David Autor – American economist
Here’s a startling fact: in the 45 years since the introduction of the automated teller machine, those vending machines that dispense cash, the number of human bank tellers employed in the United States has roughly doubled, from about a quarter of a million to a half a million. A quarter of a million in 1970 to about a half a million today, with 100,000 added since the year 2000.
These facts, revealed in a recent book by Boston University economist James Bessen, raise an intriguing question: what are all those tellers doing, and why hasn’t automation eliminated their employment by now? If you think about it, many of the great inventions of the last 200 years were designed to replace human labor.
Tractors were developed to substitute mechanical power for human physical toil. Assembly lines were engineered to replace inconsistent human handiwork with machine perfection. Computers were programmed to swap out error-prone, inconsistent human calculation with digital perfection.
These inventions have worked. We no longer dig ditches by hand, pound tools out of wrought iron or do bookkeeping using actual books. And yet, the fraction of US adults employed in the labor market is higher now in 2016 than it was 125 years ago, in 1890, and it’s risen in just about every decade in the intervening 125 years.
This poses a paradox. Our machines increasingly do our work for us. Why doesn’t this make our labor redundant and our skills obsolete? Why are there still so many jobs? I’m going to try to answer that question tonight, and along the way, I’m going to tell you what this means for the future of work and the challenges that automation does and does not pose for our society.
Why are there so many jobs? There are actually two fundamental economic principles at stake. One has to do with human genius and creativity. The other has to do with human insatiability, or greed, if you like. I’m going to call the first of these the O-ring principle, and it determines the type of work that we do.
The second principle is the never-get-enough principle, and it determines how many jobs there actually are.
Let’s start with the O-ring. ATMs, automated teller machines, had two countervailing effects on bank teller employment. As you would expect, they replaced a lot of teller tasks. The number of tellers per branch fell by about a third. But banks quickly discovered that it also was cheaper to open new branches, and the number of bank branches increased by about 40% in the same time period. The net result was more branches and more tellers.
But those tellers were doing somewhat different work. As their routine, cash-handling tasks receded, they became less like checkout clerks and more like salespeople, forging relationships with customers, solving problems and introducing them to new products like credit cards, loans and investments: more tellers doing a more cognitively demanding job.
There’s a general principle here. Most of the work that we do requires a multiplicity of skills, and brains and brawn, technical expertise and intuitive mastery, perspiration and inspiration in the words of Thomas Edison.
In general, automating some subset of those tasks doesn’t make the other ones unnecessary. In fact, it makes them more important. It increases their economic value.
Let me give you a stark example. In 1986, the space shuttle Challenger exploded and crashed back down to Earth less than two minutes after takeoff. The cause of that crash, it turned out, was an inexpensive rubber O-ring in the booster rocket that had frozen on the launchpad the night before and failed catastrophically moments after takeoff.
In this multi-billion dollar enterprise that simple rubber O-ring made the difference between mission success and the calamitous death of seven astronauts. An ingenious metaphor for this tragic setting is the O-ring production function, named by Harvard economist Michael Kremer after the Challenger disaster.
The O-ring production function conceives of the work as a series of interlocking steps, links in a chain. Every one of those links must hold for the mission to succeed. If any of them fails, the mission, or the product or the service, comes crashing down.
This precarious situation has a surprisingly positive implication, which is that improvements in the reliability of any one link in the chain increases the value of improving any of the other links.
Concretely, if most of the links are brittle and prone to breakage, the fact that your link is not that reliable is not that important. Probably something else will break anyway. But as all the other links become robust and reliable, the importance of your link becomes more essential. In the limit, everything depends upon it.
The reason the O-ring was critical to space shuttle Challenger is because everything else worked perfectly. If the Challenger were kind of the space era equivalent of Microsoft Windows 2000 — the reliability of the O-ring wouldn’t have mattered because the machine would have crashed.