Productivity and Employment — A Structural Change?
Jared Bernstein has a post on long-term job growth with a graph showing the historical relationship between productivity and employment:
People sometimes worry that we’re getting too productive, able to satisfy the demands of our economy with “too few” workers. That’s an age-old worry, and those who want to downplay it cite the fact that, as the graph shows, there is a positive, not a negative, correlation between productivity and job growth overtime.
But look at the end of the graph. Productivity accelerates while employment growth decelerates. And that ain’t no blip either…it suggests the possibility of a structural change in this relationship.
Now here is the section on the relationship between workers and machines from my book The Lights in the Tunnel. Compare the graph above to the one from my book below and notice that they both have diverging lines that seem to be saying something similar:
The Average Worker and the Average Machine
Think of an average worker using an average machine somewhere in the economy. Obviously, in the real world there are millions of workers using millions of different machines. Over time, of course, those machines have gotten far more sophisticated. Imagine a typical machine that is generally representative of all machines in the economy. At one time, that machine might have been a water wheel driving a mill. Then it became something driven by a steam engine. Later, an industrial machine powered by electricity. Today, the machine is probably controlled by a computer or by embedded microprocessors.
As the average machine has gotten more sophisticated, the wages of the worker operating that machine have increased.* As I pointed out in the previous section, more sophisticated machines also make production more efficient and that results in lower prices and, therefore, more money left in consumers’ pockets. Consumers then go out and spend that extra money, and that creates jobs for more workers who are likewise operating machines that keep getting better.
Again, the question we have to ask is: Can this process continue forever? I think the answer is no, and the very unpleasant graph below illustrates this.
The problem, of course, is that machines are going to get more autonomous. You can see this in the graph at the point where the dotted line (conventional wisdom) and the solid line diverge. As more machines begin to run themselves, the value that the average worker adds begins to decline. Remember that we are talking here about average workers. To get the graph above, you might take the distribution of incomes in the United States and then eliminate both the richest and the poorest people. Then graph the average income of the remaining “typical” people (the bulk of consumers) over time. If you were to instead graph Gross Domestic Product (GDP) per capita, you would end up with a similar graph, but the divergence between the dotted and the solid lines would occur somewhat later. This is because the wealthiest people (who own the machines or have high skill levels) would initially benefit from automation and would drag up the average. Recall that we saw this in our tunnel simulation in Chapter 1.
Once the lines diverge, things get very ugly. This is because the basic mechanism that gets purchasing power into the hands of consumers is breaking down. Eventually, unemployment, low wages—and perhaps most importantly—consumer psychology will cause a very severe downturn. As the graph shows, within the context of our current economic rules, the idea of machines being “fully autonomous” is just a theoretical point that could never actually be reached.
Some people might feel that I am being overly simplistic in equating “technological progress” with “machines getting better.” After all, technology is not just physical machines; it is also techniques, processes and distributed knowledge. The reality, however, is that the historical distinction between machines and intellectual capital is blurring. It is now very difficult to separate innovative processes from the advancing information technology that nearly always enables and underlies them. Improved inventory management systems and database marketing are examples of innovative techniques, but they rely heavily on computers. In fact, we can conceivably think of nearly any process or technique as “software”—and, therefore, part of a machine.
If you still have trouble accepting this scenario, you might try asking yourself a couple of questions: (1) Is it possible for a machine to keep getting better forever without eventually becoming autonomous? (2) Even if it is possible, then wouldn’t the machine someday become so sophisticated that its operation would be beyond the ability of the vast majority of average people? And wouldn’t that lead right back to making the machine autonomous?
* The idea that long-term economic growth is, to a large extent, the result of advancing technology was formalized by economist Robert Solow in 1956. Economists have lots of different theories about how long-term growth and prosperity come about, but nearly all of them agree that technological progress plays a significant role.