Lately, there has been a fair amount of buzz in the economics blogosphere about the issue that I’ve been discussing here: Structural Unemployment.
If you read through these posts, however, you won’t see a lot of discussion about the case I’ve been making, which is that advancing technology is the primary culprit. I’ve been arguing that as machines and software become more capable, they are beginning to match the capabilities of the average worker. In other words, as technology advances, a larger and larger fraction of the population will essentially become unemployable. While I think advancing information technology is the primary force driving this, globalization is certainly also playing a major role. (But keep in mind that aspects of globalization such as service offshoring–moving a job electronically to a low wage country–are also technology driven).
The economists sometimes mention technology, but in general they find other “structural” issues to focus on. One that I have seen again and again is this idea that people can’t move to find work because their houses are underwater (the mortgage exceeds the equity). The emphasis given to this issue strikes me as almost silly. Are there any major population centers in the U.S. that have really low unemployment?
Even if people could sell their homes, would they really be motivated to load up the U-haul and move from a city with say 12% unemployment to one where it is only 9%? Have the economists lost sight of the fact that 9% unemployment is still basically a disaster? The few locales I’ve seen with unemployment significantly lower than that are rural or small cities (Bismark ND, for example)–places that are simply incapable of absorbing huge numbers of hopeful workers. Let’s get real: playing musical chairs in a generally miserable environment is not going to solve the unemployment problem.
Another thing the economists focus on is the idea of a skill mismatch. Structural unemployment, they say, occurs because workers don’t have the particular skills demanded by employers. While there’s little doubt that there’s some of this going on, again, I think this issue is given way too much emphasis. The idea that if we could simply re-train everyone, the problem would be solved is simply not credible. If you doubt that, ask any of the thousands of workers who have completed training programs, but still can’t find work.
Economists ought to realize that if a skill mismatch was really the fundamental issue, then employers would be far more willing to invest in training workers. In reality, this rarely happens even among the most highly regarded employers. Suppose Google, for example, is looking for an engineer with very specific skills. What are the chances that Google would hire and then re-train one of the many unemployed 40+ year-old engineers with a background in a slightly different technical area? Well, basically zero.
If employers were really suffering because of a skill mismatch, they could easily help fix the problem. They don’t because they have other, far more profitable options: they can hire offshore low wage workers, or they can invest in automation. Re-training millions of workers in the U.S. is likely to make a killing for the new for-profit schools that are quickly multiplying, but it won’t solve the unemployment problem.
Why are economists so reluctant to seriously consider the implications of advancing technology? I think a lot of it has to do with pure denial. If the problem is a skill mismatch, then there’s an easy conventional solution. If the problem’s a lack of labor mobility, then that will eventually work itself out. But what if the problem is relentlessly advancing technology? What if we are getting close to a “tipping point” where autonomous technology can do the typical jobs that are required by the economy as well as an average worker? Well, that is basically UNTHINKABLE. It’s unthinkable because there are NO conventional solutions.
In my book, The Lights in the Tunnel: Automation, Accelerating Technology, and the Economy of the Future, I do propose a (theoretical) solution, but I would be the first to admit that any viable solution to such a problem would have to be both radical and politically untenable in today’s environment. That’s why I don’t spend much time suggesting solutions here: what would be the point? (but please do read the book–it’s free). I think the first step is to get past denial and start to at least seriously think about the problem in a rational way.
The few economists that have visited my econfuture.wordpress blog and commented on my previous posts have generally barricaded themselves behind economic principles that were formulated more than a century ago (see the comments on my posts about these economic concepts: lump of labour fallacy and comparative advantage).
Most economists seem to be unwilling to really consider this issue–perhaps because it threatens nearly all the assumptions they hold dear. I wrote about this in my first blog post . We’ll see how long it takes for the economists to wake up to what is really happening.
About The Author: Martin Ford is the founder of a Silicon Valley-based software development firm. He holds a computer engineering degree from the University of Michigan, Ann Arbor and a graduate business degree from the University of California, Los Angeles. He is the author of The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future (available from Amazon or as a FREE PDF eBook) and has a blog at econfuture.wordpress.com.