One of the pleasures of this blog has been/is the occasional encounter with an important book. The top 4 were probably:
To this distinguished list I want to add Louder than Words: the new science of how the mind makes meaning by Benjamin K. Bergen. It is as important a book as I have found on this blog. Maybe it is even one of the most important I've read in a lifetime of reading about language. A statement like that, of course, tips my hand. This book vindicates a great deal that I have argued over the years on this blog: words work by piloting attention; language is a tool for sharing perceptions; to start speaking our ancestors did not have to get smarter, just more social.
It is not that Bergen says these things. He is not concerned with why we speak or what it accomplishes. How we manage it is his subject. But that's what makes the book so pleasing. It is a report from an experimental scientist full of data that happens to agree (more or less) with my own lines of inquiry.
Bergen is an associate professor of cognitive science at the University of California (San Diego) and a protégé of George Lakoff, a cognitive linguist at UC Berkeley. Lakoff is co-author of a fine book that appeared in 1980, Metaphors We Live By. I read the book more than 30 years ago, but as I recall it's thesis is that metaphors are critical to understanding any abstract statement. Metaphors are more than rhetorical devices. Without them we would only be able to speak about purely concrete subjects.
It might seem a little surprising, therefore, that most of Bergen's new book is about how we understand purely concrete sentences like The polar bear hid his nose. The approach turns out to have good sense behind it. It provides a very clear foundation for the assertion that concrete statements are understood by simulating the perceptions and motions they describe. Metaphors build on that perceptual layer. Abstract statements then build on the metaphorical layer. Bergen discusses all three types of statements but his evidence is richest when he reports his many experiments on concrete sentences.
Lakoff and Bergen have a common enemy, the theory of Mentalese, most thoroughly explored by Stephen Pinker but assumed by many others as well.
Mentalese defines language as a system of symbols organized by syntactic rules. Its great strength is that this definition exactly matches computer languages. To program a machine to use a language, all you need is a dictionary and a grammar. The famous Chomsky hierarchy of languages seems to take it for granted that natural languages (human languages) fall somewhere among this listing of types of machine languages.
Bergen's thesis rejects mentalese. In place of a dictionary, it places perceptions and motor activity. Take the sentence The polar bear hid its nose. To interpret it the mentalese way, a machine or brain looks up the various words in the dictionary and uses syntactical rules to divine the abstract relationships between the words. Bergen says no, as we read the sentence we activate the very same neurons in the brain that we use when we see a polar bear or a picture of a polar bear. For the nose, we active our nose perceiving neurons. For the verb to hide, we activate the motor neurons used to hide a nose (by putting a paw/hand in front of the nose).
There are three reasons (at least) for preferring Bergen's explanation over the mentalese account. First of all, there is the fact that brain imagery confirms that brains do work the way Bergen says they do. I won't linger over this point as I have made it myself many times on this blog.
Second, Bergen's account goes a long way to explaining all the stuff we understand all the unstated material in a sentence. Polar bears are white and operate against a white background, but their nose is black, so they might want to hide their noses to achieve even greater invisibility. We may never have thought about that point before, but once made we can see the way it works. There is no way to understand the role of whiteness in the mentalese method of turning to a dictionary, unless the information is specifically included in the dictionary. Even if we grant that the dictionary does include all this color detail, we see the problem. It would be nice to understand how we can get more out of language than the words seem to say rather than merely explain it all away with the guess that we already knew what was implied. Language would be much less useful if it could not bring us news.
Third, Bergen has performed hundreds of experiments to support his point. The book reports on over two hundred experiments by Bergen, his graduate students, and likeminded investigators. The method gives the book a certain text-book tedium, but the effect is to break down all resistance and say okay, okay, I believe you.
