As Election Day loomed in 2012, traffic at the New York Times website spiked, in is normal during moments of national importance. But this time, something was different. A wildly disproportionate fraction of this trattic-more than 70 percent by some reports was visiting a single location in the sprawling domain. It wasn't a front-page breaking news story, and it wasn't commentary from one of the paper's Pulitzer Prize-winning columnists, it was instead a blog run by a baseball stats geek turned election forecaster named Nate Silver. Less than a year later, ESPN and ABC News lured Silver away frum the Times (which tried to retain him by promising a staff of up to a dozen writers) in a major deal that would give Silver's operation a rale in everything from sports to weather tonework news segments co, improbably enough, Academy Awards telecasts. Though there's debate about the methodological ngor af Silver's hand-tuned models, there are fow whn deny that in 2012 this thirty-five-your-ald data whix was a winner in our economy
Another winner is David Hememeter Hansson, a computer programming star who created the Ruby on Rails website development framework, which currently provides the foundation for some of the Web's most popular deurinations, including Twitter and Hulst Hansson is a parter in the unfluential development firm Basecamp (called 37signals until 2014) Hansson doesn't talk publicly about the magnitude of his profit share from Basecamp or his other revenue sources, but we can assume they're lucrative given that Hansson splits his time between Chicago, Malibu, and Marbella, Spain, where he dabbles in high-performance race-car driving
Our third and final example of a clear winner in our economy is John Doerr, a general partner in the famed Silicon Valley venture capital fund Kleiner Perkins Caufield &Byers. Doerr helped fund many of the key companies fueling the current technological revolution, including Twitter, Google, Amazon, Netscape, and Sun Microsystems. The return on these investments has been astronomical: Doer's net worth, as of this writing, is more than $3 billion.
Why have Silver, Hanssum, and Doerr done so well? There are two types of answers t this question. The first are micro in scope and focus on the personality traits and tactics that helped drive this trio's rise. The second type of answers are more micro in that they focus less co the individuals and more on the type of work they represent. Though both approaches to this core question are important, the macro answers will prove most relevant to our discussion, as they better illuminate what our current economy rewards.
To explore this macro perspective we turn a pair of MIT ecocomists, Erik Brynjolfsson and Andrew McAfee, who in their influential 2011 book, Roce Against the Machine, provide a compelling case that among various forces at play, it's the rise of digital texfology in particular that's transforming our labor markets in unexpected ways. "We are in the early throes of a Great Restructuring," Brynjolfsson and McAfee explain early in their book. "Our technologies are racing ahead but many of our skills and organizations are lagging behind." For many workers, this lag predicts bad news. As intelligent machines improve, and the gap between machine and human abilities shrinks, employers are becoming increasingly likely to hire "new machines instead of "new people." And when only a human will do, improvements in communications and collaboration technology are making remote work easier than ever before, motivating companies to outsource key roles ta stars-leaving the local talent pool underemployed.
This reality is not, however, universally grim. As Brynjolfsson and McAtee emphasize, this Great Hestructuring is not driving down all jobs but is instead dhiding them. Though an increasing number of people will lose in this new economy as their skill becomes automatable or easily outsourced, there are others who will not only survive, but thrive becoming more valord (and therefore once rewarded) than before. Brynjolfsson and McAfee aren't alone in proposing this bimodal trajectory for the economy. In 2013, for example, the George Mason eronomist Tyler Cowen published Average Is Over, a book that echoes this thesis of a digital division. But what makes Brynjolfsson and McAfee's analysis particularly useful is that they proceed to identify three specific groups that will fall on the lucrative side at this divide and reap a disproportionate amount of the. henefits of the Intelligent Machine Age. Not surprisingly, it's in these three groups that Silver, Hansson, and Doerr happen to belong. Let's touch on each of these groups in turn to better understand why they're suddenly so valuable.
The High-Skilled Workers
Bryojulfsson and McAfee call the group personified by Nate Silver the "high-skilled" warkers. Advances such as raboties and voice recognition are automating many low- skilled positions, but as these economists emphasize, other echtes like data visualization, analytics, high speed communications, and rapid prototyping have gmented the contributions of core abstract and data-driven reasoning, increasing the values of these jobs." In uther words, these with the oracular ability to work with and teise valuable results out of increasingly complex machines will thrive. Tyler Cowen summarizes this reality more bluntly: "The key question will be: are you good at working with intelligent machines or not?"
