Evolution versus revolution

I have heard it said that the process of improving our processes of doing things is evolutionary, and not revolutionary. The point is made that it is desirable to follow the course of evolution, and make small gradual changes to optimize our way of doing things. I want to consider this analogy through a number of other analogies.

Just how smart is it to be an ape?

In college, I took a primate psychology course in which I was required to write a paper. I had always been puzzled by the fact that the apes are in general not very successful species, so I tried to answer my puzzlement in my paper. It seemed to me that higher intelligence would imply greater adaptability, and hence greater success.

I started my paper by comparing the apes with other mammals which occupy similar niches. The pairings I made were between the gibbon and the spider monkey, the chimpanzee and the baboon, the orangutan and the tree sloth, the gorilla and the bear. In each case the ape in the pairing was less successful. Three of the apes are also on the endangered species list. The point is clear that there must be something detrimental acquired along with intelligence.

I noted two costs associated with intelligence. First, the additional size of the brain requires that the young be birthed earlier, and hence babies are more helpless and less viable. Furthermore, birth is considerably more stressful for the mother because of the larger head size. Second, the young are dependent on the parents for a much longer period, because of the shift from a "ROM based system" to a "RAM based system".

My conclusion was that, in the range of intelligence inhabited by the apes, the detriments of intelligence outweigh the benefits. I got an A+ on the paper. That was awesome.

The search for the missing link

Years later, I read a book entitled, The Panda's Thumb[1]. The author talks at great length about the fruitless search for the missing links in the fossil record between species. He argues that, while this could be explained by our sparse sampling of the geologic record, the lack of evidence points to our misconception about the evolutionary process. He claims that evolution is not always a gradual process, but that new species are created only when evolution occurs in spurts.

His argument is that, since creatures are generally fairly well fine-tuned to their environment, small changes are likely to be less viable, and will not survive. Only by making large and abrupt changes can a new species find a more successful niche. I think he was probably inspired by my paper.

A-kneeling at the optimal point

This idea is related to problems encountered with the numerical optimization of functions. The goal is to write a computer program which can automatically find the maximum of an arbitrary function. If we could be guaranteed of functions which have only a single local maximum, this is relatively easy. Methods for this have existed since Newton. They all basically steer themselves uphill until they find a flat spot. Unfortunately, in the real world, functions rarely constrain themselves to a single local maximum. Depending upon where you start, you may find yourself on a peak that is not the peak.

There is a numerical optimization method called simulated annealing [2] which can avoid getting caught in a local maximum. It is a procedure which is modeled after the annealing process.

Annealing is the process by which knife blades and the turbine blades in a jet engine are hardened. The piece is first raised to a very high temperature, enabling the molecules to wander around freely, rather than immediately seeking the lowest energy state they can find. Slowly the temperature is lowered, and molecules gradually settle into lower energy states. At any time, they are free to wander around, but as the temperatures goes down, this becomes less likely. The key feature to annealing's ability to find the lowest energy state (a single crystal) is that molecules are allowed to pass through higher energy states.

The numerical annealing process does not force that the method always head uphill. At each stage, the choice between uphill and downhill is random. As the method proceeds, the uphill choice becomes more likely; just as lowering the temperature makes the transitions out of lower energy states less likely.

Application 

I have seen this process play out again and again.

I first started pondering the relationship between evolution and revolution when I was trying to understand what made engineering groups work and what made them fail. For a very small group of engineers, it is acceptable, and in fact, most efficient, to keep everything informal - specs, documentation, project planning.

As an engineering group gets bigger, it goes through a phase where making incremental increases in the amount of structure just plain does not work. Wholesale changes must occur in order for the larger group to be efficient. I lived through a few of these. They were painful, but revolutionary evolution was necessary.


In a previous post about printing standards and a panel discussion I led at GraphExpo, I discussed the issues with optical brightening agents in printing. Several steps must be taken to solve the problem. I lamented that taking only one of these steps will make things worse. Evolutionary revolution is required.

While I am on the subject of standards, let me make an observation. As a member of a few standards committees, I have come to realize that you can never change a standard. Even though a standard makes sense, there will be always be those who cannot adapt to whatever new stuff is put into place. This requires evolutionary revolution to make it work.

Here is a quote from an article that appeared on my LinkedIn page today. Same topic. Evolutionary revolution is necessary.
"As organizations continue to evolve within an ever-changing external environment, it has become quite evident that things are shifting talent- wise. This will not likely manifest as a small iterative adjustment in how we view, attract and develop talent. Rather, it seems destined to become a long overdue metamorphosis concerning our most important asset - people."

The patent fight between Apple and Motorola is another example. There are industries where there are very few patent attorneys. And there are industries where every company needs to have a bushel basket full of them. The transition of an industry from one to the other is an evolutionary revolution. A company cannot survive if the competitors have more patent attorneys.

In all these cases, we are not faced with a choice between evolution and revolution, evolution is revolution.

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[1] Stephen Jay Gould, The Panda’s Thumb, W. W. Norton and Co., 1980

[2] Press, William, Brian Flannery, Saul Teukolsky, William Vetterling, Numerical Recipes, the Art of Scientific Computing