The experiments fall into several general categories. There are the ones where reading a word or sentence disrupts your ability to interpret a picture. It sounds crazy, but reading the word juggle slows your ability to interpret a stick drawing of a man checking his watch. Why should that be? One explanation might be that when you read the word juggle you activate motor neurons in a way that contradicts the way you would use your hands if you were to check your watch. That explanation might sound far fetched if the experiment were not one of many in which such word/visualization interferences occur. There are also the opposite kinds of experiment where words and images support each other. Then there are the metaphorical effects like rating a politician as being more serious, if you are holding something heavy in your hand.
The point of all these experiments is to see how far Bergen can push the idea that meaning is a simulation of the perception and motor activities carried out in the brain. He does a good job of it, although as is usual in the world of hypothesis and experiment, he makes a firmer case against his rival than in proving his own theory.
Mentalese is on the ropes. It cannot account for these experiments. The best it seems to manage is 'so what?' All this interference, support, and metaphorical effect does not prove that simulation determines meaning. To which the retort is no, but it sure says something is going on that Pinker, Chomsky, et al. did not expect.
Perhaps Berger's biggest problem is that putting meaning on perception—something this blog has done for years—still doesn't answer the question of the mechanics of meaning. Perception is as big a mystery as language. We see a polar bear and know it is a polar bear, how does that happen? I've never had to worry about that issue on this blog because, however it works, the answer is older than human origins. As waiters say, "It's not my table." But someday the puzzle has to be faced.
As far as this blog's direct concern—language origins—goes, the implications are important. The most commonly published date for language origins is 100 to 50 thousand years ago. That is said despite the fact that humans have all sorts of physical adaptations to speech that cannot possibly be so recent. It also ignores the evidence that genus Homo has been cooperative for millions of years and that until very recent times, the Homo brain has for some reason or other been getting bigger and bigger. So what's the evidence that language is a recent invention?
Mentalese.
If you accept the mentalese definition of language as a system of structured symbols, it is reasonable to think that the species did not use language until it started using symbols. When was that? Some evidence points to a few hundred thousand years ago, but not everybody accepts that. It is hard to deny the archaeological evidence that by 50,000 years ago symbols were to be found.
But if the mentalese definition is wrong, then there is no reason to stick with symbols as language's sine qua non. Concrete remarks could be very old indeed, with metaphors and abstractions coming later. So, of course, I welcome this account of Dr. Bergen's many experiments.
I will follow up this review with further posts.
How can you punch up this sentence? I have submitted my application for a job with the EPA?
(a) I have happily submitted my application for a job with the EPA;
(b) I have submitted my request for employment at the EPA;
(c) I have applied for a job with the EPA;
(d) I submitted my application for a job with the EPA.
Most editors would probably favor (c) which reduces a verb phrase to a simple verb. It also simplifies the reader's task. Compare the basic functional structure of I have submitted my application with I have applied for a job. The first directs the reader's attention to a trivial detail, the application, while the second points toward the heart of the matter, the job.
Those interested in improving their writing skills should master this little trick: transform the noun in a verb phrase into the verb: e.g., give a demonstration à demonstrate (or show), be in violation of à violate/break/disobey.
I've taken these examples from a new book on verbs, Vex, Hex, Smash, Smooch: let verbs power your writing by Constance Hale. Is there a whole book's worth of reading about verbs? I'm willing to try, for I am a lover of verbs. I've never forgotten a scene in the play The Madness of King George III and coming to attention when the king made this royal pronouncement, "I am the king. I tell. I am not told. I am the verb, sir, not the object." When I saw that on stage, I grinned.
The philosopher Daniel Dennett sure resembles Charles Darwin.
The Atlantic magazine's website has a brief piece by Daniel Dennett on the relation between Alan Turing's notion of a computer and Darwin's theory of natural selection. The basic connection is that Darwin defined a mindless process that produces complex life forms, and Turing defined a mindless process whereby machines can solve any problem that has a computable solution.
Dennett is probably the most important philosopher arguing that the mind-body distinction is false and that mind can indeed be fully explained in terms of material mechanisms. It is an interesting issue for this blog because of the relation between mind and language. Can a mindless machine compute any and all sentences in a language?
