9 Is the real world too “messy” for scientific laws to work?

When laws adequately predict outcomes in the real world

This is the tenth post in this series. If you haven’t read the Introduction titled The Myth of Scientific Uncertainty, and posts numbered 1-8, you may want to do those first. under “archives.”

In this section, we address the third pillar of scientific uncertainty, which is that our ‘simple’ laws do not apply in the real world where multiple phenomena can affect the outcome.

The philosopher best known for this argument is Nancy Cartwright[1]. Her point is that measurement results can only be confined to a single cause or phenomenon under carefully controlled conditions (read laboratory). In the real world, even in as simple a case as Newton’s law relating force, momentum, and acceleration, other phenomena occur when applied to a vehicle on a street. They include friction with the surface and air resistance to the vehicle’s motion. In predicting the trajectory of a falling leaf, air currents and the leaf’s orientation affect the outcome.

Cartwright is, of course, correct that observations in the real world are rarely constrained to a single phenomenon. Indeed, it would be hard to find, even in the laboratory, experiments that are free of extraneous influences. Every experimental scientist knows that her measurements have a degree of imprecision. Measurements precise to one part in a million have variations in the seventh decimal place because of uncontrolled variables.

So, exactness in a measurement is virtually always a matter of degree. The critical question then is whether it meets the need of its application. The measurement devices used by carpenters framing a house are less exact than those used by cabinet makers. The pH strips with which one measures the acidity of spa water are crude compared to the pH meters used in biological research. But each meets its need.

Experimental scientists spend a substantial part of their time determining whether their measurement results are exact enough to support the conclusions they deduce from their experiment. Statistical data analysis tools, and the skill in using them are essential parts of scientist’s kit and training. The reviews of papers include critiques of data analysis.

That brings us to the question of whether a measurement, which meets the need of its application, is wrong because it is not perfectly exact. From a practical standpoint, it is correct. The same is true from a philosophical point of view. Some observations can be clearly true or false. Jack is wearing a shirt with a buttoned front, or he isn’t. But the determination of how long it takes him to put it on involves a numerical measurement which may be accurate to the minute or microsecond. In any case, there will be a limited number of places in the result and therefore an uncertainty in the following place. Expecting the number of significant places to be infinite denies the validity of virtually every measurement ever made.

Yes, the world is messy. But is it too messy for scientific measurements to be valid? Our scientific laws make useful predictions consistently. They work because their accuracy and precision are sufficient for the task at hand. The greater the precision the task requires, the more we must control the conditions affecting reproducibility.

In the other direction, when the uncontrolled variables are too many or too complex, the accuracy of prediction may be less than desired. We can show when the conditions for cyclones are favorable, but not exactly where they will hit or when. We can assess the general effectiveness of a vaccine, but not predict which people will not be immunized. The political, economic, and social “sciences” are another matter altogether.

We look for better means to assess the uncontrolled variables in situations that constrain the predictive power of our physical and chemical laws. But it is overly harsh to cast doubt on the usefulness of all laws because of those situations in which variations in factors are too many and/or too large for the predictive power we would like to have. In the physical sciences, we know when that is the case. And we shouldn’t forget the vast number of cases where the application of scientific laws forms the basis of our way of life.

But we have found another way to deal with the problem of multiple phenomena significantly affecting an outcome. In the next post, we will explore the means we have developed for achieving degrees of predictability in situations where multiple factors play a part. It is another way to circumvent some of the messiness of the world.

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[1] Cartwright, Nancy, How the Laws of Physics Lie, Oxford University Press, 1983.

Please spread the word that there are some things we know for sure.

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