双语 | 深度剖析谷歌翻译：一时还取代不了人类译员

随着机器翻译的不断进展，我们时常会听到或者看到有关机器翻译将会取代人类译员的观点。人类译员将很快臣服于新技术的利刃之下吗？机器翻译是否能像 Deep Blue 和 AlphaGo 那样，成为一个领域的颠覆者呢？Douglas Hofstadter 在本文中分别引用法语、德语和汉语的几个段落材料对采用人造神经网络和深度学习技术之后的谷歌翻译最新版本进行了测试。

One Sunday, at one of our weekly salsa sessions, my friend Frank brought along a Danish guest. I knew Frank spoke Danish well, since his mother was Danish, and he, as a child, had lived in Denmark. As for his friend, her English was fluent, as is standard for Scandinavians. However, to my surprise, during the evening’s chitchat it emerged that the two friends habitually exchanged emails using Google Translate. Frank would write a message in English, then run it through Google Translate to produce a new text in Danish; conversely, she would write a message in Danish, then let Google Translate anglicize it. How odd! Why would two intelligent people, each of whom spoke the other’s language well, do this? My own experiences with machine-translation software had always led me to be highly skeptical about it. But my skepticism was clearly not shared by these two. Indeed, many thoughtful people are quite enamored of translation programs, finding little to criticize in them. This baffles me.

周日，在我们每周一次的萨尔萨舞会上，我的朋友 Frank 带来了一位丹麦的客人。我知道 Frank 丹麦语说的很好，因为他母亲就是丹麦人，他小时候也在丹麦生活过一段时间。他带来的这位女性朋友也说着一口流利的英语，听上去是标准的北欧式英语。但是在晚上闲聊过程中，我才惊讶地发现他们两人平时在互通电子邮件时都习惯先使用谷歌翻译来对文本进行一下转换再发送给对方。Frank 会用英文写一封邮件，然后将邮件内容复制、粘贴到谷歌翻译，生成一个新的丹麦语版本，发送给他的朋友。而反过来，他的这位朋友也会先用丹麦语写一封邮件，然后复制、粘贴到谷歌翻译，生成一个新的英语版本。这也太奇怪了吧！为什么这么聪明的两个人，两个都能讲好对方语言的人要这样做呢？就我个人在机器翻译软件方面的体验来说，我一直对这些软件持怀疑态度。但显然，他们二人并没有像我这样的质疑。事实上，许多很有想法的人都十分迷恋这些翻译程序，在他们看来，这些翻译程序没什么可以指责的地方。这令我感到非常困惑。

As a language lover and an impassioned translator, as a cognitive scientist and a lifelong admirer of the human mind’s subtlety, I have followed the attempts to mechanize translation for decades. When I first got interested in the subject, in the mid-1970s, I ran across a letter written in 1947 by the mathematician Warren Weaver, an early machine-translation advocate, to Norbert Wiener, a key figure in cybernetics, in which Weaver made this curious claim, today quite famous:

作为一名语言爱好者，一位饱含激情的翻译家，一名认知科学家，同时也是人类大脑忠实的崇拜者，我对机器翻译的关注最早可以追溯到几十年前。我第一次对机器翻译这一话题感兴趣的时候，还是七十年代中期，当时我看到了数学家 Warren Weaver（也是机器翻译的早期倡导者）在 1947 年写给 Norbert Wiener（控制论的创始人）的一封信。Weaver 在信中提出了一个有趣的说法，这段话在今天已经广为流传：

When I look at an article in Russian, I say, “This is really written in English, but it has been coded in some strange symbols. I will now proceed to decode.”

“当我看到一篇用俄语写成的文章时，我可以说，‘这篇文章其实是用英语写的，只不过用一种奇怪的符号加密了而已，我现在将对它进行解码。’”

Some years later he offered a different viewpoint: “No reasonable person thinks that a machine translation can ever achieve elegance and style. Pushkin need not shudder.” Whew! Having devoted one unforgettably intense year of my life to translating Alexander Pushkin’s sparkling novel in verse Eugene Onegin into my native tongue (that is, having radically reworked that great Russian work into an English-language novel in verse), I find this remark of Weaver’s far more congenial than his earlier remark, which reveals a strangely simplistic view of language. Nonetheless, his 1947 view of translation-as-decoding became a credo that has long driven the field of machine translation.

几年之后，他又提出了一个不同的观点：“只要你是理性的，就绝不会认为机器翻译能达到风、雅、颂的效果。普希金不必为之战栗了。”我自己曾用一年的时间想将亚历山大·普希金那部著名的诗体小说《尤金·奥涅金》翻译成我的母语（也就是说，将这部伟大的俄语作品转变成一部英文小说），有过这样难忘的经历之后，我不得不说，Weaver 后来说的这句话显然比他之前的那番言论更为贴近事实。尽管如此，他在 1947 年发表的将翻译看作是解码的观点长期以来一直是推动机器翻译领域发展的信条所在。

Since those days, “translation engines” have gradually improved, and recently the use of so-called “deep neural nets” has even suggested to some observers (see “The Great AI Awakening” by Gideon Lewis-Kraus in The New York Times Magazine, and “Machine Translation: Beyond Babel” by Lane Greene in The Economist) that human translators may be an endangered species. In this scenario, human translators would become, within a few years, mere quality controllers and glitch fixers, rather than producers of fresh new text.

从那之后，“翻译引擎”逐渐有所发展，最近由于“深层神经网络”的应用让一些观察家们甚至产生了这样的感觉（见《纽约时报》Gideon Lewis-Kraus 发表的《The Great AI Awakening》一文以及《经济学人》Lane Greene 的《Machine Translation: Beyond Babel》一文），他们认为人类翻译员可能会成为濒危职业类型。这样下去，人类翻译员在几年之内就会转变为翻译文本质量控制和错误修复人员，而不再负责产出新的翻译文本。

Such a development would cause a soul-shattering upheaval in my mental life. Although I fully understand the fascination of trying to get machines to translate well, I am not in the least eager to see human translators replaced by inanimate machines. Indeed, the idea frightens and revolts me. To my mind, translation is an incredibly subtle art that draws constantly on one’s many years of experience in life, and on one’s creative imagination. If, some “fine” day, human translators were to become relics of the past, my respect for the human mind would be profoundly shaken, and the shock would leave me reeling with terrible confusion and immense, permanent sadness.

这样的改变会在我们的精神世界引起巨大的震动。虽然我完全了解他们尝试让机器翻译发挥最大魅力的心情所在，但我并不急于看到人类译员被冷冰冰的机器所取代。确实，他们的这种想法让我感到恐惧，并且也让我反感。在我看来，翻译是一种奇妙的艺术形式，需要依赖人类译员多年的生活经验，需要他们发挥创造性的想象力来完成。如果说，人类译员未来只能成为一种历史文物般的存在，那我对人类头脑和思维的敬重之情将会被彻底地撼动，这种冲击会让我长时间的困惑，陷入无边又无尽的悲伤之中。

Each time I read an article claiming that the guild of human translators will soon be forced to bow down before the terrible swift sword of some new technology, I feel the need to check the claims out myself, partly out of a sense of terror that this nightmare just might be around the corner, more hopefully out of a desire to reassure myself that it’s not just around the corner, and finally, out of my longstanding belief that it’s important to combat exaggerated claims about artificial intelligence. And so, after reading about how the old idea of artificial neural networks, recently adopted by a branch of Google called Google Brain, and now enhanced by “deep learning,” has resulted in a new kind of software that has allegedly revolutionized machine translation, I decided I had to check out the latest incarnation of Google Translate. Was it a game changer, as Deep Blue and AlphaGo were for the venerable games of chess and Go?

