下DeepMind的穆斯塔法·苏莱曼(Mustafa Suleyman)和优步人工智能实验室主任祖宾·加哈拉马尼(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 ， 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 。


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