Douglas Hofstadter, author of the fascinating book, Gödel, Escher, Bach, is someone I’ve admired for a long time, both as an expositor and an original thinker.
But he goes badly wrong in a few places in this essay in the Atlantic Monthly. Actually, he’s said very similar things about AI in the past, so I am not really that surprised by his views here.
Hofstadter’s topic is the shallowness of Google Translate. Much of his criticism is on the mark: although Google Translate is extremely useful (and I use it all the time), it is true that it does not usually match the skills of the best human translators, or even good human translators. And he makes a strong case that translation is a difficult skill because it is not just about language, but about many facets of human experience.
(Let me add two personal anecdotes. I once saw the French version of Woody Allen’s movie Annie Hall. In the original scene, Alvy Singer (Woody Allen) is complaining that a man was being anti-semitic because he said “Did you eat?” which Alvy mishears as “Jew eat?”. This was translated as “Tu viens pour le rabe?” which Woody Allen conflates with “rabbin”, the French word for “rabbi”. The translator had to work at that one! And then there’s the French versions of the Harry Potter books, where the “Sorting Hat” became the “Choixpeau”, a truly brilliant invention on the part of the translator.]
But other things Hofstadter says are just … wrong. Or wrong-headed. For example, he says, “The bailingual engine isn’t reading anything–not in the normal human sense of the verb ‘to read.’ It’s processing text.” This is exactly the kind of complaint people made about the idea of flying machines: “A flying machine isn’t flapping its wings, so it cannot be said to fly in the normal human understanding of how birds fly.” [not an actual quote] Of course a computer doesn’t read the way a human does. It doesn’t have an iris or a cornea, it doesn’t use its finger to turn the page or make the analogous motion on a screen, and it doesn’t move its lips or write “How true!” in the margins. But what does that matter? No matter what, computer translation is going to be done differently from the exact way humans do it. The telling question is, Is the translation any good? Not, Did it translate using exactly the same methods and knowledge a human would? To be fair, that’s most of his discussion.
As for “It’s processing text”, I hardly see how that is a criticism. When people read and write and speak, they are also “processing text”. True, they process text in different ways than computers do. People do so, in part, taking advantage of their particular knowledge base. But so does a computer! The real complaint seems to be that Google Translate doesn’t currently have access to, or use extensively, the vast and rich vault of common-sense and experiential knowledge that human translators do.
Hofstadter says, “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.
“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.”
That’s a nice description — albeit maddeningly vague — of how Hofstadter thinks he does it. But where’s the proof that this is the only way to do wonderful translations? It’s a little like the world’s best Go player talking about the specific kinds of mental work he uses to prepare before a match and during it … shortly before he gets whipped by AlphaGo, an AI technology that uses completely different methods than the human.
Hofstadter goes on to say, “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.” I strongly disagree with the “end run” implication. Again, it’s like viewing flying as something that can only be achieved by flapping wings, and propellers and jet engines are just “end runs” around the true goal. This is a conceptual error. When Hofstadter says “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”, that is just an assertion. I can translate passages about war even though I’ve never been in a war. I can translate a novel written by a woman even though I’m not a woman. So I don’t need to have experienced everything I translate. If mediocre translations can be done now without the requirements Hofstadter imposes, there is just no good reason to expect that excellent translations can’t be eventually be achieved without them, at least in the same degree that Hofstadter claims.
I can’t resist mentioning this truly delightful argument against powered mechanical flight, as published in the New York Times:
The best part of this “analysis” is the date when it was published: October 9, 1903, exactly 69 days before the first successful powered flight of the Wright Brothers.
Hofstadter writes, “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…”.
But they already do think, in any reasonable sense of the word. They are already creative in a similar sense. As for words like “frightened, ecstatic, resigned, hopeful”, the main problem is that we cannot currently articulate in a suitably precise sense what we exactly mean by them. We do not yet understand our own biology enough to explain these concepts in the more fundamental terms of physics, chemistry, and neuroanatomy. When we do, we might be able to mimic them … if we find it useful to do so.
Addendum: The single most clueless comment to Hofstadter’s piece is this, from “Steve”: “Simple common sense shows that [a computer] can have zero “real understanding” in principle. Computers are in the same ontological category as harmonicas. They are *things*. As in, not alive. Not conscious.
Furthermore the whole “brain is a machine” thing is a *belief* based on pure faith. Nobody on earth has the slightest idea how consciousness actually arises in a pile of meat. Reductive materialism is fashionable today, but it is no less faith-based than Mormonism.”