每当我看到一些文章，宣称人类译员将很快臣服于新技术的利刃之下时，我就会感觉自己有必要去检验一下这些说法到底是不是真的。一方面是由于害怕这一噩梦会马上到来，另一方面则是希望检验之后能让自己放心，这种改变并不会很快发生，最后也是因为我认为有必要回击一下长期以来关于人工智能技术的各种夸大其词。我了解到谷歌内部的 Google Brain 最近采用了人造神经网络这一传统概念和想法，并利用“深度学习”技术，生成了一款新的软件，宣称能够颠覆机器翻译。于是，我认为必须去会一会谷歌翻译的最新化身，它会像 Deep Blue（1997 年 IBM Deep Blue 击败国际象棋冠军）和 AlphaGo那样，成为一个领域的颠覆者吗？

I learned that although the older version of Google Translate can handle a very large repertoire of languages, its new deep-learning incarnation at the time worked for just nine languages. (It’s now expanded to 96.) Accordingly, I limited my explorations to English, French, German, and Chinese.

旧版本的谷歌翻译可以处理大量的语言类型，但最新的深度学习翻译版本目前仅适用于九种语言。因此，我将我的检验内容限制在英语、法语、德语和中文这四种语言范围之内。

Before showing my findings, though, I should point out that an ambiguity in the adjective “deep” is being exploited here. When one hears that Google bought a company called DeepMind whose products have “deep neural networks” enhanced by “deep learning,” one cannot help taking the word “deep” to mean “profound,” and thus “powerful,” “insightful,” “wise.” And yet, the meaning of “deep” in this context comes simply from the fact that these neural networks have more layers (12, say) than do older networks, which might have only two or three. But does that sort of depth imply that whatever such a network does must be profound? Hardly. This is verbal spinmeistery.

在进一步探讨我的发现之前，我想先指出的一点是，我们应该注意一下“深度（深层）”这一形容词可能会导致的歧义问题。例如，在我们听说谷歌收购了一家名为 DeepMind 的公司，这家公司的产品具有基于“深度学习”的“深层神经网络”。我们听到这里，可能会不由自主的联想到“深远”、“深刻”、“强大”等形容词。但其实，这种语境下的“深度（深层）”只是说这些神经网络与之前的网络相比，层次更多。现在可能是 12 层，而以前只有两三层。但是，这样的深层是否意味着这样的网络就一定是深远的呢？并非这样，这只是一种语言上的使用技巧罢了。

I am very wary of Google Translate, especially given all the hype surrounding it. But despite my distaste, I recognize some astonishing facts about this bête noire of mine. It is accessible for free to anyone on earth, and will convert text in any of roughly 100 languages into text in any of the others. That is humbling. If I am proud to call myself “pi-lingual” (meaning the sum of all my fractional languages is a bit over 3, which is my lighthearted way of answering the question “How many languages do you speak?”), then how much prouder should Google Translate be, since it could call itself “bai-lingual” (“bai” being Mandarin for 100). To a mere pilingual, bailingualism is most impressive. Moreover, if I copy and paste a page of text in Language A into Google Translate, only moments will elapse before I get back a page filled with words in Language B. And this is happening all the time on screens all over the planet, in dozens of languages.

尽管宣传很多，造势也很高，但我对谷歌翻译的态度一直比较谨慎。虽然我对它有些反感，但我不得不承认这个于我如“眼中钉”一般的存在确实有一些让人感到十分惊叹的亮点。所有人都可以免费使用，并且可以将 100 种语言中的任何一种语言转化成另外的任何一种语言。单这一点就十分值得骄傲了。如果说我为自己会说三种以上的语言而自豪的话，那谷歌翻译掌握了 100 种语言又该有多自豪！并且，如果我将语言 A 的文字内容复制粘贴到谷歌翻译栏中，只需很短的时间就能得到翻译到语言 B 的文本。

The practical utility of Google Translate and similar technologies is undeniable, and probably it’s a good thing overall, but there is still something deeply lacking in the approach, which is conveyed by a single word: understanding. Machine translation has never focused on understanding language. Instead, the field has always tried to “decode”—to get away without worrying about what understanding and meaning are. Could it in fact be that understanding isn’t needed in order to translate well? Could an entity, human or machine, do high-quality translation without paying attention to what language is all about? To shed some light on this question, I turn now to the experiments I made.

谷歌翻译和类似技术的实用性毋庸置疑，总体来说，这可能是一件好事，但其中也严重缺失了一些东西，如果用一个词来概括就是：理解。机器翻译从来都不是去理解语言，而是一直在试图对语言进行“解码”，想不通过理解和意义就能达到翻译目的。要想翻译好，可能不需要理解吗？无论是人类还是机器，要想产出高质量的翻译，可能不去关注语言的意义吗？为了更好地说明这个问题，我先来展示一下我所做的实验。

I began my explorations very humbly, using the following short remark, which, in a human mind, evokes a clear scenario:

我先用一个非常简短的描述句式开始了这一实验，看到这一句话，能够让我们在脑海中形成一幅清晰的画面：

In their house, everything comes in pairs. There’s his car and her car, his towels and her towels, and his library and hers.

在他（她）们家，什么东西都是成对的：有他的车，也有她的车；有他的毛巾，也有她的毛巾；有他的书屋，也有她的书屋。

The translation challenge seems straightforward, but in French (and other Romance languages), the words for “his” and “her” don’t agree in gender with the possessor, but with the item possessed. So here’s what Google Translate gave me:

这一翻译任务看上去似乎很简单，但在法语（以及其他罗曼语族）里，“他的”和“她的”对应的单词并不是与所有者性别一致，而是与名词保持一致。下文就是谷歌翻译到法语之后的内容：

Dans leur maison, tout vient en paires. Il y a sa voiture et sa voiture, ses serviettes et ses serviettes, sa bibliothèque et les siennes.

The program fell into my trap, not realizing, as any human reader would, that I was describing a couple, stressing that for each item he had, she had a similar one. For example, the deep-learning engine used the word “sa” for both “his car” and “her car,” so you can’t tell anything about either car-owner’s gender. Likewise, it used the genderless plural “ses” both for “his towels” and “her towels,” and in the last case of the two libraries, his and hers, it got thrown by the final “s” in “hers” and somehow decided that that “s” represented a plural (“les siennes”). Google Translate’s French sentence missed the whole point.

