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The human inside the machine


本文选自 1843 | 取经号原创翻译



In 1770 a chess-playing robot, built by a Hungarian inventor, caused a sensation across Europe. It took the form of a life-size wooden figure, dressed in Turkish clothing, seated behind a cabinet which had a chessboard on top. Its clockwork arm could reach out and move pieces on the board. The Mechanical Turk was capable of beating even the best players at chess. Built to amuse the empress Maria Theresa, its fame spread far beyond Vienna, and visitors to her court insisted on seeing it.

1770年,一位匈牙利发明家组装了一个会下国际象棋的机器人,在欧洲引起了一阵轰动。这是个等身木质机器人,身穿土耳其服饰,坐在橱柜后面,橱柜上摆放着棋盘,手臂依靠发条装置运作,可以来回移动棋子。这个土耳其行棋傀儡(The Mechanical Turk)甚至能打败当时最厉害的国际象棋选手。它组装之初是为了讨好匈牙利女王玛丽娅·特蕾莎,但在名声大噪远传海外后,游客们都慕名来到女王面前,要求亲眼看一看这个机器人。

its fame spread far beyond Vienna 译者并没有把Vienna这个地名直接译出来,而是选择把原文背后的含义表达出来,这样阅读的时候情感更加直观。

The Turk toured Europe in the 1780s, prompting much speculation about how it worked, and whether a machine could really think: the Industrial Revolution was just getting started, and many people were questioning to what extent machines could replace people. Nobody ever quite guessed the Turk’s secret. But it eventually transpired that there was a human chess player cleverly concealed in its innards. The apparently intelligent machine depended on a person hidden inside.


It turns out that something very similar is happening today. Just like the Turk, modern artificial-intelligence (AI) systems rely on help from unseen humans. Training a “deep learning” system involves showing it millions of examples of an input (such as photographs of animals) and telling it what the correct output is (“cat”, “dog”) in each case. Once trained, the system can then correctly identify animals in pictures it has not seen before. But the training process requires huge numbers of correctly labelled examples – and those must be created by humans.


As a result, an entire industry has sprung up, in which armies of human workers provide the data needed to train AIs. Mighty AI, for example, based in Seattle, has an online community of 300,000 people who carefully label images of street scenes to train self-driving cars. “We want cars to have human judgment,” its boss told me, “and for that we need human expertise.” The big tech firms have their own private “crowds” of online workers who do similar work.

因此,一个完整的行业应运而生。大量人工劳力投入其中,为人工智提供所需数据。例如,位于西雅图的Mighty AI拥有一个30万人的线上社区,这些人会认真地给街景图片贴上标签,用以研发自驾汽车。“我们希望汽车能够拥有人类的判断力,”该公司老板告诉我,“为此,我们需要人类的专业技能。”大型科技公司都有自己的线上“训练劳工”从事着类似的工作。

The labelling work can also be farmed out to an online “crowdworker” platform. The largest of these platforms, where people are paid to perform simple tasks that are beyond the capabilities of computers, is called Mechanical Turk. This is a direct reference to the fact that, just as with the 18th-century original, its workers provide the human expertise that powers supposedly intelligent systems.


Without realising it, you are helping out with these tasks too. When you log onto something online, you may be asked to transcribe some distorted text, or identify the images within a grid that contains street signs or vehicles. This kind of task, known as a CAPTCHA, is used to verify that you really are a human, and not a bot – because computers still cannot perform such tasks reliably. The results of these tests, millions of which are completed each day, are used by Google and others to transcribe old books, label images for self-driving vehicles or to improve mapping services.


Your online activity helps to train online systems in other ways, too. When you tag a photo on Instagram with #cat or #dog, such labels allow your images to be used for training. Google keeps track of which search results people click on, and uses that information to determine the order in which search results will be shown to other users in the future. Spotify uses the playlists created by its users to help it recommend music tracks to others. Gmail suggests replies to emails based on analysis of millions of its users’ previous replies.


Pretty much everything you do online creates a trail of data that can be used for making systems smarter. As Google, Facebook and others operate their enormous smart machines, we are all helping to power them. A clockwork chess robot from the 1770s thus foreshadowed both the modern debate about artificial intelligence – and a key aspect of making the technology work. The internet is a giant Mechanical Turk: whether we know it or not, we have all become the people inside the machine.

你在网上做的每一件事几乎都会随之创建出一组数据,用以完善相应系统。在谷歌、脸书等公司运营着他们强大的智能机器的同时,我们也在为它们添砖加瓦。因此, 18世纪70年代的会下国际象棋的发条机器人不仅预示着现代关于人工智能的辩论,同时也预示着人工智能发展的关键。互联网就是个巨大的土耳其行棋傀儡:不管我们有没有意识到,我们都成了藏在橱柜里的人

people inside the machine 原文虽然是the people in the machine,但配图中人实际上是藏在橱柜里的,所以译者选择翻译成“藏在橱柜里的人”而不是“藏在机器里的人”。

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