The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies (17 page)

As more data become available and as the economy continues to change, the ability to ask the right questions will become even more vital. No matter how bright the light is, you won’t find your keys by searching under a lamppost if that’s not where you lost them. We must think hard about what it is we really value, what we want more of, and what we want less of. GDP and productivity growth are important, but they are means to an end, not ends in and of themselves. Do we want to increase consumer surplus? Then lower prices or more leisure might be signs of progress, even if they result in a lower GDP. And, of course, many of our goals are nonmonetary. We shouldn’t ignore the economic metrics, but neither should we let them crowd out our other values simply because they are more measurable.

In the meantime, we need to bear in mind that the GDP and productivity statistics overlook much of what we value, even when using a narrow economic lens. What’s more, the gap between what we measure and what we value grows every time we gain access to a new good or service that never existed before, or when existing goods become free as they so often do when they are digitized.

*
There have been a number of related findings since then. Last year, the economists Jeremy Greenwood and Karen Kopecky applied a similar approach and found a similar growth contribution for personal computers alone. Shane Greenstein and Ryan McDevitt, another pair of economists, asked how much consumer surplus was created by the spread of broadband Internet access. They looked at how the real price of broadband had declined over time and how adoption of the service had increased. From that, they estimate how much people would have been willing to pay compared to what they actually paid, and thus arrive at the consumer surplus. A research team at McKinsey took a more direct approach. The team asked 3,360 consumers what they would have been willing to pay for sixteen specific services available via the Internet. The average willingness to pay added up to fifty dollars per month. Based on this, the team estimated that Americans received over $35 billion worth of consumer surplus from the free Internet. The biggest single category was e-mail, with social networks like Facebook close behind.

*
Yes, our long-time friend, the same Robert J. Gordon we discussed in chapter 6. See http://faculty-web.at.northwestern.edu/economics/gordon/p376_ipm_final_060313.pdf.

*
Unlike unmeasured intangible consumption goods, the bad measures of intangible capital goods don’t automatically bias official productivity statistics. On one hand, like all intangibles, intangible capital goods make the output numbers bigger. But at the same time, they are also used for production and thus make the input numbers bigger. In a steady state where both the input and output numbers are growing at the same rate, these two effects cancel out, so there is no bias in the productivity numbers, defined as output/input. Steady growth has been roughly true for some types of intangibles, such as the human capital assets that are created by education. But other categories—like computer-related organizational capital or the user-generated capital on digital content sites—appears to have been growing rapidly. For these categories of intangible assets, the official productivity numbers understate the true growth of the economy.

“An imbalance between rich and poor is the oldest and most fatal ailment of all republics.”

—Plutarch

O
F
THE
3.5
TRILLION
photos that have been snapped since the first image of a busy Parisian street in 1838, fully 10 percent were taken in the last year.
¹
Until recently, most photos were analog, created using silver halide and other chemicals. But analog photography peaked in 2000.
²
Today, over 2.5 billion people have digital cameras and the vast majority of photos are digital.
³
The effects are astonishing: it has been estimated that more photos are now taken every two minutes than in all of the nineteenth century.
⁴
We now record the people and events of our lives with unprecedented detail and frequency, and share them more widely and easily than ever before.

While digitization has obviously increased the quantity and convenience of photography, it has also profoundly changed the economics of photography production and distribution. A team of just fifteen people at Instagram created a simple app that over 130 million customers use to share some sixteen billion photos (and counting).
⁵
Within fifteen months of its founding, the company was sold for over $1 billion to Facebook. In turn, Facebook itself reached one billion users in 2012. It had about 4,600 employees
⁶
including barely 1,000 engineers.
⁷

Contrast these figures with pre-digital behemoth Kodak, which also helped customers share billions of photos. Kodak employed 145,300 people at one point, one-third of them in Rochester, New York, while indirectly employing thousands more via the extensive supply chain and retail distribution channels required by companies in the first machine age. Kodak made its founder, George Eastman, a rich man, but it also provided middle-class jobs for generations of people and created a substantial share of the wealth created in the city of Rochester after company’s founding in 1880. But 132 years later, a few months before Instagram was sold to Facebook, Kodak filed for bankruptcy.
⁸
Photography has never been more popular. Today, seventy billion photos are uploaded to Facebook each year, and many times more are shared via other digital services like Flickr at nearly zero cost. These photos are all digital, so hundreds of thousands of people who used to work making photography chemicals and paper are no longer needed. In a digital age, they need to find some other way to support themselves.

The evolution of photography illustrates
the bounty
of the second machine age, the first great economic consequence of the exponential, digital, combinatorial progress taking place at present. The second one,
spread
, means there are large and growing differences among people in income, wealth, and other important circumstances of life. We’ve created a cornucopia of images, sharing nearly four hundred billion “Kodak moments” each year with a few clicks of a mouse or taps on a screen. But companies like Instagram and Facebook employ a tiny fraction of the people that were needed at Kodak. Nonetheless, Facebook has a market value several times greater than Kodak ever did and has created at least seven billionaires so far, each of whom has a net worth ten times greater than George Eastman did. The shift from analog to digital has delivered a bounty of digital photos and other goods, but it has also contributed to an income distribution that is far more spread out than before.