任何人都知道，我所说的这段话描述的是一对夫妻，强调的是他所拥有的每一样物品，他的妻子也同样有对应的一样。但是，谷歌翻译对于“他的车”和“她的车”都用了“sa”这个词，所以你无法分辨出车主的性别。同样，“他的毛巾”和“她的毛巾”用的也都是无性别复数词“ses”。而在最后他和她的书屋这一段，原文最后“hers”里面的“s”让谷歌翻译误以为这是一个复数，所以最后在目的语中以复数形式呈现出来（“les siennes”）。显而易见，谷歌翻译这次产出的法语句子完全就没有表现出原文的重点所在。

Next I translated the challenge phrase into French myself, in a way that did preserve the intended meaning. Here’s my French version:

接下来，我自己尝试将原文翻译成法语版本，前提是保留原文想要表达的意象，最终译文如下：

Chez eux, ils ont tout en double. Il y a sa voiture à elle et sa voiture à lui, ses serviettes à elle et ses serviettes à lui, sa bibliothèque à elle et sa bibliothèque à lui.

The phrase “sa voiture à elle” spells out the idea “her car,” and similarly, “sa voiture à lui” can only be heard as meaning “his car.” At this point, I figured it would be trivial for Google Translate to carry my French translation back into English and get the English right on the money, but I was dead wrong. Here’s what it gave me:

“sa voiture à elle”所代表的是“她的车”，而“sa voiture à lui”则只能译为“他的车”。然后，我想到如果用谷歌翻译将这段法语内容翻译到英语，那应该不会出什么问题，但我想的太天真了。它给我的英语译文如下：

At home, they have everything in double. There is his own car and his own car, his own towels and his own towels, his own library and his own library.

在家里，他们什么东西都是双倍的，有他自己的车和他自己的车、他自己的毛巾和他自己的毛巾，他自己的书屋和他自己的书屋。

What?! Even with the input sentence screaming out the owners’ genders as loudly as possible, the translating machine ignored the screams and made everything masculine. Why did it throw the sentence’s most crucial information away?

什么鬼东西？即便我给出的内容已经明确而又用力的表述出了物品所有者的性别，谷歌机器翻译仍然忽略了我的呐喊，将所有物品的所有者都变成了男性。它为什么要将这个句子最重要的信息丢掉？

We humans know all sorts of things about couples, houses, personal possessions, pride, rivalry, jealousy, privacy, and many other intangibles that lead to such quirks as a married couple having towels embroidered “his” and “hers.” Google Translate isn’t familiar with such situations. Google Translate isn’t familiar with situations, period. It’s familiar solely with strings composed of words composed of letters. It’s all about ultrarapid processing of pieces of text, not about thinking or imagining or remembering or understanding. It doesn’t even know that words stand for things. Let me hasten to say that a computer program certainly could, in principle, know what language is for, and could have ideas and memories and experiences, and could put them to use, but that’s not what Google Translate was designed to do. Such an ambition wasn’t even on its designers’ radar screens.

我们人类对于夫妻、房屋、个人财产这些有形事物会出于骄傲、竞争、嫉妒、隐私以及其他许多无形情绪的影响，而形成一些癖好，例如夫妻双方使用的毛巾分别绣有“他”和“她”这样的字样。谷歌翻译显然并不熟悉这种情况。或者也可以说，谷歌翻译并不熟悉任何的现实情况。谷歌翻译所熟悉的只是由单词组成的字符串，是对文本进行超快速的转换处理，而不是思考或想象，也不是记忆或理解。它甚至都不知道单词代表的是什么含义。但我想说，一个计算机程序原则上肯定可以知道语言的意义是什么，也可以让自己有想法、记忆和经验，并且用上这些，但这并不是谷歌翻译的初衷，他们的设计师甚至都没将这样的想法放在未来要实现的目标范围之内。

Well, I chuckled at these poor shows, relieved to see that we aren’t, after all, so close to replacing human translators by automata. But I still felt I should check the engine out more closely. After all, one swallow does not thirst quench.

好吧，我承认看到谷歌翻译这样拙劣的表现让我有些窃喜，因为我终于可以松一口气，机器翻译取代人类翻译的时代显然还不是近在眼前。但我感觉我应该更加细致的继续这一实验，毕竟这还没有达到让我“高枕无忧”（one swallow does not thirst quench：一口不解渴）的程度。

Indeed, what about this freshly coined phrase “One swallow does not thirst quench” (alluding, of course, to “One swallow does not a summer make”)? I couldn’t resist trying it out; here’s what Google Translate flipped back at me: “Une hirondelle n’aspire pas la soif.” This is a grammatical French sentence, but it’s pretty hard to fathom. First it names a certain bird (“une hirondelle”—a swallow), then it says this bird is not inhaling or not sucking (“n’aspire pas”), and finally reveals that the neither-inhaled-nor-sucked item is thirst (“la soif”). Clearly Google Translate didn’t catch my meaning; it merely came out with a heap of bull. “Il sortait simplement avec un tas de taureau.” “He just went out with a pile of bulls.” “Il vient de sortir avec un tas de taureaux.” Please pardon my French—or rather, Google Translate’s pseudo-French.

那对于我新造的这个短语“One swallow does not thirst quench”（正常用语是“One swallow does not a summer make”一燕不成夏），谷歌翻译表现如何呢？我忍不住想试一下，而谷歌翻译给我提供的法语版本是这样的：“Une hirondelle n’aspire pas la soif.”这个句子从语法角度来看没什么问题，但意思却让人很难理解。首先，“une hirondelle”指的是一种鸟—燕子，然后说这只鸟不吸气也不吸吮（“n’aspire pas”），最终意思就是这一既不吸气也不吸吮的物品渴了（“la soif”）。显然，谷歌翻译并没有理解我想要表达的意思，翻译出来的只是胡言乱语。

From the frying pan of French, let’s jump into the fire of German. Of late I’ve been engrossed in the book Sie nannten sich der Wiener Kreis (They Called Themselves the Vienna Circle), by the Austrian mathematician Karl Sigmund. It describes a group of idealistic Viennese intellectuals in the 1920s and 1930s, who had a major impact on philosophy and science during the rest of the century. I chose a short passage from Sigmund’s book and gave it to Google Translate. Here it is, first in German, followed by my own translation, and then Google Translate’s version. (By the way, I checked my translation with two native speakers of German, including Karl Sigmund, so I think you can assume it is accurate.)

试验了法语之后，接下来我们再来看一下德语。最近，我一直沉浸在奥地利数学家 Karl Sigmund 的著作《Sie nannten sich der Wiener Kreis》（《他们称自己是维也纳学派》）之中。这本书描述的是二十世纪二三十年代一群理想主义的维也纳知识分子，他们对二十世纪的哲学和科学产生了重大的影响。我从 Sigmund 的书中节选了一小段话，复制粘贴到了谷歌翻译栏中。详见下文，首先是德语，紧随其后的是我的翻译版本，最后是谷歌翻译的版本。（顺便说一下，我将我的版本交给过两位母语是德语的人（其中一位就是 Karl Sigmund 本尊）过目，所以我的版本应该没什么问题。）

Sigmund:

原文：

Nach dem verlorenen Krieg sahen es viele deutschnationale Professoren, inzwischen die Mehrheit in der Fakult?t, gewisserma?en als ihre Pflicht an, die Hochschulen vor den “Ungeraden” zu bewahren; am schutzlosesten waren junge Wissenschaftler vor ihrer Habilitation. Und Wissenschaftlerinnen kamen sowieso nicht in frage; über wenig war man sich einiger.