We know as a matter of fact that the other animals of the earth cannot generate sentences, so, following Dennett, humans must have evolved new computational abilities to support language. Did we do that?
In my account of speech origins I propose that while our ape brains were adequate to get us speaking words and phrases, they were not enough to get us speaking true sentences or speaking about subjective processes. A true sentence consists of two focal points of attention united by a verb. An example is John Wilkes Booth shot Abraham Lincoln. To understand this sentence you have to focus on both Booth and Lincoln at the same time, normally an impossibility, but the two men are held together by the verb shot. We can imagine the scene with Booth. Lincoln, and the gun together and we pay attention to all at once because we understand it as a unitary event. Apes in their use of sign language have shown no hint of being able to create true sentences like this.
In my account, speech was originally used to direct attention to the concrete world, but eventually we developed the ability to speak about subjective things too. For example, Jack wrestled with Jill's idea. This is a true sentence with two focal points—Jack and Jill's idea. But the unifying verb—wrestled—is a metaphor. Some other verb might be possible—e.g., struggled, grappled… but they are all metaphors. No concrete verb gets at whatever it is Jack is doing. We can use computer verbs like tried to process but that's a metaphor too. I believe the ability to use metaphorical verbs—and perhaps metaphors in general—had to evolve to produce modern language.
The implication of Dennett's essay is that we must have evolved some Turing machines which could compute true sentences and metaphors. Yet, I confess that I doubt that such was the case.
Mindless Success
Most people assume that to speak you have to understand what you are saying, but Dennett's point is that understanding is not necessary if you have a sufficiently well programmed computer. Take, for example, machines that play chess. I am old enough to have seen that whole story develop. In the 1950s the mastery of chess was often cited as a task for humans alone. Efforts to program machines to play chess were so limited that "toy" versions of the game with a few squares and pieces were the best most programmers could manage.
Back in the 1960's there was a big argument over whether the best approach was to mimic human thought or to rely on the "brute force" of a computer's great speed and data storage. I seem to recall a story in Scientific American from those days that said mimicking human thought was the more promising approach.
By the early 1980s chess playing machines were available and they used brute force. I bought one. It quickly became apparent that the only way a player of my feeble skills could beat the machine was to have a clear strategy in mind. A strategy was some long-range, general goal whose details I could not specify but which I could imagine sharply enough to guide my judgment about positions. With a strategy I could choose moves and eventually see my way to victory.
The other way to play chess is to use tactics, basically finding a set of specific moves that result in a stronger position. Chess machines use tactics. They follow moves and give the resulting outcome a score. They pick the move that leads to the highest score. I can only see a couple of moves ahead and if I relied on tactics alone, I would fail. The machine could evaluate more moves than I could, but with a strategy, if I stayed alert, I could win. I would make a move to support my plan and the computer would respond with an irrelevant move. Eventually, my strategy would overwhelm the machine. But by the early 1990s the story was different.
The best chess applications by that time were able to look deeply enough to give even some grandmasters a rough go. For me it was hopeless. The better players would hang on until they reached the end game. Chess end games—when each side is reduced to a couple of pieces—are especially strategic. Typically, players try to reach a situation, then aim for another situation, and then perhaps another. Machines still had a hard time with that kind of purposeful behavior.
In May 1997, however, an IBM machine called Deep Blue defeated Gary Kasparov in two out of three games. Kasparov was the greatest player of the time and possibly of all time. Deep Blue was able to compute so many steps ahead that it turned Kasparov's strategies into mere tactics and it had stored all possible end game positions and what move to make. Without even knowing that it was playing chess or what a pawn is, Deep Blue was able to out maneuver a man who understood the positions more profoundly than any other person alive.
Mindless Language
Can something similar be accomplished using language? Can a mindless machine produce literature? The chess story reminds us that what many had once declared impossible can be done, but to do the impossible a machine must find a way to simulate purposeful behavior by generating a long string of computational steps. Can the production of meaningful sentences be reduced blind steps?
