Is Translation an Art or a Math Problem?
Since 2009, the White House’s policy paper on innovation has included, in its list of near-term priorities, “automatic, highly accurate and real-time translation” to dismantle all barriers to international commerce and cooperation. If that were possible, a variety of local industries would lose the final advantage of their natural camouflage, and centralization — in social networking, the news, science — would accelerate geometrically. Nobody in machine translation thinks that we are anywhere close to that goal; for now, efforts in the discipline are mostly concerned with the dutiful assembly of “cargo trucks” to ferry information across linguistic borders. The hope is that machines might efficiently and cheaply perform the labor of rendering sentences whose informational content is paramount: “This metal is hot,” “My mother is in that collapsed house,” “Stay away from that snake.” Beyond its use in Google Translate, machine translation has been most successfully and widely implemented in the propagation of continent-spanning weather reports or the reproduction in 27 languages of user manuals for appliances. As one researcher told me, “We’re great if you’re Estonian and your toaster is broken.”
Warren Weaver, a founder of the discipline, conceded: “No reasonable person thinks that a machine translation can ever achieve elegance and style. Pushkin need not shudder.” The whole enterprise introduces itself in such tones of lab-coat modesty. The less modest assumption behind the aim, though, is that it’s possible to separate the informational content of a sentence from its style. Human translators, like poets, might be described as people for whom such a distinction is never clear or obvious. But human translators, today, have virtually nothing to do with the work being done in machine translation. A majority of the leading figures in machine translation have little to no background in linguistics, much less in foreign languages or literatures. Instead, virtually all of them are computer scientists. Their relationship with language is mediated via arm’s-length protective gloves through plate-glass walls.
The problem is that all texts have some purpose in mind, and what a good human translator does is pay attention to how the means serve the end — how the “style” exists in relationship to “the gist.”
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