Hofstadter:

我的版本：

After the defeat, many professors with Pan-Germanistic leanings, who by that time constituted the majority of the faculty, considered it pretty much their duty to protect the institutions of higher learning from “undesirables.” The most likely to be dismissed were young scholars who had not yet earned the right to teach university classes. As for female scholars, well, they had no place in the system at all; nothing was clearer than that.

失败之后，当时占高校教职人员大多数的教授都拥有泛德主义倾向，他们认为保护高等教育机构不受“政治不良分子”的影响是他们的责任。最有可能被解雇的是那些还没有获得终身职位的年轻学者，至于女学者在体系内根本就没有什么地位，这一点是再清楚不过了。

Google Translate:

谷歌翻译版本：

After the lost war, many German-National professors, meanwhile the majority in the faculty, saw themselves as their duty to keep the universities from the “odd”; Young scientists were most vulnerable before their habilitation. And scientists did not question anyway; There were few of them.

败仗之后，许多德国国家教授，同时也是大多数高校教职人员，将保护大学远离“怪人”看作是自己的责任。还没有获得特许任教资格的那些年轻的科学家是最脆弱的群体……不知其所以然。

The words in Google Translate’s output are all English words (even if, for unclear reasons, a couple are inappropriately capitalized). So far, so good! But soon it grows wobbly, and the further down you go the wobblier it gets.

谷歌翻译输出的版本都是由正确拼写的英语单词组成，看上去还不错。但很快你就会发现，这个译文根本站不住脚，并且越往后的内容越经不起推敲。

I’ll focus first on “the ‘odd.’” This corresponds to the German “die ‘Ungeraden,’” which here means “politically undesirable people.” Google Translate, however, had a reason—a very simple statistical reason—for choosing the word “odd.” Namely, in its huge bilingual database, the word “ungerade” was almost always translated as “odd.” Although the engine didn’t realize why this was the case, I can tell you why. It’s because “ungerade”—which literally means “un-straight” or “uneven”—nearly always means “not divisible by two.” By contrast, my choice of “undesirables” to render “Ungeraden” had nothing to do with the statistics of words, but came from my understanding of the situation—from my zeroing in on a notion not explicitly mentioned in the text and certainly not listed as a translation of “ungerade” in any of my German dictionaries.

首先是“odd”这个词，对应的是德语原文中的“ungeraden”，意为“在政治领域内不受欢迎的人”。谷歌翻译显然是出于一定的理由才会选择“odd”这个词，其实也就是非常纯粹的根据统计结果来选择。也就是说，在谷歌庞大的双语数据库中，“ungeraden”这个词几乎总是会被翻译为“odd”。而我选择用“undesirables”一词来表示“ungeraden”与统计数据无关，而纯粹是基于我对语意的理解，只有这样才能对文中没有明确说出，但其实就是想这样表达的意思给传递出来。用“undesirables”来翻译文中的“ungerade”可能是你查阅任何德语字典也找不到的一个配对。

Let’s move on to the German “Habilitation,” denoting a university status resembling tenure. The English cognate word “habilitation” exists but it is super-rare, and certainly doesn’t bring to mind tenure or anything like it. That’s why I briefly explained the idea rather than just quoting the obscure word, since that mechanical gesture would not get anything across to anglophonic readers. Of course Google Translate would never do anything like this, as it has no model of its readers’ knowledge.

接下来我们看一下德语原文中“Habilitation”，这个词在文中是用于表示一种类似于终身职位的大学任教资质或者说地位。在英语中也能找到它的同源词“habilitation”，但其实这一词汇非常罕见，更不会让人联想到终身任期或者说类似的其他信息。正因为如此，我才会用一个短语来解释出这层意思，而没有直接用引用这样一个语义十分模糊的词汇，因为通过机械地引用这一方式所产出的翻译版本无法传达给英语读者准确的信息。当然，谷歌翻译不可能给出像我这样的翻译版本，因为它对读者的知识模型一无所知。

The last two sentences really bring out how crucial understanding is for translation. The 15-letter German noun “Wissenschaftler” means either “scientist” or “scholar.” (I opted for the latter, as in this context it was referring to intellectuals in general. Google Translate didn’t get that subtlety.) The related 17-letter noun “Wissenschaftlerin,” found in the closing sentence in its plural form “Wissenschaftlerinnen,” is a consequence of the gendered-ness of German nouns. Whereas the “short” noun is grammatically masculine and thus suggests a male scholar, the longer noun is feminine and applies to females only. I wrote “female scholar” to get the idea across. Google Translate, however, did not understand that the feminizing suffix “-in” was the central focus of attention in the final sentence. Since it didn’t realize that females were being singled out, the engine merely reused the word “scientist,” thus missing the sentence’s entire point. As in the earlier French case, Google Translate didn’t have the foggiest idea that the sole purpose of the German sentence was to shine a spotlight on a contrast between males and females.

下面，我们再看一下最后三句话，相信看完之后你也会明白理解对于翻译有多么的重要。由 15 个字母所组成的德语名词“Wissenschaftler” 意指“科学家”或“学者。”（我选择了后者，因为在这种语境下，它指的是一般的知识分子，这是谷歌翻译体会不到的微妙差异。）由 20 个字母组成的“Wissenschaftlerinnen”是“Wissenschaftlerin”（17个字母）的复数形式，两者之间体现的是德语名词中性别的差异。较“短”的名词在语法上是阳性的，因此表示的是一位男性学者，而长一点的名词是阴性的，代表的是女性学者。我用“female scholar”（女性学者）一词将原文要传递的意思表达了出来。但是，谷歌翻译并没有注意到阳性后缀“-in”才是这句话的重点所在，所以只是用“scientists”（科学家）一词来对应“Wissenschaftlerinnen”，也就漏掉了这句话的主要观点所在。正如上文中我所使用的那段法语一样，谷歌翻译在这里同样没有意识到，这句话的唯一目的就在于突出男女两性之间的对比效果。

Aside from that blunder, the rest of the final sentence is a disaster. Take its first half. Is “scientists did not question anyway” really a translation of “Wissenschaftlerinnen kamen sowieso nicht in frage”? It doesn’t mean what the original means—it’s not even in the same ballpark. It just consists of English words haphazardly triggered by the German words. Is that all it takes for a piece of output to deserve the label “translation”?

除去这一错误之外，最后两句的翻译也完全就是事故现场。先看“scientists did not question anyway”这句，这真的是翻译的“Wissenschaftlerinnen kamen sowieso nicht in frage”吗?英语译文所表达的根本就不是原文的意思，甚至可以说是牛头不对马嘴。这句英语译文只是根据原文德语单词逐个找到对应的英文单词拼凑到一起而已，这样的输出过程和内容难道也称得上是在翻译吗？

The sentence’s second half is equally erroneous. The last six German words mean, literally, “over little was one more united,” or, more flowingly, “there was little about which people were more in agreement,” yet Google Translate managed to turn that perfectly clear idea into “There were few of them.” We baffled humans might ask “Few of what?” but to the mechanical listener, such a question would be meaningless. Google Translate doesn’t have ideas behind the scenes, so it couldn’t even begin to answer the simple-seeming query. The translation engine was not imagining large or small amounts or numbers of things. It was just throwing symbols around, without any notion that they might symbolize something.