Language evolves in two ways—one is like natural selection, lacking in purpose. Phonetic changes, for example, don't matter per se. A coin might be called a penny or a benny or a venny. The important thing is that sounds distinguish words enough that listeners can catch which coin is meant. To the extent that language can change without changing meaning, language can evolve mindlessly.
But some changes do result from purposeful changes in meaning. I have noticed that a new verb has appeared in the past month. Americans can now say things like Governor Romney has etch-a-sketched his position on immigration. (*For non-Americans I explain the etymology of etch-a sketch beneath this post.) Until quite recently Etch-a-Sketch was a proper noun, but now it I have heard Democratic commentators use it as a verb, a metaphorical synonym for opportunistic change.
Suppose we had a computer that was fully up to date on the American form of English on May 1, 2012 and then in June was confronted with the etch-a-sketch verb. The computer's dictionary would identify Etch-A-Sketch as a proper noun with an –ed suffix and conclude that this is a noun being used as a verb. But what does it mean? Is there a step by step process going from the definition of the word as a noun to its use as a verb?
Sometimes there might be, when the verb simply means to use the noun, as in He Photoshopped his picture. But this new use of etch-a-sketch is metaphorical. I understand it by imagining the Etch-A-Sketch shaking and covering up an old image, ready to display something else. I also know the context of where the word came from and catch the implication of insincere opportunism as well.
Understanding a sentence is like watching a chess game and grasping the player's strategy, something chess-playing machines still cannot do. The observer sees a move and makes a leap, grasping the purpose supporting the move. In understanding a metaphorical sentence the listener must leap to the relevant references and see the purpose that justifies them.
Can a machine do this in some step-by-step manner? I don't like to say never, but I don't know what those steps would be.
Is the brain a computer?
Dennett takes it for granted that the brain is a computer, and although many agree with him the assumption is not proven. And if we believe that human chess playing involves strategic thinking, there is strong evidence that we think in a manner unavailable to chess-playing machines. The fact that machines can beat us at the game is not evidence that our brains are inferior computers anymore than the fact that automobiles can outrace us proves that our bodies are powered by inferior internal-combustion engines.
The assumption that the brain is a computer relies on our understanding of matter. Back when Galileo was laying down the rules of scientific thinking, he said it must stick to primary qualities, i.e., measurable qualities. Sensations, judgments, and purposes are secondary qualities and not to be included in scientific explanations of phenomena. That's why Lamarck's account of evolution was dismissed by people like Lyell and Darwin as unscientific. It appealed to a secondary quality, purpose. Darwin found the way to explain evolution without appealing to purpose.
But science's success does not mean that secondary qualities do not exist. It would be hard to persuade people that they don't have sensations, don't make judgments, and don't have purposes. The mind-body distinction is widely debated by philosophers and psychologists, with opponents of the distinction confident that they are attacking some form of spiritualism. Furthermore, the details of the distinction are vague. If you want to replicate the mind in a mechanical body, you are unsure how to prove you've done it beyond Turing's suggestion of seeing if a person can be fooled by a machine.
The primary-secondary quality distinction, however, has a more scientifically acceptable provenance, and makes for a more clear challenge. To cross the primary-secondary quality divide, a mindless machine would have to follow a series of steps to get from primary-based knowledge (scientific, measurable knowledge) to secondary-based knowledge (humanistic, metaphorical knowledge).
One challenge of this test is to prove the presence of secondary knowledge. I happen to believe that elephants have sensations, make judgments, and behave purposefully, but I cannot prove it. Elephants may be mindless, as Descartes said they were. But Descartes also said that the presence of language proves the existence of the human mind. So lets look at language. Can a machine which can detect only primary qualities compute sentences that express secondary qualities.
