Personal Science is to Professional Science as Professional Science is to Engineering

A few days ago I gave a talk at Microsoft Beijing titled “The Rise of Personal Science: Discoveries about Acne, Blood Sugar, Mood, Weight Loss, Sleep, and Brain Function.” (Thanks to Richard Sprague, who invited me.) The audience was engineers.

In response to a question, I said that the relationship between personal science and professional science resembled the relationship between professional science and engineering. Cause-effect statements (X causes Y) vary in their degree of plausibility anywhere from zero (can’t possibly be true) to one (absolute certainty). Engineers, professional scientists, and personal scientists tend to work at different places along this scale:

Engineers work with cause-effect relationships at the top of the scale, that are well-established. (For example, Newton’s Laws.) Relationships in which we have total confidence.

Professional scientists like to study cause-effect relationships that are in the middle of the scale of degree of belief: true and false are equally plausible. When both true and false are plausible, you can publish the results no matter what you find. If everyone already agrees that X causes Y, further evidence isn’t publishable — too obvious. If it is highly implausible that X causes Y, professional scientists cannot study the question because a test of whether X causes Y is too unlikely to pay off. If you find that X does cause Y you can publish it but that’s too unlikely. Finding that X does not cause Y is unpublishable (“we already knew that”).

Personal scientists can easily test ideas with low plausibility. First, because personal science is cheap. Many tests cost nothing. Second, because what other people think is irrelevant. (A professional scientist who takes seriously an idea that “everyone knows is nonsense” risks loss of reputation.) Third, because there is no pressure to produce a steady stream of publications. An example of a personal scientist testing an idea with low plausibility is when I tested the idea that standing causes weight loss. I thought it was unlikely (and, indeed, I didn’t lose weight when I stood much more than usual). But I could easily test it. It led me to discover that standing a lot improves my sleep.

Plainly we need all three (engineers, professional scientists, personal scientists). Has anyone reading this heard someone besides me make this point?

I have been shocked — I sort of continue to be shocked — how much I have been able to discover via personal science. But a high rate of discovery makes sense if personal science supplies a necessary ingredient — ability to test low-plausibility ideas — that has been missing.

3 Replies to “Personal Science is to Professional Science as Professional Science is to Engineering”

  1. Maybe because you actually have an educational background in statistics and psychology I think you have a slight advantage at personal science. I also think you might have a more innate ability for observation. Some people are able analysis their behavior but are unable to be successful.

    The question then is why is Seth Roberts so successful at personal science/low plausibility ideas while others fail?

    For instance, I tried an extremely low-salt diet (low-flavor) and was able to lose 10 pounds. Then I could not stand the lack of flavor and started to eat salt again thus gaining back all the weight.

    I have been doing personal science all my life with abysmal outcomes. I can’t think of any idea I have ever come up after careful observation has changed my life in a significant way.

    Seth: My weight loss ideas derived from a combination of unexpected observation and new theory. But a lot of other things I have found that worked came from long-term monitoring (e.g., sleep) that turned up a sudden change. That’s what led me to study one-legged standing and butter, for example. I think long-term monitoring is something many people can do.

  2. Not quite, but nearly on the same track – I have been reading the beginning of Good Disruptive Change ( where Susan Alexander talks about the importance of measurement for keeping track of change.

    This seems to me as personal science in action – even if it is only for the benefit of the originator.

  3. Why is it important to make sure a medical ultrasound is properly calibrated and maintained?

    “Ultrasound is used in labs normally for lysing cells, for ripping them open and getting out the DNA,”
    So, how many ways can medical ultrasound go wrong and create the same effect? Can it accidentally get lensed or echo?

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