最后一句同样是个错误，德语原文是“这一点没什么异议”或者说“这一点再清楚不过了”，但是谷歌翻译给出的译文是“There were few of them.”（几乎没有）。这句话听上去让人一脸困惑，不禁会产生这样的疑问，“few of what？（几乎没有什么？）”但对于谷歌翻译这位机械的听者来说，这样的问题没有意义。谷歌翻译不知道这些话背后想传达的意思是什么，所以哪怕是看上去很简单的问题，它可能也回答不了。谷歌翻译只是将一种语言符号转化为另一种语言符号，而对于符号可能象征的信息和意义它却没有任何概念。

It’s hard for a human, with a lifetime of experience and understanding and of using words in a meaningful way, to realize how devoid of content all the words thrown onto the screen by Google Translate are. It’s almost irresistible for people to presume that a piece of software that deals so fluently with words must surely know what they mean. This classic illusion associated with artificial-intelligence programs is called the “eliza effect,” since one of the first programs to pull the wool over people’s eyes with its seeming understanding of English, back in the 1960s, was a vacuous phrase manipulator called eliza, which pretended to be a psychotherapist, and as such, it gave many people who interacted with it the eerie sensation that it deeply understood their innermost feelings.

对于一位有着现实生活体验、了解如何用单词组成句子来准确传达意思的人类来说，似乎很难意识到谷歌翻译在我们电脑屏幕上输出的翻译文本内容是多么空洞。人们总是习惯性认为这样一款能够流利处理单词的软件一定知道怎样去表达意思，这是人类对于人工智能项目所出现的一种典型的幻觉，被称为“Eliza 效应”（大意是指人可以过度解读机器的结果，读出原来不具有的意义）。Eliza 是 20 世纪 60 年代的一个早期人工智能项目，能通过脚本理解简单的自然语言，并能进行类似人类的互动。其中 Eliza 还假装自己是一位心理治疗师，与它互动过的许多人都认为 Eliza 确实了解他们内心最深处的感觉。

For decades, sophisticated people—even some artificial-intelligence researchers—have fallen for the eliza effect. In order to make sure that my readers steer clear of this trap, let me quote some phrases from a few paragraphs up—namely, “Google Translate did not understand,” “it did not realize,” and “Google Translate didn’t have the foggiest idea.” Paradoxically, these phrases, despite harping on the lack of understanding, almost suggest that Google Translate might at least sometimes be capable of understanding what a word or a phrase or a sentence means, or is about. But that isn’t the case. Google Translate is all about bypassing or circumventing the act of understanding language.

几十年来，哪怕是很有经验的人，甚至是一些人工智能领域的研究人员，也都掉进了 Eliza 效应的陷阱。为了确保我的读者可以避开这个陷阱，我先引用一下之前段落中我曾说过的几个短语，“谷歌翻译不明白”、“它没有意识到”以及“谷歌翻译根本没想到”。这几个短语虽然一直在反复强调谷歌翻译缺乏对句子的理解，其实这些话也表达了这样一个意思，谷歌翻译至少有时候应该去理解单词、短语或句子的意思，或者至少知道它们说的是什么。但事实并非如此，谷歌翻译一直在尝试绕过或避开去理解语言这一环节。

To me, the word “translation” exudes a mysterious and evocative aura. It denotes a profoundly human art form that graciously carries clear ideas in Language A into clear ideas in Language B, and the bridging act not only should maintain clarity, but also should give a sense for the flavor, quirks, and idiosyncrasies of the writing style of the original author. Whenever I translate, I first read the original text carefully and internalize the ideas as clearly as I can, letting them slosh back and forth in my mind. It’s not that the words of the original are sloshing back and forth; it’s the ideas that are triggering all sorts of related ideas, creating a rich halo of related scenarios in my mind. Needless to say, most of this halo is unconscious. Only when the halo has been evoked sufficiently in my mind do I start to try to express it—to “press it out”—in the second language. I try to say in Language B what strikes me as a natural B-ish way to talk about the kinds of situations that constitute the halo of meaning in question.

对我而言，“翻译”一词散发着神秘的光芒，让人可以细细品味。翻译属于一种深刻的人类艺术形式，将语言 A 中的思想清晰而又传神的传递到语言 B 中。发挥桥梁作用的译文不仅要保持语义清晰，而且要保留原作者写作的风格、遣词造句的特点和文体特征。我在翻译的时候，每次都是先仔细地阅读原文，并尽可能清晰地将原文的意思进行内化，在脑海中反复地回放。这并不是说去反复回放原文文本，而是原文的意义和想法在我的脑海中会触发各种相关的想法，创造出各种相关的场景，生成一道道光环。这一过程在很大程度上来说是一个无意识的过程，直到一道道光环充分聚集到一起，激发足够的反应，我才会开始尝试用另一种语言来自然地将它们表达出来。

I am not, in short, moving straight from words and phrases in Language A to words and phrases in Language B. Instead, I am unconsciously conjuring up images, scenes, and ideas, dredging up experiences I myself have had (or have read about, or seen in movies, or heard from friends), and only when this nonverbal, imagistic, experiential, mental “halo” has been realized—only when the elusive bubble of meaning is floating in my brain—do I start the process of formulating words and phrases in the target language, and then revising, revising, and revising. This process, mediated via meaning, may sound sluggish, and indeed, in comparison with Google Translate’s two or three seconds per page, it certainly is—but it is what any serious human translator does. This is the kind of thing I imagine when I hear an evocative phrase like “deep mind.”

简而言之，在翻译过程中，我并不是简单地将语言 A 中的单词和短语直接转变为语言 B 中的单词和短语。我的脑海中会不自觉得浮现出图像、场景和想法，联想到我自己曾经的（或在书中读过的、在电影中看过的或者在朋友那里听过的）经历。只有当这种非语言的、形象、具有现实体验性的光环形成之后，只有当那些由难以捉摸的意义所形成的泡沫在我的脑海中漂浮起来之后，我才会开始用目标语言来输出单词和短语，然后会修改、修改、再修改。这样一个通过理解原文意义来推进的过程听上去可能显得反应迟缓，与谷歌翻译那每页两到三秒的反应时间相比确实是慢了很多，但这是任何一位严谨的人类译者都会去经历的一个过程。这也是我在听到像“深度大脑”这样的词汇时会联想到的场景。

That said, I turn now to Chinese, a language that gave the deep-learning software a far rougher ride than the two European languages did. For my test material, I drew from the touching memoir Women Sa (We Three), written by the Chinese playwright and translator Yang Jiang, who recently died at 104. Her book recounts the intertwined lives of herself, her husband Qian Zhongshu (also a novelist and translator), and their daughter. It is not written in an especially arcane manner, but it uses an educated, lively Chinese. I chose a short passage and let Google Translate loose on it. Here are the results, along with my own translation (again vetted by native speakers of Chinese):

