In-sourcing

The big business news of the moment, other than cheap oil and gas from fracking, is the continuing growth in US manufacturing. What this hasn't meant is a ton of new jobs. The reason for this is pretty simple, US workers are about three times more efficient than Chinese workers doing the same job. That means you need a third of the staff to get the same output.

The other thing this means is you need to be more efficient to get these jobs. Assembly lines no longer represent rote tasks you can train anyone to do. You have to be capable of learning to operate a complex machine, and meet all the complicated social rules of the modern workplace too. This leaves a lot of people at the bottom of the ability distribution without a means of making a decent living.

The massive productivity of American workers means that we can actually afford to have a significant fraction of the population not doing useful work, but this is ultimately dehumanizing to those stuck at the bottom. I have no idea what to do about this, but it is only going to get worse as the economy improves.

h/t Steve Hsu

Laws of Human Nature: The Map is not the Territory

The first article I read about the laws of human nature today was about a numerical simulation of the Peter Principle, which states that employees keep getting promoted until the point where they can no longer perform their jobs well. This simulation is pretty clever, but I don't know that is in fact quite as revolutionary as the article hints. Based on the random ability model the authors created, the optimal promotion strategy is to select employees at random for promotions. This is pretty clearly bad for morale.

It sounds counter-intuitive, but the best promotion strategy might be to choose people at random.

"This is a really interesting alternative approach to looking at the Peter principle," says Rajiv Mehta, a professor of marketing at the New Jersey Institute of Technology in Newark. "But it would turn on its head almost every established theory of human behaviour and would face a multitude of problems."

The other principle we ought to keep in mind here is the map is not the territory: the model is not reality. I think this model could probably be turned into something really useful if it took into account the distribution of abilities such as g and the OCEAN personality factors, plus the experience people gain on the job. I think the model is just too simple to be actually useful, rather than an interesting exercise. I really like the attempt to apply a quantitative model, it just needs to much more complicated.

I will be curious to see whether the authors of the study follow up on this, or if it was just a one-off neat idea they had. This was done by a group of physicists, and I suspect that they are not really interested in getting into all the details it would take to get this right. Physicists are notorious for their simplifying assumptions [well, assume you have a perfectly spherical cow....] and I think this tendency is at play here. Philosophers are subject to the same tendency these days, so strongly wedded to simplicity that they will prefer a simple theory even when it doesn't work quite right. I am grateful that I have worked as an engineer because it has attuned me to complexity. I have to attempt to optimize 50 attributes at the same time, and I don't understand many of them very well, but I have to get on with it nonetheless. Physics and philosophy alike tend to make simplifying assumptions in order to make problems solvable, whereas I do not have that luxury.

I followed a link in the New Scientist article, and I found another post on 5 Laws of Human Nature that is also interesting. Among the 5 laws listed in the second New Scientist article is Parkinson's Law, named for C. Northcote Parkinson. Parkinson is on my list of people to read real soon now. I started reading The Evolution of Political Thought, which is an updating of Aristotle for the XXth century, but I found Parkinson's style idiosyncratic, so I decided to put the book down and come back to it later.

The other laws, Pareto's principle especially, are also worth attention.

h/t John D Cook

Physics for Future Presidents

Physics for Future Presidents is a course offered by Richard Muller at Berkeley. The course is intended primarily for liberal arts types, but Muller opened the course up to physics majors because the subject matter is not typically covered in the required courses.

This course really is amazing: it covers the essential science to understand modern technology, especially the technology that is likely to make a big impact on our lives, and is interesting besides. Nuclear power. Spy satellites. Low earth orbits. Moore's Law.

The objective of the course is understanding, not computation. An entirely reasonable goal. As Muller says, if you really need to calculate something physical, you hire a physicist (or an engineer). However, you need to be able to understand the science well enough to make a good judgment about what you are given, and what to do with it. Something along these lines would be much more effective than forcing all college students to take lab science, because this class effectively focuses on the big picture. Learning how to titrate in University Chemistry I does not necessarily make for scientific insight or good judgment. Learning how to compute a surface integral for Gauss' Law is really no better for that purpose (albeit fun).

That being said, I don't know how well this course would work on the general student population at say, Northern Arizona University (my alma mater). Jokes about liberal arts majors aside, anyone who gets into Berkeley is pretty damn smart. Students at a state college are much closer to the population mean in intellectual ability, so this course may be too hard for them as is. However, I think there is something to this. The science courses offered at most universities really are more like vocational training for scientists than the building blocks of a liberal education. The unelected elites that Charles Murray talks about really do need to understand science, but good judgment is more important than the calculus.

If you ever wanted to know more about science, but hated the classes, or couldn't hack the math, buy the popular version of the book, or watch the lectures on YouTube. It would be better if more people understood science in this fashion.