A Whole New Mind: Why Right-Brainers Will Rule the Future (6 page)

The programmers I met in Mumbai are but four well-educated drops in a global tsunami. Each year, India’s colleges and universities produce about 350,000 engineering graduates.
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That’s one reason that more than half of the Fortune 500 companies now outsource software work to India.
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For instance, about 48 percent of GE’s software is developed in India. The company employs a whopping twenty thousand people there (and has even posted signs in its Indian offices reading, “Trespassers will be recruited”). Hewlett-Packard employs several thousand software engineers in India. Siemens employs three thousand computer programmers in India and is moving another fifteen thousand such jobs overseas. Oracle has a five-thousand-person Indian staff. The large Indian IT consultancy Wipro employs some seventeen thousand engineers who do work for Home Depot, Nokia, and Sony. And the list goes on. As the chief executive of GE India told London’s
Financial Times:
“Any job that is English-based in markets such as the U.S., the U.K. and Australia can be done in India. The only limit is your imagination.”
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Indeed, active imaginations have already expanded India’s professional ranks well beyond computer programmers. Financial services firms such as Lehman Brothers, Bear Stearns, Morgan Stanley, and JPMorgan Chase have contracted out number crunching and financial analysis to Indian MBAs.
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The financial news service Reuters has offshored low-level editorial jobs. And throughout India, you’ll find chartered accountants who prepare American tax returns, lawyers who do legal research for American lawsuits, and radiologists who read CAT scans for American hospitals.

But it’s not just India. L-Directed white-collar work of all sorts is migrating to other parts of the world as well. Motorola, Nortel, and Intel operate software development centers in Russia, where Boeing has also sent a large portion of its aerospace engineering work. The computer services giant Electronic Data Systems has software developers in Egypt, Brazil, and Poland. Meantime, Hungarian architects are drawing basic blueprints for California design firms. Philippine accountants are performing audits for CapGemini Ernst & Young. And the Dutch firm Philips employs some seven hundred engineers in China, a nation that is now producing nearly as many engineering graduates each year as the United States.
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The main reason is money. In the United States, a typical chip designer earns about $7,000 per month; in India, she earns about $1,000. In the United States, a typical aerospace engineer earns about $6,000 each month; in Russia, his monthly salary is closer to $650. And while an accountant in the United States can earn $5,000 a month, an accountant in the Philippines brings in about $300 a month, no small sum in a country where the
annual
per capita income is $500.
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For these battalions of international knowledge workers, this new world order is a dream. But for white-collar, left-brain workers in Europe and North America, the implications are more nightmarish. For example:

• One out of ten jobs in the U.S. computer, software, and information technology industry will move overseas in the next two years. One in four IT jobs will be offshored by 2010.
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• According to Forrester Research, “at least 3.3 million white-collar jobs and $136 billion in wages will shift from the U.S. to low-cost countries like India, China, and Russia” by 2015.
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• Nations such as Japan, Germany, and the United Kingdom will see similar job loss. The United Kingdom alone will lose some 25,000 IT jobs and upwards of 30,000 finance positions to India and other developing nations in the next few years. By 2015, Europe will lose 1.2 million jobs to offshore locales.
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Much of the anxiety over this issue outstrips the reality. We are not all going to lose our jobs tomorrow. Outsourcing is overhyped in the short term. But it’s underhyped in the long term. As the cost of communicating with the other side of the globe falls essentially to zero, and as developing nations continue to mint millions of extremely capable knowledge workers, the working lives of North Americans, Europeans, and Japanese people will change dramatically. If standardized, routine L-Directed work such as many kinds of financial analysis, radiology, and computer programming can be done for a lot less overseas and delivered to clients instantly via fiber optic links, that’s where the work will go. This upheaval will be difficult for many, but it’s ultimately not much different from transitions we’ve weathered before. This is precisely what happened to routine mass production jobs, which moved across the oceans in the second half of the twentieth century. And just as those factory workers had to master a new set of skills and learn how to bend pixels instead of steel, many of today’s knowledge workers will likewise have to command a new set of aptitudes. They’ll need to do what workers abroad cannot do equally well for much less money—using R-Directed abilities such as forging relationships rather than executing transactions, tackling novel challenges instead of solving routine problems, and synthesizing the big picture rather than analyzing a single component.

Automation

Meet two more people. One is an iconic figure who may have been real. The other is a real human being who, perhaps to his regret, may become iconic.

The first is this fellow, immortalized here on a U.S. postage stamp:

As most American schoolchildren could tell you, John Henry was a steel-driving man. Born with a hammer in his hand, he was a figure of immense strength and integrity. (Alas, nobody is certain whether he was an actual person. Many historians believe he was a former slave who worked on the railroads after the Civil War, though none have been able to verify his existence.) He was part of a team of workers who smashed through mountains to clear tunnels for laying railroad tracks. But John Henry was no ordinary laborer. He could drive steel faster and more powerfully than any man alive, and his prowess soon became the stuff of legend.

One day, the tale goes, a salesman arrived at the workers’ camp bearing a new steam-powered drill that he claimed could outperform even the strongest man. John Henry scoffed at the notion that gears and grease were any match for human muscle. So he proposed a contest—man vs. machine—to see which could blast through a mountainside the fastest.