相比以上两段欧洲语言来说，中文对于这款深度学习软件的考验显然更为严峻。关于中文测试材料，我是从中国剧作家和翻译家杨绛的著作《我们仨》中节选了一段内容，并将其复制粘贴到了谷歌翻译栏。下文依次是《我们仨》的原文段落、我翻译的版本（请母语为汉语的人进行过审核）以及谷歌翻译给出的版本：

Yang:

杨绛原文：

锺书到清华工作一年后，调任毛选翻译委员会的工作，住在城里，周末回校。 他仍兼管研究生。

毛选翻译委员会的领导是徐永煐同志。介绍锺书做这份工作的是清华同学乔冠华同志。

事定之日，晚饭后，有一位旧友特雇黄包车从城里赶来祝贺。客去后，锺书惶恐地对我说：

他以为我要做“南书房行走”了。这件事不是好做的，不求有功，但求无过。

Hofstadter:

我的翻译版本：

After Zhongshu had worked at Tsinghua University for a year, he was transferred to the committee that was translating selected works of Chairman Mao. He lived in the city, but each weekend he would return to school. He also was still supervising his graduate students.

The leader of the translation committee of Mao’s works was Comrade Xu Yongying, and the person who had arranged for Zhongshu to do this work was his old Tsinghua schoolmate, Comrade Qiao Guanhua.

On the day this appointment was decided, after dinner, an old friend specially hired a rickshaw and came all the way from the city just to congratulate Zhongshu. After our guest had left, Zhongshu turned to me uneasily and said:

“He thought I was going to become a ‘South Study special aide.’ This kind of work is not easy. You can’t hope for glory; all you can hope for is to do it without errors.”

Google Translate:

谷歌翻译版本：

After a year of work at Tsinghua, he was transferred to the Mao Translating Committee to live in the city and back to school on weekends. He is still a graduate student.

The leadership of the Mao Tse Translation Committee is Comrade Xu Yongjian. Introduction to the book to do this work is Tsinghua students Qiao Guanhua comrades.

On the day of the event, after dinner, an old friend hired a rickshaw from the city to congratulate. Guest to go, the book of fear in the book said to me:

He thought I had to do “South study walking.” This is not a good thing to do, not for meritorious service, but for nothing.

I’ll briefly point out a few oddities. First of all, Google Translate never refers to Zhongshu by name, although his name (“锺书”) occurs three times in the original. The first time, the engine uses the pronoun “he”; the second time around it says “the book”; the third time it says “the book of fear in the book.” Go figure!

我来简短地指出谷歌译本与原文存在的一些不符之处。首先，谷歌翻译版本一次也没有提到“钟书”，而这一人名在原文中出现了三次。在谷歌译文中，第一次用“he”来指代，第二次翻译成了“book”，第三次则是“the book of fear in the book”。简直让人啼笑皆非！

A second oddity is that the first paragraph clearly says that Zhongshu is supervising graduate students, whereas Google Translate turns him into a graduate student.

第二个不符之处是原文清楚地表明，钱钟书是在监管研究生，而谷歌翻译却直接将他变成了研究生。

A third oddity is that in the phrase “Mao Tse Translation Committee,” one third of Chairman Mao Tse Tung’s name fell off the train.

第三处是“Mao Tse Translation Committee”这一短语，漏掉了毛泽东主席（Chairman Mao Tse Tung）名字的最后一个字。

A fourth oddity is that the name “Yongying” was replaced by “Yongjian.”

第四处是原文的“徐永煐”（Xu Yongying）被翻译成了“Xu Yongjian”。

A fifth oddity is that “after our guest had left” was reduced to “guest to go.”

第五处是“客去后”被翻译成了“guest to go”（客人要走）。

A sixth oddity is that the last sentence makes no sense at all.

第六处是最后一句话想要表达什么意思根本讲不通。

Well, these six oddities are already quite a bit of humble pie for Google Translate to swallow, but let’s forgive and forget. Instead, I’ll focus in on just one confusing phrase I ran into—a five-character phrase in quotation marks in the last paragraph (“南书房行走”). Character for character, it might be rendered as “south book room go walk,” but that jumble is clearly unacceptable, especially as the context requires it to be a noun. Google Translate invented “South study walking,” which is not helpful.

这六处错误对于谷歌翻译来说已经够尴尬的了，但在这里我们没必要横加指责。我想要同你们探讨一个让我感到很困惑的短语“南书房行走”，这一短语由五个汉字组成，逐字理解，可能是“south book room go walk”，但这样胡乱拼凑到一起显然表达不了原文的意思，并且尤其需要注意的一点是，在原文中的“南书房行走”是作为一个名词形式存在。谷歌翻译发明出了“South study walking”这样的说法，显然对于读者来说仍然是不知其所以然的效果。

Now I admit that the Chinese phrase was utterly opaque to me. Although literally it looked like it meant something about moving about on foot in a study on the south side of some building, I knew that couldn’t be right; it made no sense in the context. To translate it, I had to find out about something in Chinese culture that I was ignorant of. So where did I turn for help? To Google! (But not to Google Translate.) I typed in the Chinese characters, surrounded them by quote marks, then did a Google search for that exact literal string. Lickety-split, up came a bunch of web pages in Chinese, and then I painfully slogged my way through the opening paragraphs of the first couple of websites, trying to figure out what the phrase was all about.

我不得不承认，这句话对我来说也很难理解。虽然从字面意思上看，似乎是指在某个建筑物南侧的书房来行走，但我知道应该不是指的这个意思，因为根据上下文语境这样讲不通。因此，要想准确地翻译这句话，我需要去挖掘这背后中国文化中我不了解的一些东西。那我该去哪里寻找答案呢？当然是谷歌（但绝不是谷歌翻译）。我将南书房行走这五个汉字输入谷歌搜索栏，并加了双引号，然后开始搜索。立马就出现了一大堆中文网页，然后我极为费劲地试图去理解前几个网页的开头部分信息，试图弄清楚这个五个字的含义。

I discovered the term dates back to the Qing Dynasty (1644–1911), and refers to an intellectual assistant to the emperor, whose duty was to help the emperor (in the imperial palace’s south study) stylishly craft official statements. The two characters that seem to mean “go walk” actually form a chunk denoting an aide. And so, given that information supplied by Google Search, I came up with my phrase “South Study special aide.”

