The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies (13 page)

BOOK: The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies
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IBM and partners including Memorial Sloan-Kettering Cancer Center and the Cleveland Clinic are working to build Dr. Watson. The organizations involved in this program are careful to stress that the AI technologies will be used to augment physicians’ clinical expertise and judgment, not replace them. Still, it is not implausible that Dr. Watson might one day be the world’s best diagnostician.

We’re already seeing AI-aided diagnoses in some medical specialties. A team led by pathologist Andrew Beck developed the C-Path (computational pathologist) system to automatically diagnose breast cancer and predict survival rates by examining images of tissue, just as human pathologists do.
5
Since the 1920s, these humans have been trained to look at the same small set of cancer cell features.
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The C-Path team, in contrast, had its software look at images with a fresh eye—without any pre-programmed notions about which features were associated with cancer severity or patient prognosis. Not only was this software at least as accurate as humans, it also identified three features of breast cancer tissue that turned out to be good predictors of survival rates. Pathologists, however, had not been trained to look for them.

As it races ahead, artificial intelligence might bring with it some troubles, which we’ll discuss in our conclusion. But fundamentally, the development of thinking machines is an incredibly positive one.

Billions of Innovators, Coming Soon

In addition to powerful and useful AI, the other recent development that promises to further accelerate the second machine age is the digital interconnection of the planet’s people. There is no better resource for improving the world and bettering the state of humanity than the world’s humans—all 7.1 billion of us. Our good ideas and innovations will address the challenges that arise, improve the quality of our lives, allow us to live more lightly on the planet, and help us take better care of one another. It is a remarkable and unmistakable fact that, with the exception of climate change, virtually all environmental, social, and individual indicators of health have improved over time, even as human population has increased.

This improvement is not a lucky coincidence; it is cause and effect. Things have gotten better
because
there are more people, who in total have more good ideas that improve our overall lot. The economist Julian Simon was one of the first to make this optimistic argument, and he advanced it repeatedly and forcefully throughout his career. He wrote, “It is your mind that matters economically, as much or more than your mouth or hands. In the long run, the most important economic effect of population size and growth is the contribution of additional people to our stock of useful knowledge. And this contribution is large enough in the long run to overcome all the costs of population growth.”
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Both theory and data bear out Simon’s insight. The theory of recombinant innovation stresses how important it is to have more eyeballs looking at challenges and more brains thinking about how existing building blocks can be rearranged to meet them. This theory further holds that people also play the vital role of filtering and improving the innovations of others. And the data on everything from air quality to commodity prices to levels of violence show improvement over time. These data, in other words, show humanity’s remarkable ability to meet its challenges.

We do have one quibble with Simon, however. He wrote that, “The main fuel to speed the world’s progress is our stock of knowledge, and the brake is our lack of imagination.”
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We agree about the fuel but disagree about the brake. The main impediment to progress has been that, until quite recently, a sizable portion of the world’s people had no effective way to access the world’s stock of knowledge or to add to it.

In the industrialized West we have long been accustomed to having libraries, telephones, and computers at our disposal, but these have been unimaginable luxuries to the people of the developing world. That situation is rapidly changing. In 2000, for example, there were approximately seven hundred million mobile phone subscriptions in the world, fewer than 30 percent of which were in developing countries.
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By 2012 there were more than six billion subscriptions, over 75 percent of which were in the developing world. The World Bank estimates that three-quarters of the people on the planet now have access to a mobile phone, and that in some countries mobile telephony is more widespread than electricity or clean water.

The first mobile phones bought and sold in the developing world were capable of little more than voice calls and text messages, yet even these simple devices could make a significant difference. Between 1997 and 2001 the economist Robert Jensen studied a set of coastal villages in Kerala, India, where fishing was the main industry.
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Jensen gathered data both before and after mobile phone service was introduced, and the changes he documented are remarkable. Fish prices stabilized immediately after phones were introduced, and even though these prices dropped on average, fishermen’s profits actually increased because they were able to eliminate the waste that occurred when they took their fish to markets that already had enough supply for the day. The overall economic well-being of both buyers and sellers improved, and Jensen was able to tie these gains directly to the phones themselves.

Now, of course, even the most basic phones sold in the developing world are more powerful than the ones used by Kerala’s fisherman over a decade ago. Approximately 70 percent of all phones sold worldwide in 2012 were ‘feature phones’—less capable than the Apple iPhone and Samsung Galaxy smartphones of the rich world, but still able to take pictures (and often videos), browse the Web, and run at least some applications.
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And cheap mobile devices keep improving. Technology analysis firm IDC forecasts that smartphones will outsell feature phones in the near future, and will make up about two-thirds of all sales by 2017.
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This shift is due to continued simultaneous performance improvements and cost declines in both mobile phone devices and networks, and it has an important consequence: it will bring billions of people into the community of potential knowledge creators, problem solvers, and innovators.

