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January 25 - February 15, 2018
The first is that we’re living in a time of astonishing progress with digital technologies—those that have computer hardware, software, and networks at their core.
Our second conclusion is that the transformations brought about by digital technology will be profoundly beneficial ones.
Our third conclusion is less optimistic: digitization is going to bring with it some thorny challenges.
Rapid and accelerating digitization is likely to bring economic rather than environmental disruption, stemming from the fact that as computers get more powerful, companies have less need for some kinds of workers. Technological progress is going to leave behind some people, perhaps even a lot of people, as it races ahead.
So this is a book about the second machine age unfolding right now—an inflection point in the history of our economies and societies because of digitization.
In 2004 Frank Levy and Richard Murnane published their book The New Division of Labor.1 The division they focused on was between human and digital labor—in other words, between people and computers.
The authors put information processing tasks—the foundation of all knowledge work—on a spectrum. At one end are tasks like arithmetic that require only the application of well-understood rules. Since computers are really good at following rules, it follows that they should do arithmetic and similar tasks.
At the other end of Levy and Murnane’s spectrum, however, lie information processing tasks that cannot be boiled down to rules or algorithms. According to the authors, these are tasks that draw on the human capacity for pattern recognition.
Moravec’s paradox, nicely summarized by Wikipedia as “the discovery by artificial intelligence and robotics researchers that, contrary to traditional assumptions, high-level reasoning requires very little computation, but low-level sensorimotor skills require enormous computational resources.”
“When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind.” —Lord Kelvin
According to Cisco Systems, worldwide Internet traffic increased by a factor of twelve in just the five years between 2006 and 2011, reaching 23.9 exabytes per month.12
you want to have good ideas you must have many ideas.” —Linus Pauling
Economist Bob Gordon, one of the most thoughtful, thorough, and widely respected researchers of productivity and economic growth,
In his 2011 book The Great Stagnation, economist Tyler Cowen is definitive about the source of America’s economic woes: We are failing to understand why we are failing. All of these problems have a single, little noticed root cause: We have been living off low-hanging fruit for at least three hundred years. . . . Yet during the last forty years, that low-hanging fruit started disappearing, and we started pretending it was still there. We have failed to recognize that we are at a technological plateau and the trees are more bare than we would like to think.6
The cotton gin, for example, was unquestionably important within the textile sector at the start of the nineteenth century, but pretty insignificant outside of it.* The steam engine and electrical power, by contrast, quickly spread just about everywhere.
economists call innovations like steam power and electricity general purpose technologies (GPTs).
“deep new ideas or techniques that have the potential for important impacts on many sectors of the economy.”7
GPTs: they should be pervasive, improving over time, and able to spawn new innovations.8
Another school of thought, though, holds that the true work of innovation is not coming up with something big and new, but instead recombining things that already exist.
Brian Arthur
The Nature of Technology,
Economic growth occurs whenever people take resources and rearrange them in ways that make them more valuable. . .
Perhaps the most important ideas of all are meta-ideas—ideas about how to support the production and transmission of other ideas. . . . There are . . . two safe predictions. First, the country that takes the lead in the twenty-first century will be the one that implements an innovation that more effectively supports the production of new ideas in the private sector. Second, new meta-ideas of this kind will be found.16
Like language, printing, the library, or universal education, the global digital network fosters recombinant innovation. We
Innocentive, an online clearinghouse for scientific problems.
The innovation scholars Lars Bo Jeppesen and Karim Lakhani studied 166 scientific problems posted to Innocentive, all of which had stumped their home organizations. They found that the crowd assembled around Innocentive was able to solve forty-nine of them, for a success rate of nearly 30 percent. They also found that people whose expertise was far away from the apparent domain of the problem were more likely to submit winning solutions. In other words, it seemed to actually help a solver to be ‘marginal’—to have education, training, and experience that were not obviously relevant for the
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Kaggle also assembles a diverse, non-credentialist group of people from around the world to work on tough problems submitted by organizations.
Kaggle specializes in data-intensive ones where the goal is to arrive at a better prediction than the submitting organization’s starting baseline prediction.
“The Gross National Product does not include the beauty of our poetry or the intelligence of our public debate. It measures neither our wit nor our courage, neither our wisdom nor our learning, neither our compassion nor our devotion. It measures everything, in short, except that which makes life worthwhile.” —Robert F. Kennedy
businesses rarely get significant performance gains from simply “paving the cowpaths” as opposed to rethinking how the business can be redesigned to take advantage of new technologies.24 Creativity and organizational redesign are crucial to investments in digital technologies.*
work can be divided into a two-by-two matrix: cognitive versus manual and routine versus nonroutine.
They found that the demand for work has been falling most dramatically for routine tasks, regardless of whether they are cognitive or manual.
“One machine can do the work of fifty ordinary men. No machine can do the work of one extraordinary man.” —Elbert Hubbard
The great economist Joseph Schumpeter wrote of “creative destruction,” where each innovation not only created value for consumers but also wiped out the previous incumbent.
GDP has never been higher and innovation has never been faster, yet people are increasingly pessimistic about their children’s future living standards. Adjusted for inflation, the combined net worth on Forbes’ billionaire list has more than quintupled since 2000, but the income of the median household in America has fallen.
technological unemployment. This means unemployment due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor.”
Ideation in its many forms is an area today where humans have a comparative advantage over machines.
So ideation, large-frame pattern recognition, and the most complex forms of communication are cognitive areas where people still seem to have the advantage, and also seem likely to hold on to it for some time to come.
a Wall Street Journal blog post by Peter Sims put it, “the Montessori educational approach might be the surest route to joining the creative elite, which are so overrepresented by the school’s alumni that one might suspect a Montessori Mafia.”
the ‘performance task,’ which presents students with a set of background documents and gives them ninety minutes to write an essay requiring them to extract information from the materials given and develop a point of view or recommendation. In short, the performance task is a good test of ideation, pattern recognition, and complex communication.