我发现“南书房行走”这一术语其实可以追溯到清朝时期，并不是指官职，而是由御用知识份子翰林担任的一个“差使”，职责是帮助皇帝（在皇宫的南书房）起草“特颁诏旨”。这样一来便容易理解字面意思看是“go walk”的两个字其实是指助手。所以，根据谷歌搜索提供的信息，我用“South Study special aide”（南书房特别的助手）来表达原文的意思。

It’s too bad Google Translate couldn’t avail itself of the services of Google Search as I did, isn’t it? But then again, Google Translate can’t understand web pages, although it can translate them in the twinkling of an eye. Or can it? Below I exhibit the astounding piece of output text that Google Translate super-swiftly spattered across my screen after being fed the opening of the website that I got my info from:

谷歌翻译无法像我这样利用到谷歌搜索这一服务中的信息，真的是太遗憾了。虽然谷歌翻译可以即时翻译网页内容，但它并不理解网页中的信息。下文是我在刚才搜索“南书房行走”时浏览的网页信息经过谷歌翻译之后的版本：

“South study walking” is not an official position, before the Qing era this is just a “messenger,” generally by the then imperial intellectuals Hanlin to serve as. South study in the Hanlin officials in the “select chencai only goods and excellent” into the value, called “South study walking.” Because of the close to the emperor, the emperor’s decision to have a certain influence. Yongzheng later set up “military aircraft,” the Minister of the military machine, full-time, although the study is still Hanlin into the value, but has no participation in government affairs. Scholars in the Qing Dynasty into the value of the South study proud. Many scholars and scholars in the early Qing Dynasty into the south through the study.

Is this actually in English? Of course we all agree that it’s made of English words (for the most part, anyway), but does that imply that it’s a passage in English? To my mind, since the above paragraph contains no meaning, it’s not in English; it’s just a jumble made of English ingredients—a random word salad, an incoherent hodgepodge.

这是英语吧？这个确实是，我们都赞同上述段落是由英语单词构成（大部分是），但这是一个英文段落吗？在我看来，由于这一段落绝大部分内容看上去让人摸不着头脑，所以这并不是一个英文段落，只是由随机的单词沙拉这一原料组成的一盘零散的大杂烩而已。

In case you’re curious, here’s my version of the same passage (it took me hours):

接下来是我用了几个小时的时间，对同样内容所做的英语译文，供你参考：

The nan-shufang-xingzou (“South Study special aide”) was not an official position, but in the early Qing Dynasty it was a special role generally filled by whoever was the emperor’s current intellectual academician. The group of academicians who worked in the imperial palace’s south study would choose, among themselves, someone of great talent and good character to serve as ghostwriter for the emperor, and always to be at the emperor’s beck and call; that is why this role was called “South Study special aide.” The South Study aide, being so close to the emperor, was clearly in a position to influence the latter’s policy decisions. However, after Emperor Yongzheng established an official military ministry with a minister and various lower positions, the South Study aide, despite still being in the service of the emperor, no longer played a major role in governmental decision-making. Nonetheless, Qing Dynasty scholars were eager for the glory of working in the emperor’s south study, and during the early part of that dynasty, quite a few famous scholars served the emperor as South Study special aides.

Some readers may suspect that I, in order to bash Google Translate, cherry-picked passages on which it stumbled terribly, and that it actually does far better on the vast majority of passages. Though that sounds plausible, it’s not the case. Nearly every paragraph I selected from books I’m currently reading gave rise to translation blunders of all shapes and sizes, including senseless and incomprehensible phrases, as above.

有些读者可能会怀疑我是为了抨击谷歌翻译，故意找了一些非常难懂的段落，他们认为其实谷歌翻译在大部分段落上的表现其实比这要好很多。这听上去似乎合理，但事实并非如此。我从当下看的书中选择了好多个段落进行测试，几乎每一段都会出现形式不一、大小各异的翻译错误，其中也包括上文所述的完全不明所以、无法理解的句子。

Of course I grant that Google Translate sometimes comes up with a series of output sentences that sound fine (although they may be misleading or utterly wrong). A whole paragraph or two may come out superbly, giving the illusion that Google Translate knows what it is doing, understands what it is “reading.” In such cases, Google Translate seems truly impressive—almost human! Praise is certainly due to its creators and their collective hard work. But at the same time, don’t forget what Google Translate did with these two Chinese passages, and with the earlier French and German passages. To understand such failures, one has to keep the eliza effect in mind. The bailingual engine isn’t reading anything—not in the normal human sense of the verb “to read.” It’s processing text. The symbols it’s processing are disconnected from experiences in the world. It has no memories on which to draw, no imagery, no understanding, no meaning residing behind the words it so rapidly flings around.

当然，我也承认谷歌翻译有时也会产出一系列看上去不错的英语句子（尽管与原文意思可能会发现存在理解偏差或完全错误），有时看上去一段甚至两段的翻译内容都很棒，让人产生一种错觉，错以为谷歌翻译理解自己所“读取”的内容。这种情况下，人们就会对谷歌翻译刮目相看，认为它几乎可以与人类相媲美。对于谷歌翻译的创造者和背后所付出的集体努力我们确实应该表示赞扬，但与此同时，也不要忘了谷歌翻译在这两个中文段落，还有之前的法语和德语段落的翻译表现。要想理解这样的不足，我们就必须时刻提醒自己注意 Eliza 效应。谷歌翻译并不是像正常意义上的人类那样来“阅读”文本，它只是在处理文本。它所处理的符号与现实世界的体验是分离开来的，在它迅速转换单词之时，没有任何现实体验可以提取、没有画面去形成，没有理解，也没有意义。

A friend asked me whether Google Translate’s level of skill isn’t merely a function of the program’s database. He figured that if you multiplied the database by a factor of, say, a million or a billion, eventually it would be able to translate anything thrown at it, and essentially perfectly. I don’t think so. Having ever more “big data” won’t bring you any closer to understanding, since understanding involves having ideas, and lack of ideas is the root of all the problems for machine translation today. So I would venture that bigger databases—even vastly bigger ones—won’t turn the trick.

一位朋友问我谷歌翻译的水平是不是不仅仅由程序数据库来决定。他认为，如果能将数据库扩大 100 万倍甚至十亿被，那就应该能够翻译任何内容，并且译文基本上能达到完美的水平。对他的这一观点，我并不赞同。拥有更多的“大数据”并不会让你在理解层面有任何进步，因为理解需要思想发挥作用，而缺乏思想是当下机器翻译所有问题的根源所在。所以，我敢说，更大的数据库也解决不了问题。

Another natural question is whether Google Translate’s use of neural networks—a gesture toward imitating brains—is bringing us closer to genuine understanding of language by machines. This sounds plausible at first, but there’s still no attempt being made to go beyond the surface level of words and phrases. All sorts of statistical facts about the huge databases are embodied in the neural nets, but these statistics merely relate words to other words, not to ideas. There’s no attempt to create internal structures that could be thought of as ideas, images, memories, or experiences. Such mental etherea are still far too elusive to deal with computationally, and so, as a substitute, fast and sophisticated statistical word-clustering algorithms are used. But the results of such techniques are no match for actually having ideas involved as one reads, understands, creates, modifies, and judges a piece of writing.

