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

by Erik Brynjolfsson

GPTs: they should be pervasive, improving over time, and able to spawn new innovations.

For any good scientist, of course, data are the ultimate decider of hypotheses. So what do the data say here? Do the productivity numbers back up this pessimistic view of the power of digitization?

Economic growth occurs whenever people take resources and rearrange them in ways that make them more valuable.

best way to accelerate progress is to increase our capacity to test out new combinations of ideas.

with Waze, Innocentive, Kaggle, Quirky, Affinnova, and

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.

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.*

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.*

for most of the subsequent century, additional complementary innovations, from lean manufacturing and steel minimills to Total Quality Management and Six Sigma principles, continued to boost manufacturing productivity.

bits are created at virtually zero cost and transmitted almost instantaneously worldwide. What’s more, a copy of a digital good is exactly identical to the original. This leads to some very different economics and some special measurement problems.

It soon becomes clear that the trends in the official statistics not only underestimate our bounty, but in the second machine age they have also become increasingly misleading.

the rapidly growing consumer surplus from price declines in computers increased economic welfare by about $50 billion each year.*10

the official GDP numbers miss the value of new goods and services added to the tune of about 0.4 percent of additional growth each year, according to economist Robert Gordon.*

Production in the second machine age depends less on physical equipment and structures and more on the four categories of intangible assets: intellectual property, organizational capital, user-generated content, and human capital.

In addition, a lot of research and development (R&D) is never formalized as intellectual property but is still very valuable.

The second—and even larger—category of intangibles is organizational capital like new business processes, techniques of production, organizational forms, and business models.

Our research suggests that a correct accounting for computer-related intangible assets would add over $2 trillion to the official estimates of the capital assets in the United States economy.21

The fourth and biggest category is the value of human capital.

The fact that GDP may be a poor measure of well-being, or even of market activity, has, of course, long been recognized. But changes in society and the economy may have heightened the problems, at the same time that advances in economics and statistical techniques may have provided opportunities to improve our metrics.28

In Bhutan, they’ve begun measuring “Gross National Happiness.” There is also a long-running poll behind the Gallup-Healthways Well-Being Index.34

They call it skill-biased technical change. By definition, skill-biased technical change favors people with more human capital.

Companies with the biggest IT investments typically made the biggest organizational changes, usually with a lag of five to seven years before seeing the full performance benefits.

This means that the best way to use new

technologies is usually not to make a literal substitution of a machine for each human worker, but to restructure the process.

“When a sergeant makes a mistake only the platoon suffers, but when a general makes a mistake the whole army suffers.”

Why are winner-take-all markets more common now? Shifts in the technology for production and distribution, particularly these three changes: a) the digitization of more and more

information, goods, and services, b) the vast improvements in telecommunications and, to a lesser extent, transportation, and c) the increased importance of networks and standards.

Spending by households on many of modern life’s “basics”—food at home, automobiles, clothing and footwear, household furnishings and equipment, and housing and utilities—fell from 53% of disposable income in 1950 to 44% in 1970 to 32% today. . .

The argument that technology cannot create ongoing structural unemployment, rather than just temporary spells of joblessness during recessions, rests on two pillars: 1) economic theory and 2) two hundred years of historical evidence. But both of these are less solid than they first appear. First, the theory. There are three economic mechanisms that are candidates for explaining technological unemployment: inelastic demand, rapid change, and severe inequality.

greater productivity leads to enough of an increase in demand that more labor ends up employed. The possibility of this happening for some types of energy has been called the Jevons paradox: more energy efficiency can sometimes lead to greater total energy consumption.

We’ve never seen a truly creative machine, or an entrepreneurial one, or an innovative one. We’ve seen software that could create lines of

English text that rhymed, but none that could write a true poem

“Judge a man by his questions, not his answers.”6

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.

skills of ideation, broad-frame pattern recognition, and complex communication.

Today, the cognitive skills of college graduates—including not only science, technology, engineering, and math, the so-called STEM disciplines, but also humanities, arts, and social sciences—are often complements to low-cost data and cheap computer power. This helps them command a premium wage.

We favor reducing unnecessary, redundant, and overly burdensome regulation, but recognize that this is likely to be slow and difficult work. First, regulators rarely like giving up authority once it’s granted to them. Second, those companies and industries protected by existing regulations will no doubt lobby strenuously to preserve their privileged positions. And third, separate sets of regulations exist at the federal, state, and municipal levels in America, so comprehensive change cannot be

brought about by any single entity.

Governments therefore have to strike a delicate balance; they have to provide enough intellectual property protection to encourage innovation but not so much that they stifle it.

1. Shine a spotlight on a problem or opportunity 2. Pay only for results 3. Target an ambitious goal without predicting which team or approach is most likely to succeed 4. Reach beyond usual suspects to tap top talent 5. Stimulate private-sector investment many times greater than the prize purse 6. Bring out-of-discipline perspectives to bear 7. Inspire risk taking by offering a level playing field 8. Establish clear target metrics and validation protocols

We don’t pretend that the policies we advocate here will be easy to adopt in the current political climate, or that if they somehow were all adopted they would immediately bring back full employment and rising average wages. We know that these are challenging times; many people have seen their fortunes suffer during the Great Recession and subsequent slow recovery and are being left behind by the twin forces of technology and globalization. Inequality and other forms of spread are increasing, and everyone is not sharing in all the types of bounty the economy is generating.

Capitalism allocates resources, generates innovation, rewards effort, and builds affluence with high efficiency, and these are extraordinarily important things to do well in a society.

boredom, vice, and need.”

The consequences of high neighborhood joblessness are more devastating than those of high neighborhood poverty. A neighborhood in which people are poor but employed is different from a neighborhood in which many people are poor and

jobless. Many of today’s problems in the inner-city ghetto neighborhoods—crime, family dissolution, welfare, low levels of social organization, and so on—are fundamentally a consequence of the disappearance of work.11

And we see two pieces of good news here. The first is that economists have developed interventions that encourage and reward work in ways that a basic income guarantee alone does not. The second is that innovators and entrepreneurs have developed technologies not only to substitute for human labor but also to complement it.

The Negative Income Tax

First, it’s subject to seeing minor initial flaws cascade via an unpredictable sequence into something much larger and more damaging.

Second, complex, tightly coupled systems make tempting targets for spies, criminals, and those who seek to wreak havoc.

destruction. The physical limits on how much damage any individual or small group could do are becoming less and less constrained.