The Next Industrial Revolution
An interview with the Economist columnist Ryan Avent on his new book about how technology will change the labor force
By DEREK THOMPSON
Sep 6 2016
A “crisis of abundance” initially seems like a paradox. After all, abundance is the ultimate goal of technology and economics. But consider the early history of the electric washing machine. In the 1920s, factories churned them out in droves. (With the average output of manufacturing workers rising by a third between 1923 and 1929, making more washing machines was relatively cheap.) But as the decade ended, factories saw they were making many more than American households demanded. Companies cut back their output and laid off workers even before the stock market crashed in 1929. Indeed, some economists have said that the oversupply of consumer goods like washing machines may have been one of the causes of the Great Depression.
What initially looked like abundance was really something more harmful: overproduction. In economics, as in anything, too much of a good thing can be problematic.
That sentiment is one of the central theses of The Wealth of Humans, a new book by the Economist columnist Ryan Avent about how technology is changing the nature of work. In the next few years, self-driving cars, health-care robots, machine learning, and other technology will complement many workers in the office. Counting both humans and machines, the world’s labor force will be able to do more work than ever before. But this abundance of workers—both those made of cells and those made of bits—could create a glut of labor. The machines may render many humans as redundant as so many vintage washing machines.
Once again, what once seems like abundance will instead be over-supply: The machines may invent their makers out of work.
Last week, I spoke with Avent about his book, how his theories might help to explain the 2016 election, and the future of working. The following conversation has been edited for clarity and concision.
Derek Thompson: In classic Economist style, your title, The Wealth of Humans, is doing double or triple duty. First, it’s a play on Adam Smith’s The Wealth of Nations, and indeed there’s a lot of Smith in here. Second, it’s a book about the most common definition of wealth, money, and how it might be earned and distributed in the future. Third, it’s about Merriam-Webster’s second definition of wealth, which is a surfeit, a surplus, and your argument is that we may be entering a world with too many workers. Anything I’m missing?
Ryan Avent: Those were the ones I had in mind. There may be others lurking.
Thompson: There is an ongoing debate about whether technological growth is accelerating, as economists like Erik Brynjolfsson and Andrew McAfee (the authors of The Second Machine Age) insist, or slowing down, as the national productivity numbers indicate. Where do you come down?
Avent: I come down squarely in the Brynjolfsson and McAfee camp and strongly disagree with economists like Robert Gordon, who have said that growth is basically over. I think the digital revolution is probably going to be as important and transformative as the industrial revolution. The main reason is machine intelligence, a general-purpose technology that can be used anywhere, from driving cars to customer service, and it’s getting better very, very quickly. There’s no reason to think that improvement will slow down, whether or not Moore’s Law continues.
I think this transformative revolution will create an abundance of labor. It will create enormous growth in [the supply of workers and machines], automating a lot of industries and boosting productivity. When you have this glut of workers, it plays havoc with existing institutions.
I think we are headed for a really important era in economic history. The Industrial Revolution is a pretty good guide of what that will look like. There will have to be a societal negotiation for how to share the gains from growth. That process will be long and drawn out. It will involve intense ideological conflict, and history suggests that a lot will go wrong.
Thompson: Even I would admit that is a weird time to predict the end of work, considering that the unemployment rate has been at or under 5 percent all year, the private sector in the U.S. has created jobs for record-high 77 consecutive months, and wages are actually rising at their fastest rate since the Great Recession.
So what is the best evidence that your prediction is plausible?
Avent: I would say the best evidence comes from the wage growth numbers. I know we’ve experienced an uptick in recent months, but we’re seven years into the recovery and still well short of the level of nominal wage growth we would expect, even compared to recent disappointing recoveries. In the bigger picture, for a lot of middle-skilled workers, especially men, you have stagnating wages for several decades. Apart from the top 1 percent, a lot of people are having a lousy time.
If you look at the experience of rich countries across the world, you see there is a tradeoff between wage growth, productivity, and employment growth. Employment in Britain is at an all-time high, and wage growth there has underperformed America and most of Europe. This suggests that the main way that employers are using people in countries like the U.K. is to use them to do low-productivity work.
Thompson: There is a familiar story of technology and the labor force that one might call the “we used to” story. We used to work on farms, we used to work in textiles, we used to work in factories … What’s the next chapter of the “we used to” story? What sector currently employing a lot of Americans is the lowest-hanging fruit for disruption?
Avent: Driving is certainly an area where we’ve seen more rapid progress than I would have guessed. Truck drivers, bus drivers, and train drivers have pretty good pay and those account for millions of jobs. Most importantly, there seems to be an interest among companies employing those workers to bring [the tech that would replace humans] forward. In the long run, I’m optimistic for technology to transform health care, but that’s a harder sector to disrupt.
Machine intelligence will be applied in ways we cannot imagine yet. One example is talking. Today, if you have a problem with a car company, you might end up conversing with a bot over the phone. Those are conversations that we thought weren’t automatable that are now. We used to employ a lot of people to talk to people and people have those conversations with bots.