Photography is not an isolated example of this shift. Similar stories have been and will be told in music and media; in finance and publishing; in retailing, distribution, services, and manufacturing. In almost every industry, technological progress will bring unprecedented bounty. More wealth will be created with less work. But at least in our current economic system, this progress will also have enormous effects on the distribution income and wealth. If the work a person produces in one hour can instead be produced by a machine for one dollar, then a profit-maximizing employer won’t offer a wage for that job of more than one dollar. In a free-market system, either that worker must accept a wage of one dollar an hour or find some new way to make a living. Conversely, if a person finds a new way to leverage insights, talents, or skills across one million new customers using digital technologies, then he or she might earn one million times as much as would be possible otherwise. Both theory and data suggest that this combination of bounty and spread is not a coincidence. Advances in technology, especially digital technologies, are driving an unprecedented reallocation of wealth and income. Digital technologies can replicate valuable ideas, insights, and innovations at very low cost. This creates bounty for society and wealth for innovators, but diminishes the demand for previously important types of labor, which can leave many people with reduced incomes.

The combination of bounty and spread challenges two common though contradictory worldviews. One common view is that advances in technology always boost incomes. The other is that automation hurts workers’ wages as people are replaced by machines. Both of these have a kernel of truth, but the reality is more subtle. Rapid advances in our digital tools are creating unprecedented wealth, but there is no economic law that says all workers, or even a majority of workers, will benefit from these advances.

For almost two hundred years, wages did increase alongside productivity. This created a sense of inevitability that technology helped (almost) everyone. But more recently, median wages have stopped tracking productivity, underscoring the fact that such a decoupling is not only a theoretical possibility but also an empirical fact in our current economy.

How’s the Median Worker Doing?

Let’s review some basic facts.

A good place to start is median income—the income of the person at the fiftieth percentile of the total distribution. The year 1999 was the peak year for the real (inflation-adjusted) income of the median American household. It reached $54,932 that year, but then started falling. By 2011, it had fallen nearly 10 percent to $50,054, even as overall GDP hit a record high. In particular, wages of unskilled workers in the United States and other advanced countries have trended downward.

Meanwhile, for the first time since before the Great Depression, over half the total income in the United States went to the top 10 percent of Americans in 2012. The top 1 percent earned over 22 percent of income, more than doubling their share since the early 1980s. The share of income going to the top hundredth of one percent of Americans, a few thousand people with annual incomes over $11 million, is now at 5.5 percent, after increasing more between 2011 and 2012 than any year since 1927–28.
⁹

Several other metrics have also been increasingly unequal. For instance, while overall life expectancy continues to rise, life expectancies for some groups have started to fall. According to a study by S. Jay Olshansky and his colleagues published in
Health Affairs
, the average American white woman without a high school diploma had a life expectancy of 73.5 years in 2008, compared to 78.5 years in 1990. Life expectancy for white men without a high school education fell by three years during this period.
¹⁰

It’s no wonder that protests broke out across America even as it was beginning to recover from the Great Recession. The Tea Party movement on the right and the Occupy movement on the left each channeled the anger of the millions of Americans who felt the economy was not working for them. One group emphasized government mismanagement and the other abuses in the financial services sector.

How Technology Is Changing Economics

While undoubtedly both of these problems are important, the more fundamental challenge is deep and structural, and is the result of the diffusion to the second machine age technologies that increasingly drive the economy.

Recently we overheard a businessman speaking loudly (and cheerfully) into his mobile phone: “No way. I don’t use an H&R Block tax preparer anymore. I’ve switched to TurboTax software. It’s only forty-nine dollars, and it’s much quicker and more accurate. I love it!” The businessman was better off. He had a better service at a lower price. Multiplied by millions of customers, TurboTax has created a great deal of value for its users, not all of which even shows up in the GDP statistics. The creators of TurboTax are also better off—one is a billionaire. But tens of thousands of tax preparers now find their jobs and incomes threatened.

The businessman’s experience holds a mirror to the broader changes in the economy. Consumers are better off and enormous wealth is created, but a relatively small group of people often earns most of the income from the new products or services. Like the chemists who used silver halide to create camera film in the 1990s, human tax preparers have a hard time competing with machines. They can be made worse off by advances in technology, not just relative to the winners, but also relative to their income when they were working with the older technologies.

The crucial reality from the standpoint of economics is that it takes only a relatively small number of designers and engineers to create and update a program like TurboTax. As we saw in chapter 4, once the algorithms are digitized they can be replicated and delivered to millions of users at almost zero cost. As software moves to the core of every industry, this type of production process and this type of company increasingly populates the economy.

A Smaller Slice of a Bigger Pie

What happens when you scale up these types of examples to a whole economy? Is there something bigger going on? The data say yes.

Between 1983 and 2009, Americans became vastly wealthier overall as the total value of their assets increased. However, as noted by economists Ed Wolff and Sylvia Allegretto, the bottom 80 percent of the income distribution actually saw a net
decrease
in their wealth.
¹¹
Taken as a group, the top 20 percent got not 100 percent of the increase, but more than 100 percent. Their gains included not only the trillions of dollars of wealth newly created in the economy but also some additional wealth that was shifted in their direction from the bottom 80 percent. The distribution was also highly skewed even among relatively wealthy people. The top 5 percent got 80 percent of the nation’s wealth increase; the top 1 percent got over half of that, and so on for ever-finer subdivisions of the wealth distribution. In an oft-cited example, by 2010 the six heirs of Sam Walton’s fortune, earned when he created Walmart, had more net wealth than the bottom 40 percent of the income distribution in America.
¹²
In part, this reflects the fact that thirteen million families had a negative net worth.