Today, people with connected smartphones or tablets anywhere in the world have access to many (if not most) of the same communication resources and information that we do while sitting in our offices at MIT. They can search the Web and browse Wikipedia. They can follow online courses, some of them taught by the best in the academic world. They can share their insights on blogs, Facebook, Twitter, and many other services, most of which are free. They can even conduct sophisticated data analyses using cloud resources such as Amazon Web Services and R, an open source application for statistics.
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In short, they can be full contributors in the work of innovation and knowledge creation, taking advantage of what Autodesk CEO Carl Bass calls “infinite computing.”
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Until quite recently rapid communication, information acquisition, and knowledge sharing, especially over long distances, were essentially limited to the planet’s elite. Now they’re much more democratic and egalitarian, and getting more so all the time. The journalist A. J. Liebling famously remarked that, “Freedom of the press is limited to those who own one.” It is no exaggeration to say that billions of people will soon have a printing press, reference library, school, and computer all at their fingertips.
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Those of us who believe in the power of recombinant innovation believe that this development will boost human progress. We can’t predict exactly what new insights, products, and solutions will arrive in the coming years, but we are fully confident that they’ll be impressive. The second machine age will be characterized by countless instances of machine intelligence and billions of interconnected brains working together to better understand and improve our world. It will make mockery out of all that came before.

“Most economic fallacies derive from the tendency to assume that there is a fixed pie, that one party can gain only at the expense of another.”

—Milton Friedman

E
ACH
DAY
GOVERNMENT
AGENCIES
, think tanks, NGOs, and academic researchers generate more statistics than any person could read, let alone absorb. On television, in the pages of the business press, and in the blogosphere, a chorus of analysts debate and predict trends in interest rates, unemployment, stock prices, deficits and myriad other indicators. But when you zoom out and consider trends over the past century, one overwhelming fact looms above all others: overall living standards have increased enormously in the United States and worldwide. In the United States, the rate of GDP growth per person has averaged 1.9 percent per year going back to the early 1800s.
1
Applying the rule of 70 (the time to double a value is roughly equal to 70 divided by its growth rate), we see that this was enough to double living standards every thirty-six years, quadrupling them over the course of a typical lifetime.
*

This increase is important because economic growth can help solve a host of other challenges. If GDP of the United States grows just 1 percent faster each year than currently projected, Americans would be five trillion dollars richer by 2033.
2
If GDP grows just 0.5 percent faster, the U.S. budget problem would be solved without any changes to policy.
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Of course, slower growth would make it significantly harder to close the deficit, let alone increase spending on any new initiatives or cut taxes.

Productivity Growth

But what drives increases in GDP per person? Part of it comes from using more resources. But most of it comes from increases in our ability to get more output from the given level of inputs—in other words, increases in productivity. (Most commonly, this term is used as shorthand for ‘labor productivity,’ which is output per hour worked [or output per worker].)
*
In turn, productivity growth comes from innovations in technology and techniques of production.

Simply working more hours does not increase productivity. Indeed, Americans once routinely worked fifty, sixty, or even seventy hours per week. While some still do, the average workweek is shorter now (thirty-five hours per week), and yet living standards are higher. Robert Solow got his Nobel Prize in Economics for showing that increases in labor input and capital input could not explain most of the increase in the total output of the economy.

In fact, it would take the average American only eleven hours of labor per week to produce as much as he or she produced in forty hours in 1950. That rate of improvement is comparable for workers in Europe and Japan, and even higher in some developing nations.
*

FIGURE 7.1
Labor Productivity

Productivity improvement was particularly rapid in the middle part of the twentieth century, especially the 1940s, 50s, and 60s, as the technologies of the first machine age, from electricity to the internal combustion engine, started firing on all cylinders. However, in 1973 productivity growth slowed down (see figure 7.1).

In 1987, Bob Solow himself noted that the slowdown seemed to coincide with the early days of the computer revolution, famously remarking, “We see the computer age everywhere, except in the productivity statistics.”
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In 1993, Erik published an article evaluating the “Productivity Paradox” that noted the computers were still a small share of the economy and that complementary innovations were typically needed before general purpose technologies like IT had their real impact.
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Later work taking into account more detailed data on productivity and IT use among individual firms revealed a strong and significant correlation: the heaviest IT users were dramatically more productive than their competitors.
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By the mid-1990s, these benefits were big enough to become visible in the overall U.S. economy, which experienced a general productivity surge. While this rise had a number of causes, economists now attribute the lion’s share of those gains to the power of IT.
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