Deep Work: Rules for Focused Success in a Distracted World(6)
This reality is not, however, universally grim. As Brynjolfsson and McAfee emphasize, this Great Restructuring is not driving down all jobs but is instead dividing 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 valued (and therefore more rewarded) than before. Brynjolfsson and McAfee aren’t alone in proposing this bimodal trajectory for the economy. In 2013, for example, the George Mason economist 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 of this divide and reap a disproportionate amount of the benefits of the Intelligent Machine Age. Not surprisingly, it’s to 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
Brynjolfsson and McAfee call the group personified by Nate Silver the “high-skilled” workers. Advances such as robotics and voice recognition are automating many low-skilled positions, but as these economists emphasize, “other technologies like data visualization, analytics, high speed communications, and rapid prototyping have augmented the contributions of more abstract and data-driven reasoning, increasing the values of these jobs.” In other words, those with the oracular ability to work with and tease 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 data 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 Heinemeier Hansson 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 virtual meeting software have destroyed regionalism in many sectors of knowledge work. It no longer makes sense, for example, to hire a full-time 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 Hansson 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 suffer.
In a seminal 1981 paper, the economist Sherwin Rosen worked out the mathematics behind these “winner-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 mediocre singers does not add up to a single outstanding 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 everyone’s q value is clear, the consumer will choose the very best. Even if the talent advantage of the best is small compared to 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 markets, such as music stores and movie theaters, where an audience has access to different performers and can accurately approximate their talent before making a purchasing 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 consultant 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 rock stars of their sectors.
The Owners
The final group that will thrive in our new economy—the group epitomized by John Doerr—consists of those with capital to invest in the new technologies that are driving the Great Restructuring. As we’ve understood since Marx, access to capital provides massive advantages. It’s also true, however, that some periods offer 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”).