Tyler Cowen, in his recent book Average Is Over, argues that computer technology is creating a sharp economic and class distinction between people who know how to effectively use these “genius machines” (a term he uses over and over) and those who don’t, and is also increasing inequality in other ways. Isegoria recently excerpted some of his Tyler’s comments on this thesis from a recent New Yorker article.
I read the book a couple of months ago, and although it’s worth reading and is occasionally thought-provoking, I think much of what Tyler has to say is wrong-headed. In the New Yorker article, for example, he says:
The first (reason why increased inequality is here to stay) is just measurement of worker value. We’re doing a lot to measure what workers are contributing to businesses, and, when you do that, very often you end up paying some people less and other people more.
The second is automation — especially in terms of smart software. Today’s workplaces are often more complicated than, say, a factory for General Motors was in 1962. They require higher skills. People who have those skills are very often doing extremely well, but a lot of people don’t have them, and that increases inequality.
And the third point is globalization. There’s a lot more unskilled labor in the world, and that creates downward pressure on unskilled labor in the United States. On the global level, inequality is down dramatically — we shouldn’t forget that. But within each country, or almost every country, inequality is up.
Taking the first point: Businesses and other organizations have been measuring “what workers are contributing” for a long, long time. Consider piecework. Sales commissions. Criteria-based bonuses for regional and division executives. All of these things are very old hat. Indeed, quite a few manufacturers have decided that it is unwise to take the quantitative measurement of performance down to an individual level, in cases where the work is being done by a closely-coupled team.
It is true that advancing computer technology makes it feasible to measure more dimensions of an individual’s work, but so what? Does the fact that I can measure (say) a call-center operator on 33 different criteria really tell me anything about what he is contributing the the business?
Anyone with real-life business experience will tell you that it is very, very difficult to create measurement and incentive plans that actually work in ways that are truly beneficial to the business. This is true in sales commission plans, it is true in manufacturing (I talked with one factory manager who said he dropped piecework because it was encouraging workers to risk injury in order to maximize their payoffs), and it is true in executive compensation. Our blogfriend Bill Waddell has frequently written about the ways in which accounting systems can distort decision-making in ultimately unprofitable ways. The design of worthwhile measurement and incentive plans has very little to do with the understanding of computer technology; it has a great deal to do with understanding of human nature and of the deep economic structure of the business.