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The program uses state-of-the-art AI techniques, but simple tests show that it’s a long way from real understanding.
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One Sunday, at one of our weekly salsa sessions, my friend Frank brought along a Danish guest. I knew Frank spoke Danish well, because his mother was Danish, & he had lived in Denmark as a child. As for his friend, her English was fluent, as is standard for Scandinavians. However, khổng lồ 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 lớn 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, vị this? My own experiences with machine-translation software had always led me lớn be highly skeptical of it. But my skepticism was clearly not shared by these two. Indeed, many thoughtful people are quite enamored of translation programs, finding little khổng lồ criticize in them. This baffles me.
As a language lover & an impassioned translator, as a cognitive scientist and a lifelong admirer of the human mind’s subtlety, I have followed the attempts lớn 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 lớn Norbert Wiener, a key figure in cybernetics, in which Weaver made this curious claim, today quite famous:
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 khổng lồ decode.”
Some years later he offered a different viewpoint: “No reasonable person thinks that a machine translation can ever achieve elegance và 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.
Since those days, “translation engines” have gradually improved, và recently the use of so-called deep neural nets has even suggested lớn some observers (see “The Great A.I. Awakening” by Gideon Lewis-Kraus in The new york Times Magazine, & “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 unique controllers và glitch fixers rather than producers of fresh new text.
Such a development would cause a soul-shattering upheaval in my mental life. Although I fully understand the fascination of trying lớn get machines to translate well, I am not in the least eager khổng lồ see human translators replaced by inanimate machines. Indeed, the idea frightens and revolts me. To lớn my mind, translation is an incredibly subtle art that draws constantly on one’s many years of life experience, and on one’s creative imagination. If, some “fine” day, human translators were lớn become relics of the past, my respect for the human mind would be profoundly shaken, và the shock would leave me reeling with terrible confusion và immense, permanent sadness.
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Each time I read an article claiming that the guild of human translators will soon be forced to lớn 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 lớn reassure myself that it’s not just around the corner, and finally, out of my long-standing belief that it’s important to combat exaggerated claims about artificial intelligence. & so after reading about how the old idea of artificial neural networks, recently adopted by a branch of Google called Google Brain và 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 & AlphaGo were for the venerable games of chess & Go?
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 lớn English, French, German, & Chinese.
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 lớn mean “profound,” và thus “powerful,” “insightful,” “wise.” và yet, the meaning of deep in this context comes simply from the fact that these neural networks have more layers (12, say) than 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.
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 không lấy phí 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 hotline myself “pi-lingual” (meaning the sum of all my fractional languages is a bit more than 3, which is my lighthearted way of answering the question “How many languages vị you speak?”), then how much prouder should Google Translate be, as it could điện thoại tư vấn itself “bai-lingual” (bai being Mandarin for “100”). Khổng lồ a mere pi-lingual, bai-lingualism is most impressive. Moreover, if I copy & 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.
The practical utility of Google Translate and similar technologies is undeniable, và probably 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 with not worrying about what understanding và meaning are. Could it in fact be that understanding isn’t needed in order to lớn translate well? Could an entity, human or machine, vày high-quality translation without paying attention to lớn what language is all about? khổng lồ shed some light on this question, I turn now to the experiments I did.
I began my explorations very humbly, using the following short remark, which, in a human mind, evokes a clear scenario:
