AS MATURE INDUSTRIES stagnate, information technology has advanced so rapidly that it has now become synonymous with “technology” itself. Today, more than 1.5 billion people enjoy instant access to the world’s knowledge using pocket-sized devices. Every one of today’s smartphones has thousands of times more processing power than the computers that guided astronauts to the moon. And if Moore’s law continues apace, tomorrow’s computers will be even more powerful.
Computers already have enough power to outperform people in activities we used to think of as distinctively human. In 1997, IBM’s Deep Blue defeated world chess champion Garry Kasparov. Jeopardy!’s best-ever contestant, Ken Jennings, succumbed to IBM’s Watson in 2011. And Google’s self-driving cars are already on California roads today. Dale Earnhardt Jr. needn’t feel threatened by them, but the Guardian worries (on behalf of the millions of chauffeurs and cabbies in the world) that self-driving cars “could drive the next wave of unemployment.” Everyone expects computers to do more in the future—so much more that some wonder: 30 years from now, will there be anything left for people to do? “Software is eating the world,” venture capitalist Marc Andreessen has announced with a tone of inevitability. VC Andy Kessler sounds almost gleeful when he explains that the best way to create productivity is “to get rid of people.” Forbes captured a more anxious attitude when it asked readers: Will a machine replace you? Futurists can seem like they hope the answer is yes. Luddites are so worried about being replaced that they would rather we stop building new technology altogether. Neither side questions the premise that better computers will necessarily replace human workers. But that premise is wrong: computers are complements for humans, not substitutes. The most valuable businesses of coming decades will be built by entrepreneurs who seek to empower people rather than try to make them obsolete.
SUBSTITUTION VS. COMPLEMENTARITY Fifteen years ago, American workers were worried about competition from cheaper Mexican substitutes. And that made sense, because humans really can substitute for each other. Today people think they can hear Ross Perot’s “giant sucking sound” once more, but they trace it back to server farms somewhere in Texas instead of cut-rate factories in Tijuana. Americans fear technology in the near future because they see it as a replay of the globalization of the near past. But the situations are very different: people compete for jobs and for resources; computers compete for neither.
Globalization Means Substitution When Perot warned about foreign competition, both George H. W. Bush and Bill Clinton preached the gospel of free trade: since every person has a relative strength at some particular job, in theory the economy maximizes wealth when people specialize according to their advantages and then trade with each other. In practice, it’s not unambiguously clear how well free trade has worked, for many workers at least. Gains from trade are greatest when there’s a big discrepancy in comparative advantage, but the global supply of workers willing to do repetitive tasks for an extremely small wage is extremely large. People don’t just compete to supply labor; they also demand the same resources. While American consumers have benefited from access to cheap toys and textiles from China, they’ve had to pay higher prices for the gasoline newly desired by millions of Chinese motorists. Whether people eat shark fins in Shanghai or fish tacos in San Diego, they all need food and they all need shelter. And desire doesn’t stop at subsistence—people will demand ever more as globalization continues. Now that millions of Chinese peasants can finally enjoy a secure supply of basic calories, they want more of them to come from pork instead of just grain. The convergence of desire is even more obvious at the top: all oligarchs have the same taste in Cristal, from Petersburg to Pyongyang.
Technology Means Complementarity Now think about the prospect of competition from computers instead of competition from human workers. On the supply side, computers are far more different from people than any two people are different from each other: men and machines are good at fundamentally different things. People have intentionality—we form plans and make decisions in complicated situations. We’re less good at making sense of enormous amounts of data. Computers are exactly the opposite: they excel at efficient data processing, but they struggle to make basic judgments that would be simple for any human. To understand the scale of this variance, consider another of Google’s computer-for-human substitution projects. In 2012, one of their supercomputers made headlines when, after scanning 10 million thumbnails of YouTube videos, it learned to identify a cat with 75% accuracy. That seems impressive—until you remember that an average four-year-old can do it flawlessly. When a cheap laptop beats the smartest mathematicians at some tasks but even a supercomputer with 16,000 CPUs can’t beat a child at others, you can tell that humans and computers are not just more or less powerful than each other—they’re categorically different.
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