Douglas Hofstadter on the limitations of machine translation

Ashutosh Jogalekar over the 3 Quarks Daily (look in the comments) has called my attention to a recent article in which Douglas Hofstadter puts Google Translate through its paces and, surprise! surprise! finds it wanting. This is the sort of thing he does:

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

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

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:

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.

What any human reader would realize, in this case, falls under the general heading of common sense knowledge, a known failing of AI.

Hofstadter goes on more-or-less in the vein, I think–for I just skimmed over the article–until he arrived at something that captured my attention:

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.

Yes, of course. The illusion is very compelling, both with ELIZA and with Google Translate. But it is just that, an illusion. It seems that our so-called Theory of Mind module is easily fooled. We're more than willing to attribute mindful behavior at the drop of a semi-coherent word or three.

Hofstadter goes on to wax a bit poetic about what he does when he translates:

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.

And so on and so forth etc. Here he states his faith in the theoretical possibility of machines mimicking the mind:

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.

I take it that the "wrong stuff" remark is a dig principally at John Searle. He goes on:

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.

But what that last sentence? I conclude with some remarks from a paper David Hays and I wrote some years ago – incidentally, several years before Deep Blue defeated Garry Kasparov at chess:

The computer is similarly ambiguous. It is clearly an inanimate machine. Yet we interactwith it through language; a medium heretofore restricted to communication with other people.To be sure, computer languages are very restricted, but they are languages. They have words,punctuation marks, and syntactic rules. To learn to program computers we must extend ourmechanisms for natural language.

As a consequence it is easy for many people to think of computers as people. Thus JosephWeizenbaum, with considerable dis-ease and guilt, tells of discovering that his secretary "consults" Eliza—a simple program which mimics the responses of a psychotherapist—asthough she were interacting with a real person (Weizenbaum 1976). Beyond this, there areresearchers who think it inevitable that computers will surpass human intelligence and somewho think that, at some time, it will be possible for people to achieve a peculiar kind ofimmortality by "downloading" their minds to a computer. As far as we can tell suchspeculation has no ground in either current practice or theory. It is projective fantasy,projection made easy, perhaps inevitable, by the ontological ambiguity of the computer. Westill do, and forever will, put souls into things we cannot understand, and project onto them ourown hostility and sexuality, and so forth.

A game of chess between a computer program and a human master is just as profoundlysilly as a race between a horse-drawn stagecoach and a train. But the silliness is hard to see atthe time. At the time it seems necessary to establish a purpose for humankind by asserting thatwe have capacities that it does not. It is truly difficult to give up the notion that one has to add"because . . . " to the assertion "I'm important." But the evolution of technology will eventuallyinvalidate any claim that follows "because." Sooner or later we will create a technology capableof doing what, heretofore, only we could.