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.
Taking the second point–that automated workplaces require higher skills–it’s not really that simple. Sometimes automation requires higher skills, sometimes it results in de-skilling of jobs. One example is a cashier, who not so long ago had to be able to do simple math. Now, many of them are lost if the POS terminal can’t do their calculations for them. Another example: in a factory, running a CNC machine tool (that has been programmed by someone else) is generally a lower-skill job than operating a manual machine tool. Finally, being a manager in a chain retail store where inventory & ordering are handled centrally (by automated ordering systems with some input from centralized buyers at HQ) is a lower-skill job than being a manager in a retail store where the manager has to manage inventory control directly.( See my post Myths of the Knowledge Society for further thoughts on skill requirements and technological evolution.)
The degree to which automation is used to reduce the skill requirements of a given job is not a function of technological determinism; it is a consequence of management choices. I understand that Costco, for example, gives individual store managers a higher degree of empowerment than does the typical chain store in which these functions are more highly centralized.
Tyler talks a great deal about “genius machines,” and returns repeatedly to the example of a program that acts as an assistant to human chess players. I would have liked to see him focus some attention and analysis on actual supposedly-smart systems that are actually now being used or recently have been used in business and other fields. One example might be the models that have been used to evaluate the risk of mortgage and other loans, both on an individual-loan basis and for tradable pools of mortgages. Another might be the autopilot and flight-control systems used in aviation, and the dispatcher-assistant programs used in the freight-rail industry. And then there are the Enterprise Resource Planning systems used in a wide variety of companies. (I have heard many comments by people about their companies’ ERP systems, but have never once heard anyone refer to “our genius ERP system.”)
It is true that automation and centralization tends to create some jobs which are more abstract and conceptual in their nature than were the jobs they replace–the case of a buyer in a centralized chain store versus the store manager doing his own buying in a very hands-on environment is a good example of this. This is really more a function of centralization more than of automation per se. And there is real danger in losing the intuitive feel for a marketplace via excessive reliance on purely-quantitative information, whether this information comes from 2013 “Big Data” systems, 1995 mainframe computer systems, or 1938 punched card systems. See Peter Drucker’s description of two old-line, hands on merchants, one of whom he calls “Uncle Henry” and the other of whom was Charlie Kellstadt of Sears. After relating some anecdotes about these two men and their management styles–and also introducing Uncle Henry’s son Irving, a Harvard B-school graduate, Drucker continues:
Fifty years or more ago the Uncle Henry’s and the Charlie Kellsadts dominated; then it was necessary for Son Irvin to emphasize systems, principles, and abstractions. There was need to balance the overly perceptual with a little conceptual discipline. I still remember the sense of liberation during those years in London when I stumbled onto the then new Symblolical Logic (which I later taught a few times), with its safeguards against tautologies and false analogies, against generalizing from isolated events, that is, from anecdotes, and its tools of semantic rigor. But now we again need the Uncle Henrys and Charlie Kellstadts. We have gone much too far toward dependence on untested quantification, toward symmetrical and purely formal models, toward argument from postulates rather than from experience, and toward moving from abstraction to abstraction without once touching the solid ground of concreteness. We are in danger of forgetting what Plato taught at the very beginning of systematic analysis and thought in the West, in two of the most beautiful and moving of his Dialogues, the Phaedrus and the Krito…They teach us that experience without the test of logic is not “rhetoric” but chitchat, and that logic without the test of experience is not “logic” but absurdity. Now we need to learn again what Charlie Kellstadt meant when he said, “How else can I see a problem in my mind’s eye?”
Companies that understand the point Drucker was making here are going to do better than those that place exclusive emphasis on “big data” and “genius machines.”
Regarding the overall questions of increasing inequality, and especially reduced class mobility, I would have like to see Tyler give more attention to the influence of government and runaway credentialism.
Anyhow, despite my disagreements a worthwhile book, which readers should find thought-provoking.
Has anyone else here read the book yet?