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| READ AN EXCERPT |
TWO OF THE SMARTEST PEOPLE you'll ever meet are the guys
who used to operate the M. Coy bookshop on Pine Street in
Seattle. Business pressures recently forced them to shutter their
shop, but for 20 years, they sold their books, and from the moment
you walked into their store, they had you figured out. They noticed
where your gaze would go; they noticed where you paused. They
noticed what books you picked up and how long you lingered over
them. They recalled earlier customers who had bought the same
titles and remembered other books those shoppers bought. They
flashed through their entire 20,000-book inventory and then
approached you with the single most important thing they had to
offer: a recommendation.
Across town, in the Art Deco headquarters of Amazon.com the
booksellers are good at making recommendations too. Log on to
their site, and you've walked into their store. There, Amazon
computers also keep an eye on you. They see where you click;
they see where you pause. They recall every book you've ever
bought and what other customers like you have bought. They
shovel through data about millions of buyers and tens of millions of
sales and then, like the shopkeepers, come up with a suggestion.
However, the computers don't do all this in a 1,400-g (3 lb.), walnut-
wrinkled mass of brain tissue but in a vast network of computers.
It's easy to say that one approach is more complex than the other.
It's a lot harder to say which one.
Of all the things that confuse human beings, perhaps nothing trips
us up so much as what it means for something to be simple or
complex. A houseplant, with its microhydraulics, fine-tuned
metabolism and dense schematic of nucleic acids, may be more
complex than a manufacturing plant. A modern army, with its
thicket of bureaucracy and static encampments, may be simpler
than a nimble guerrilla group. A guppy, with its symphony of
biological systems and subsystems, is vastly more complicated
than a star.
Human beings are not wired to look at things this way. We're
suckers for size, for flash, for speed, for scale; we mistake
immensity for complexity and subtlety for simplicity. That has very
often been our undoing. Shock and awe should win a war, until an
insurgency beats it back. An election should be sealed by storming
Super Tuesday, until the campaign dies of a thousand little losses.
The 2003 Yankees, with their $180 million payroll, should win the
World Series, until the $63 million Marlins send them packing.
These may be lessons most of us must repeat again and again,
but science increasingly is learning something from them. A
generation ago, the paradigm-shifting understanding of chaos
theory revealed the power of disorder in meteorology, marketing,
plate tectonics and more. Similarly, investigators across the social
and scientific spectrums are today studying how systems that
seem simple or complex may be just the opposite—and how that
fact can expand our understanding of our world. "Ask me why I
forgot my keys today, and the answer may be that something was
on my mind," says neuroscientist Chris Wood of the Santa Fe
Institute (SFI) in New Mexico, a multidisciplinary think tank devoted
to complexity theory. "Ask me about the calcium channels in my
brain that drive remembering, and you're asking a much harder
question."
There are a lot of ways the push-pull between simplicity and
complexity is being explored and explained. Consider how babies
learn to speak—a job so complicated that by some measures they
shouldn't be able to do it at all. By the time babies are 18 months
old, they have a core vocabulary of 50 words they can pronounce
and 100 more they understand. By their sixth birthday, children
have a working vocabulary of 6,000 words—meaning they've
learned, on average, three new words every day since birth.
Mastering conversational English requires about 50,000 words.
What's more, since babies can't know where they'll be born, they
must start life able to learn any of the world's nearly 7,000
tongues. It's processing speed that makes all this possible.
At Rutgers University in Newark, N.J., neuroscientist April Benasich
fits prelingual babies with caps that read electrical activity in the
brain. Benasich then plays one-syllable word bits to them—da and
ta sounds, for example—and watches as their brains process the
difference. At first, the sounds are separated by 300 milliseconds,
very fast but well within the brain's ability. She then speeds things
up so that the gap shrinks to 200 milliseconds, then 100, then 35—
the point at which the length of the space is less than the length of
the syllable itself. Even then the babies keep pace, getting all the
way down to 10 milliseconds before the sounds run together.
Not all kids, however, have the same gifts. Benasich has found that
some children fall out of the word-break race at about 70
milliseconds. Find the kids who later develop reading or speech
disabilities, and they may also turn out to be the ones who had
trouble keeping up with the sounds. "If you can't make a precise
phonological map of a word," Benasich says, "you can't recognize
it or reproduce it." If therapists could spot kids with such
processing problems early, they could provide programs better
targeted to their needs. No matter how the children's disability is
corrected, it's a mark of the simple things on which speech stands
or falls that the need for such retraining may turn on a few
milliseconds of hearing either way.
Mundane matters like traffic move through simplicity choke points
too. On any given day, about a million cars stream into and out of
Manhattan. At any given moment, however, only about 8,000 of
them are in operation in the heavily traveled midtown area. Keep
those cars moving, and traffic flows smoothly all over the island.
Jam them up, and gridlock can spread like ice freezing. "In fact,"
says urban-planning consultant Sam Schwartz, a former New York
traffic commissioner who helped the city prepare for the 1980
transit strike, "in the case of true gridlock, the streets are actually
60% empty. All of the crowding is at the intersections, with nothing
getting to midblock."
In the arts as well, simplicity and complexity may masquerade as
each other. Two years ago, physicist Richard Taylor of the
University of Oregon began trying to establish the authenticity of
six possible Jackson Pollock paintings. Taylor ultimately
determined that the paintings were done by someone else, not
because the materials or colors were wrong but because they
lacked the microscopic fractals—repetitive patterns within
patterns—that defined Pollock's abstractions. Fractals were a well-
known concept in mathematics, but nobody expected to find them
in a free-form splatter painting. Something in the way Pollock
tossed his paint, however, allowed him not only to create fractals
but also to manipulate them so that they landed only on the
canvas. The floor around them? Just splatters.
The ability to balance on the simplicity-complexity fulcrum is
producing results elsewhere too—in increasingly complex software
that yields increasingly intuitive user interfaces (think the iPhone);
in algorithms that show how the movements of schooling fish mirror
the behavior of investors, making stock-market predictions more
reliable. Murray Gell-Mann, a Nobel Prize—winning physicist and a
co-founder of SFI, likes to cite the case of physicist Karl Jansky,
who founded the science of radio astronomy in 1931 when he was
studying the hiss of electromagnetic static that bathes the Earth—
part of the same hiss you hear on a car radio. Jansky realized that
the sound was caused not by atmospheric disturbances but by
ancient signals streaming to us from the very center of the galaxy.
What everyone else heard as noise, Gell-Mann says, Jansky
heard as a "beautiful regularity." Slowly, we're all learning to listen
the same way.