The next afternoon, the race began—the steam drill on the right, John Henry on the left. The machine took the lead, but John Henry quickly rallied. Chunks of rocks fell as the duo bored through their tunnels. Before long, John Henry had closed in on his competitor. And in an instant before the end of the race, he surged past the steam drill and broke through the other side of the mountain first. His fellow workers cheered. But John Henry, exhausted by the superhuman effort, collapsed. Then he died. The story spread. In ballads and books, John Henry’s demise became a parable of the Industrial Age: machines could now do some things better than human beings, and as a result a measure of human dignity had been sacrificed.

Now meet our second figure:

Garry Kasparov is a chess grand master—the finest chess player of his generation and perhaps the greatest of all time. He’s also the John Henry of our new age—a person whose seemingly superhuman prowess has been surpassed by a machine.

Kasparov won his first chess world championship in 1985, around the same time that several research teams began developing computer programs that could play chess. Over the next decade, Kasparov never lost a match. And in 1996, he defeated what was then the world’s most powerful chess computer.

But in 1997, Kasparov took on an even more powerful machine, a 1.4-ton IBM supercomputer called Deep Blue, in a six-game match that some dubbed “the brain’s last stand.”
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To the surprise of many, Deep Blue defeated Kasparov, the consequences of which the cover of
Inside Chess
magazine reduced to a single word: “ARMA-GEDDON!”
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Seeking vengeance—for himself and for all flesh-and-blood L-Directed thinkers—Kasparov then arranged a rematch against another computer, Deep Junior, a still more potent Israeli computer that had thrice won the world computer chess championship.

Chess is in many ways the quintessential left-brain activity. It leaves relatively little room for emotion—and depends heavily on memory, rational thinking, and brute calculation, two things at which computers excel. Kasparov says that when he looks at the board, he can examine between one and three moves per second. Deep Junior is, uh, slightly more impressive. Each second, it analyzes between two and three
million
possible moves. Yet, Kasparov believed that human beings had other advantages that would level the sixty-four-square playing field.

On Super Bowl Sunday 2003, Kasparov strutted into the posh New York Downtown Athletic Club to begin another epic contest between man and machine—a six-game match with a million-dollar purse. Hundreds of fans watched in person. Millions more followed the action on the Internet. Kasparov won game one and settled for a draw in game two. In game three, he started strong, but on the edge of victory, he fell into one of Junior’s traps and lost. In game four, Kasparov played haltingly and eked out another draw, still so distraught over blowing game three that he admitted that he “couldn’t sleep and lost confidence.”
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Game five was another draw, leaving the outcome of the match to the sixth and final game.

Kasparov quickly took the lead. As
Newsweek
later reported, “Against any human player, he would have moved aggressively and gone for the win. But he wasn’t playing against a human.” In his tentativeness, he made a slight mistake and that left him

devastated in a way that an unfeeling machine would never be. Worse, having yielded the advantage he had no hope—as he would have against a human—that his well-programmed opponent might make its own mistake and let him back in the game. The realization paralyzed even the great Kasparov, and it haunted him for the rest of the match.
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In the end, he settled for a draw—in this game and the entire match.
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Human beings have much to recommend, but when it comes to chess—and increasingly other endeavors that depend heavily on rule-based logic, calculation, and sequential thinking—computers are simply better, faster, and stronger. What’s more, computers don’t fatigue. They don’t get headaches. They don’t choke under pressure or sulk over losses. They don’t worry what the audience thinks or care what the press will say. They don’t space out. They don’t slip up. And that has humbled even the notoriously egomaniacal grand master. In 1987, Kasparov, then the chess world’s enfant terrible, boasted: “No computer can ever beat me.”
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Today, Kasparov, now our modern John Henry, says: “I give us only a few years. Then they’ll win every match, and we may have to struggle to win even a single game.”
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Last century, machines proved they could replace human backs. This century, new technologies are proving they can replace human left brains. Management meta-guru Tom Peters puts it nicely, saying that for white-collar workers “software is a forklift for the mind.” It won’t eliminate every left-brain job. But it will destroy many and reshape the rest. Any job that depends on routines—that can be reduced to a set of rules, or broken down into a set of repeatable steps—is at risk. If a $500-a-month Indian chartered accountant doesn’t swipe your comfortable accounting job, Turbo-Tax will.

Consider three heavily L-Directed professions: computer programmers, physicians, and lawyers. “In the old days,” says computer scientist Vernor Vinge, “anybody with even routine skills could get a job as a programmer. That isn’t true anymore. The routine functions are increasingly being turned over to machines.”
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Indeed, a small British company called Appligenics has created software that can write software. Where a typical human being—whether the Indians I met or their higher-paid counterparts in the United States—can write about four hundred lines of computer code per day, Appligenics applications can do the same work in
less than a second.
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The result: as the scut work gets off-loaded, engineers and programmers will have to master different aptitudes, relying more on creativity than competence, more on tacit knowledge than technical manuals, and more on fashioning the big picture than sweating the details.