Methodological Lessons from Self-Experimentation (part 3 of 4)

4. There are serious defects in the way science is usually done. I found a new and powerful way of losing weight — yet I’m an outsider to that area. Although obesity is a huge problem, and hundreds of millions of dollars go into obesity research every year, I was completely outside that group of people and resources. If science is being done properly, there should be a relation between input and output — the more input, the more output. That failed here. Professional obesity researchers, given vast input, failed to discover this; whereas I, given zero input, managed to do so. You might say this was a weird fluke except the same thing happened again with mood: I discovered a powerful way of changing mood, even though I was an outsider to the study of mood. Depression is a huge problem, vast resources go into trying to do something about it.

What the serious defects are has no simple answer. After the next lesson learned I’ll try to explain what I think is wrong.

5. There are serious strengths in the way science is usually done. I relied heavily on conventional science and could never have gotten where I did without it. Ramirez and Cabanac did brilliant research. I say there are serious strengths in conventional science because I used conventional scientific methods and conclusions to find a new solution to a serious problem — obesity is a serious problem. I didn’t just use conventional scientific tools; I also used self-experimentation, which is unconventional. But self-experimentation alone wouldn’t have gotten very far, I’m sure. The turning point in my weight control research was reading a paper by Ramirez about rat experiments. Not only did I use a vast number of conclusions from conventional science, I also used conventional experimental designs and standard, common tools for data analysis, such as programs for plotting data.

To say that science is glorified common sense has a lot of truth to it. To say that science is a collection of methods to help us understand and control the world also has a lot of truth to it. But science is far more than a collection of tools; it is a whole community and culture, with beliefs as well as tools. Like any culture, many of its beliefs are based on faith.

Here is a story to illustrate what happens. It’s pure human nature. Suppose someone gave you a power saw. Your first thought is: Wow, I have a power saw. There are many things I can now do that I couldn’t do before. It seems like a pure benefit. No negatives. You learn how to use the power saw and you become better and better at using it. Eventually you start to make a living using the power saw — other people, who don’t have a power saw, pay you to saw stuff for them. You become a power-saw professional and, along with other professionals, you establish rules about how to use power saws. To save the public from bad power saw usage, you establish a licensing test to become a power-saw professional. Your view of yourself is: I know how to use a power saw. And if there is a problem to be solved, you try to solve it with your power saw — that’s what you know how to do best. All this makes perfect sense to you. Hundreds of professions have followed this path. What is hard for you to notice is that in certain ways you have become weaker — if a problem doesn’t call for power-saw usage, you are less likely to find the solution. Because you are too busy making a living using your power saw.

I hope my point is obvious. Budding scientists go to graduate school where they learn a bundle of specialized research methods that varies from one research area to the next. That is their power saw. After graduate school, they make a living using the techniques that they have learned. After graduate school, they are in better shape to make a living; but they are in worse shape to solve problems for which the techniques that they have learned are not appropriate. Conventional scientific methods could go part of the way toward finding the Shangri-La Diet; but they could not go all the way. Other techniques were needed — very simple ones, pre-power-saw. So conventional science never found it.

In Dark Age Ahead, Jane Jacobs gives another example of this. During a recent heat wave in Chicago, two nearby neighborhoods, similar in many ways, had very different death rates. A good explanation of the difference was provided by a graduate student in sociology, who used very simple very low-cost methods. In contrast, a task force of scientists from the Centers For Disease Control, with vast resources and great methodological sophistication, failed to explain the difference. They were blinded by their expertise. They failed to see that their methods weren’t working.

Read Part 1 and Part 2.