Smarter Than You Think: How Technology is Changing Our Minds for the Better. Clive Thompson

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СКАЧАТЬ brain you had before you read this paragraph? You don’t get that brain back. I’m hoping the trade-off is worth it.

      The rise of advanced chess didn’t end the debate about man versus machine, of course. In fact, the centaur phenomenon only complicated things further for the chess world—raising questions about how reliant players were on computers and how their presence affected the game itself. Some worried that if humans got too used to consulting machines, they wouldn’t be able to play without them. Indeed, in June 2011, chess master Christoph Natsidis was caught³⁷ illicitly using a mobile phone during a regular human-to-human match. During tense moments, he kept vanishing for long bathroom visits; the referee, suspicious, discovered Natsidis entering moves into a piece of chess software on his smartphone. Chess had entered a phase similar to the doping scandals that have plagued baseball and cycling, except in this case the drug was software and its effect cognitive.

      This is a nice metaphor for a fear that can nag at us in our everyday lives, too, as we use machines for thinking more and more. Are we losing some of our humanity? What happens if the Internet goes down: Do our brains collapse, too? Or is the question naive and irrelevant—as quaint as worrying about whether we’re “dumb” because we can’t compute long division without a piece of paper and a pencil?

      Certainly, if we’re intellectually lazy or prone to cheating and shortcuts, or if we simply don’t pay much attention to how our tools affect the way we work, then yes—we can become, like Natsidis, overreliant. But the story of computers and chess offers a much more optimistic ending, too. Because it turns out that when chess players were genuinely passionate about learning and being creative in their game, computers didn’t degrade their own human abilities. Quite the opposite: it helped them internalize the game much more profoundly and advance to new levels of human excellence.

      Before computers came along, back when Kasparov was a young boy in the 1970s in the Soviet Union, learning grand-master-level chess was a slow, arduous affair. If you showed promise and you were very lucky, you could find a local grand master to teach you. If you were one of the tiny handful who showed world-class promise, Soviet leaders would fly you to Moscow and give you access to their elite chess library, which contained laboriously transcribed paper records of the world’s top games. Retrieving records was a painstaking affair; you’d contemplate a possible opening, use the catalog to locate games that began with that move, and then the librarians would retrieve records from thin files, pulling them out using long sticks resembling knitting needles. Books of chess games were rare and incomplete. By gaining access to the Soviet elite library, Kasparov and his peers developed an enormous advantage over their global rivals. That library was their cognitive augmentation.

      But beginning in the 1980s, computers took over the library’s role and bested it. Young chess enthusiasts could buy CD-ROMs filled with hundreds of thousands of chess games. Chess-playing software could show you how an artificial opponent would respond to any move. This dramatically increased the pace at which young chess players built up intuition. If you were sitting at lunch and had an idea for a bold new opening move, you could instantly find out which historic players had tried it, then war-game it yourself by playing against software. The iterative process of thought experiments—“If I did this, then what would happen?”—sped up exponentially.

      Chess itself began to evolve. “Players became more creative and daring,” as Frederic Friedel, the publisher of the first popular chess databases and software, tells me. Before computers, grand masters would stick to lines of attack they’d long studied and honed. Since it took weeks or months for them to research and mentally explore the ramifications of a new move, they stuck with what they knew. But as the next generation of players emerged, Friedel was astonished by their unusual gambits, particularly in their opening moves. Chess players today, Kasparov has written, “are almost as free of dogma as the machines with which they train. Increasingly, a move isn’t good or bad because it looks that way or because it hasn’t been done that way before. It’s simply good if it works and bad if it doesn’t.”

      Most remarkably, it is producing players who reach grand master status younger. Before computers, it was extremely rare for teenagers to become grand masters. In 1958, Bobby Fischer stunned the world by achieving that status at fifteen. The feat was so unusual it was over three decades before the record was broken, in 1991. But by then computers had emerged, and in the years since, the record has been broken twenty times, as more and more young players became grand masters. In 2002, the Ukrainian Sergey Karjakin became one at the tender age of twelve.³⁸

      So yes, when we’re augmenting ourselves, we can be smarter. We’re becoming centaurs. But our digital tools can also leave us smarter even when we’re not actively using them.

      Let’s turn to a profound area where our thinking is being augmented: the world of infinite memory.

       We, the Memorious_

      What prompts a baby, sitting on the kitchen floor at eleven months old, to suddenly blurt out the word “milk” for the first time? Had the parents said the word more frequently than normal? How many times had the baby heard the word pronounced—three thousand times? Or four thousand times or ten thousand? Precisely how long does it take before a word sinks in anyway? Over the years, linguists have tried to ask parents to keep diaries of what they say to their kids, but it’s ridiculously hard to monitor household conversation. The parents will skip a day or forget the details or simply get tired of the process. We aren’t good at recording our lives in precise detail, because, of course, we’re busy living them.

      In 2005, MIT speech scientist Deb Roy and his wife, Rupal Patel (also a speech scientist) were expecting their first child—a golden opportunity, they realized, to observe the boy developing language. But they wanted to do it scientifically. They wanted to collect an actual record of every single thing they, or anyone, said to the child—and they knew it would work only if the recording was done automatically. So Roy and his MIT students designed “TotalRecall,” an audacious setup that involved wiring his house with cameras and microphones. “We wanted to create,” he tells me, “the ultimate memory machine.”

      In the months before his son arrived, Roy’s team installed wide-angle video cameras and ultrasensitive microphones in every room in his house. The array of sensors would catch every interaction “down to the whisper” and save it on a huge rack of hard drives stored in the basement. When Roy and his wife brought their newborn home from the hospital, they turned the system on. It began producing a firehose of audio and video: About 300 gigabytes per day, or enough to fill a normal laptop every twenty-four hours. They kept it up for two years, assembling a team of grad students and scientists to analyze the flow, transcribe the chatter, and figure out how, precisely, their son learned to speak.

      They made remarkable discoveries. For example, they found that the boy had a burst of vocabulary acquisition—“word births”—that began around his first birthday and then slowed drastically seven months later. When one of Roy’s grad students analyzed this slowdown,¹ an interesting picture emerged: At the precise moment that those word births were decreasing, the boy suddenly began using far more two-word sentences. “It’s as if he shifted his cognitive effort² from learning new words to generating novel sentences,” as Roy later wrote about it. Another grad student discovered that the boy’s caregivers³ tended to use certain words in specific locations in the house—the word “don’t,” for example, was used frequently in the hallway, possibly because caregivers often said “don’t play on the stairs.” And location turned out to be important: The boy tended to learn words more quickly when they were linked to a particular space. It’s a tantalizing finding, Roy points out,⁴ because it suggests we could help children learn language more effectively by changing where we use СКАЧАТЬ