Nate Silver, of course, with his comfort in feeding date into large databases, then siphoning it out into his mysterious Monte Carlo simulations, is the epitome of the high- skilled worker Intelligent machines are not an obstacle to Silver's success, but instead provide its precondition
The Superstars
The ace programmer David Helaneler Hanson provides an example of the second group that Brynjolfsson and McAfee predict will thrive in our new economy: "superstars High-speed data networks and collaboration tools like e-mail and vital meeting software have destruyed regionalism in many sectors of knowledge work. It no longer makes sense, for example, to hire a full-these programmer, put aside office space, and pay benefits, when you can instead pay one of the world's best programmers, like Hansson, for just enough time to complete the project at hand. In this scenario, you'll probably get a better result for less money, while Hamson can service many more clients per year, and will therefore also end up better off.
The fact that Hansson might be working remotely from Marbella, Spain, while your office is in Des Moines, Iowa, doesn't matter to your company, as advances in communication and collaboration technology make the process near seamless. (This reality does matter, however, to the less-skilled local programmers living in Des Moines and in need of a steady paycheck.) This same trend holds for the growing number of fields where technology makes productive remote work possible consulting, marketing, writing, design, and so on. Once the talent market is made universally accessible, those at the peak of the market thrive while the rest surfer.
In a seminal 1981 paper, the economist Sherwin Rosen worked out the mathematics behind these "inner-take-all" markets. One of his key insights was to explicitly model talent-labeled, innocuously, with the variable q in his formulas as a factor with imperfect substitution, which Rosen explains as follows: "Hearing a succession of medione singers does not add up to a single standing performance." In other words,
talent is not a commodity you can buy in bulk and combine to reach the needed levels There's a premium to being the best. Therefore, if you're in a marketplace where the consumer has access to all performers, and every one's q valce is clear, the consumer will choose the very hest. Even if the talent advantage of the best is small compared the next rung down on the skill ladder, the superstars still win the bulk of the market.
In the 1980s, when Rosen studied this effect, he focused on examples like movie stars and musicians, where there existed clear mærkets, such as music stores and movie. theaters, where an audience has access to different performers and can accurately approximate their talent before making porchasing decision. The rapid rise of communication and collaboration technologies has transformed many other formerly local markets into a similarly universal bazaar. The small company looking for a computer programmer or public relations cons lant now has access to an international marketplace of talent in the same way that the advent of the record store allowed the small-town music fan to bypass local musicians to buy albums from the world's best bands. The superstar effect, in other words, has a broader application today than Rosen could have predicted thirty years ago. An increasing number of individuals in our economy are now competing with the ruck scam of their sets.
The Owners
The fd group that will drive in our new economy-che group epitomized by John Doen comists of those with capital to invest in the new technologies that are driving the Great Reseracturing. As we've understood since Mars, access to capital provides massive advantages. It's also true, however, that some periods uffer more advantages than others As Brynjolfsson and McAfee point out, postwar Europe was an example of a bad time to be sitting on a pile of cash, as the combination of rapid inflation and aggressive taxation wiped out old fortunes with surprising speed (what we might call the "Downton Abbey Effect").
The Great Restructuring, unlike the postwar period, is a particularly good time to have access to capital. To understand why, first verall that bargaining theory, a key component in standard economic thinking, argues that when money is made through the combination of capital investment and labor, the rewards are returned, roughly speaking. proportional to the input. As digital technology reduces the need for labor in many industries, the proportion of the rewards returned to those who own the intelligent machines is growing A venture capitalist in today's economy can fund a company like Instagram, which was eventually sold for a billion dollars, while employ ng only thirteen people. When eise in history could such a small amount of labor be involved in such a large amount of value? With so little input from labor, the proportion of this wealth that flows back to the machine owners in this case, the venture Investors is without precedent. It's no wonder that a venture capitalist I interviewed for my last book admitted to the with some concerns, "Everyone wants my job.