另一个问题是谷歌翻译用到了神经网络之后是否能让机器翻译更接近于理解语言。一听上去似乎也有道理，但其实机器翻译仍未试图去超越单词和短语层面。形成庞大数据库的各种统计事实都体现在了神经网络中，但这些统计事实仅仅是将单词与其他单词联系到一起，并不是将单词与想法联系到一起。没有尝试去创造可以被看作是想法、图像、记忆或体验的内部结构，这些属于人类的心理活动仍然很难从计算层面上来体现，于是他们使用快速而复杂的统计单词聚类算法来作为替代物。但这种形式下出来的结果与人类在阅读、理解、创造、修改和评判一篇文章时所汇成的最终想法并不相符。

Despite my negativism, Google Translate offers a service many people value highly: It effects quick-and-dirty conversions of meaningful passages written in language A into not necessarily meaningful strings of words in language B. As long as the text in language B is somewhat comprehensible, many people feel perfectly satisfied with the end product. If they can “get the basic idea” of a passage in a language they don’t know, they’re happy. This isn’t what I personally think the word “translation” means, but to some people it’s a great service, and to them it qualifies as translation. Well, I can see what they want, and I understand that they’re happy. Lucky them!

尽管我对谷歌翻译持否定态度，但谷歌翻译提供的服务确实也让许多人给出了很高的评价：它能将 A 语言的表意段落快速转换为由 B 语言单词串所组成的文本。只要 B 语言文本有些是可以理解的，这就足以让许多人对这款产品感到满意。如果他们能通过谷歌翻译对一段他们不认识的语言段落所讲的大体意思有所了解，那他们就会感到很高兴。这虽然不符合我个人对“翻译”这一词的看法，但对很多人来说这是一项很好的服务，对他们来说，这就是翻译。我知道他们的需求所在，我也理解他们这份高兴和满意。只能说，他们很幸运！

I’ve recently seen bar graphs made by technophiles that claim to represent the “quality” of translations done by humans and by computers, and these graphs depict the latest translation engines as being within striking distance of human-level translation. To me, however, such quantification of the unquantifiable reeks of pseudoscience, or, if you prefer, of nerds trying to mathematize things whose intangible, subtle, artistic nature eludes them. To my mind, Google Translate’s output today ranges all the way from excellent to grotesque, but I can’t quantify my feelings about it. Think of my first example involving “his” and “her” items. The idealess program got nearly all the words right, but despite that slight success, it totally missed the point. How, in such a case, should one “quantify” the quality of the job? The use of scientific-looking bar graphs to represent translation quality is simply an abuse of the external trappings of science.

我最近看到一些由技术爱好者们制作的一些条形图，他们声称这些图表反映的是人类和机器翻译的“质量”，并认为最新的翻译引擎与人类翻译之间的距离已经缩小到令人惊叹的程度。但是对我来说，这是在对无法量化的事物去进行量化的一种伪科学，或者说是一群书呆子在将一些他们无法理解的无形的、微妙的、艺术性的东西进行数学化计算。在我看来，谷歌翻译现在的产出质量参差不齐，有很优秀的译文，也有荒诞不经的译文，但我无法将我对此的感受来进行量化。想想我在本文中举的第一个例子，其中有“他的”和“她的”的那段法语材料，机器翻译对每一个单词几乎都可以实现正确地对应，但尽管如此，原文最重要的意思却完全没有表达出来。在这样的情况下，又该怎样对它的翻译质量进行“量化”呢？用看上去似乎很科学的条形图来反映翻译质量只不过是对科学外在表象的滥用罢了。

Let me return to that sad image of human translators, soon outdone and outmoded, gradually turning into nothing but quality controllers and text tweakers. That’s a recipe for mediocrity at best. A serious artist doesn’t start with a kitschy piece of error-ridden bilgewater and then patch it up here and there to produce a work of high art. That’s not the nature of art. And translation is an art.

让我们再回到文章开篇所提到的悲惨翻译者形象上来，看上去很快就被淘汰，未来只能沦为质量检验者和文字校改者的翻译者形象。这充其量也只能是形容那些平庸的翻译者。一位严肃的艺术家并不会一开始给出一个错误泛滥的粗糙版本，然后这缝缝那补补，这样产出不了高水准的艺术作品。这不是艺术的本质，而翻译就是一门艺术。

In my writings over the years, I’ve always maintained that the human brain is a machine—a very complicated kind of machine—and I’ve vigorously opposed those who say that machines are intrinsically incapable of dealing with meaning. There is even a school of philosophers who claim computers could never “have semantics” because they’re made of “the wrong stuff” (silicon). To me, that’s facile nonsense. I won’t touch that debate here, but I wouldn’t want to leave readers with the impression that I believe intelligence and understanding to be forever inaccessible to computers. If in this essay I seem to come across sounding that way, it’s because the technology I’ve been discussing makes no attempt to reproduce human intelligence. Quite the contrary: It attempts to make an end run around human intelligence, and the output passages exhibited above clearly reveal its giant lacunas.

在我多年的创作生涯中，我始终认为人脑是一台机器，一台非常复杂的机器，而且对于那种认为机器本质上无法把控意义的看法，我表示强烈反对。甚至还有一个哲学派别声称计算机永远不会“理解语义”，因为它们是由“错误地东西”（硅）构成的。在我看来，这只是一些不经过大脑就说出的废话而已。在这里，我不会就这一论点展开辩论，但我不想让读者产生这样的印象，不想让读者误认为我的观点是电脑无法获得智慧，无法实现理解的层面。如果在这篇文章中，我让你产生了这样的误解，那是因为我一直在讨论机器翻译并没有试图去重现人类的智慧。并且恰恰相反，它试图绕过人类智慧，而上文我所展示的谷歌翻译输出文本也清楚地暴露出了它所存在的巨大缺陷。

From my point of view, there is no fundamental reason that machines could not, in principle, someday think, be creative, funny, nostalgic, excited, frightened, ecstatic, resigned, hopeful, and, as a corollary, able to translate admirably between languages. There’s no fundamental reason that machines might not someday succeed smashingly in translating jokes, puns, screenplays, novels, poems, and, of course, essays like this one. But all that will come about only when machines are as filled with ideas, emotions, and experiences as human beings are. And that’s not around the corner. Indeed, I believe it is still extremely far away. At least that is what this lifelong admirer of the human mind’s profundity fervently hopes.

就我个人认为，并没有什么根本的依据，能让我们断言机器未来也不会有创意，未来也无法变得有趣、怀旧、激动、恐惧、狂喜、充满希望，从而断言机器翻译未来也无法实现两种语言之间生动的翻译。同样，也没有什么根本的原因能让我们否定掉机器翻译未来可能成功翻译笑话、双关语、电影剧本、小说以及诗歌的潜力。但是，只有当机器翻译像人一样充满想法、感情和经历时，我所说的这些才会实现。而现在，这些还无法实现，并且也绝非转角就能遇到爱的距离。事实上，我认为要实现这些，还有很长的路要走，至少这是我这位对于人类思维的终极崇拜者所热切期盼的一个结果。

When, one day, a translation engine crafts an artistic novel in verse in English, using precise rhyming iambic tetrameter rich in wit, pathos, and sonic verve, then I’ll know it’s time for me to tip my hat and bow out.

有一天，如果一个翻译引擎能够将一部诗词以精确地抑扬格五音步精确地翻译出来，传达出原文的智慧、悲怆和文体神韵，那我就知道向机器翻译脱帽致敬的时候终于到了。

原标题：深度剖析谷歌翻译：浅薄而冰冷，一时还取代不了人类译员

英文来源：The Atlantic

中文来源：36氪

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