Language works at the conscious level, forcing things into our attention, and appealing routinely to secondary qualities: Wow, she's a looker; Try this. It tastes great; I'm going to write a blog so I can understand the details of the subject; I think 'Casablanca' is better than 'Citizen Kane.' Are sentences like these computable? Come to think of it, the etch-a-sketch metaphor is also based on a secondary-quality. The opportunism it implies is subjective, like beauty or grandeur. So computing a sentence about Romney etch-a-sketching his way to a position requires crossing the primary-secondary divide.
Even I am enough of a programmer that I could have a computer look into a database and pull out one of these sentences. But we know that is not how we create our own secondary–quality sentences. The etch-a-sketch sentence, for example, reflects a novel use of a noun as a verb. It cannot have been pre-stored in our brains. We either have some way of computing our way across the divide, or our brains are not Turing machines.
Chess machines cross the strategy-tactics divide by extending its analysis so many steps that the difference between strategy and tactics disappears. The difference between primary and secondary qualities seems to be more categorical, but in some cases that difference makes crossing the divide easier. You just need a simple table to convert wave length (primary quality) into colors (secondary quality). Other secondary qualities—like favorite color, contrasting colors, and an illustrator's pallet—have no counterpart in the world of primary qualities.
Another difference between chess and language is that chess is a complete system. The rules refer to moves made by defined pieces on a prescribed board. Language is not complete. At any moment a speaker might say something like His face turned the color of Grandma's cherry pie. Analogies can come from anywhere. Yet they cannot come from everywhere. His face turned the color of Granma's first novel will not do. Computing all the sentences of a language, and only the sentences of a language may be impossible.
*Etch-a-sketch etymology
The Etch-a-sketch is a popular toy used for drawing. It displays a silver screen and lets a user draw images. To produce a different drawing you shake the toy and the silver powder erases the old image.
Earlier this year, when Governor Romney was campaigning against other Republicans to get the party nomination for president, he advertised himself as a "severe" conservative. At some point a reporter asked one of Romney's aides how they planned to appeal to less conservative voters when the whole nation was voting. The aide replied that presenting a less conservative Romney would be as easy as changing a picture on an Etch-A-Sketch. There was a hullaballoo about Romney's apparent hypocrisy and the campaign's cynicism implied by this image.
A bit later spokespeople for the Obama campaign began using a new verb: to etch-a-sketch.
There has been a flurry of publicity in the New York Times and The Chronicle of Higher Education about Daniel Everett's new book, Language: the cultural tool. The hype has to do with an old controversy (see a post from 5 years ago: Just the Facts) concerning Everett and Noam Chomsky over recursion. Chomsky (along with Marc Hauser and Tecumseh Fitch) published a paper claiming that the only feature of language that might be limited to humans was a recursive structure. The exact nature of recursion is open to some confusion but is generally taken to embed words or phrases into sentences. Everett reported on a people living in the upper Amazon, the Piraha, whom—Everett said—did not have recursive language, and therefore challenged Chomsky's view of what makes language language.
I can hardly believe that Everett's whole argument against the "language instinct," using Steven Pinker's term, rests on the presence or absence of recursion in Piraha language. I've always thought that making recursion language's sine qua non was absurd. The difference between chimpanzee and human communication is not that chimps converse without recursion. At the same time, recursion is a feature of linguistic structure and it would be astonishing to discover a people who don't take advantage of the capacity. After all, recursion is a way of clarifying what you're saying: That man, the one with the red hat, made a rude gesture at me. Am I to accept the claim that Piraha cannot make themselves more clear?
Actually, I don't have to. Apparently, the corpus of known Piraha sentences includes His mother, Itaha, spoke which is simple recursion. But can Everett's argument really be so simple that this small bit of speech really falsifies his claims? A check of the Amazon page shows many blurbs from serious people, so I'm hoping that Everett's argument is more profound than the hype suggests.
I haven't gotten my hands on the book yet and am opening up this post to comments from readers who have seen Everett's new book. If I manage to snag a copy, I'll pass along what I learn. Meanwhile, I'm returning to my long commute.
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