Philosophy of Science Part 3: Physics Envy

Part 1, Part 2

There's a fantastic XKCD comic strip that discusses the relative "purity" of the sciences, ranking them with physics and math on top. And, indeed, in the history of the sciences, physics tends to get top billing- it's the most glamorous and the top physicists are the scientists most likely to be household names. There is a very real popular sense of physics being the most important science.

The Hubble Deep Field, the farthest away optical view of the universe we have. Definitely going to be putting a few photos in this article just because they look cool. [Image source]

This sense doesn't come from nowhere- physics does have a tendency to get clearcut, mindblowing results. It was getting scientific answers with precision and mathematical exactitude far beyond the other sciences during the early days of the industrial revolution and well into the nineteenth century. And, of course, other science started getting jealous, and physics envy was born. Other sciences began regularly trying to make themselves resemble physics. The social sciences are most frequently accused of physics envy, but it's present in many other hard sciences as well. Almost regardless of where it shows up, however, it tends to be Procrustean to its new home. (In Greek mythology, Procrustes was an innkeeper who chopped of his guests feet if they were too tall so that they'd fit in the guest bed.)

The worst offender is almost certainly economics, stretching all the way back to the early Marginalists. Early economists regularly tried to include concepts from physics wholesale into economics. Mechanical equilibrium was an especial favorite of those early economists- they actually ported it into economics wholesale. In retrospect this was obviously immensely foolish- economies are complex systems, and complex systems don't have equilibrated resting points like simple mechanical systems do. The direct inclusion of this (and other) models and physics did serious harm to economists understanding of the economy and their ability to make economic predictions.

A stable equilibria in a mechanical system. When economists tried to apply the idea to economics, they claimed that such stable equilibria existed for economies, and that economic upheavals would be inevitably followed by a return to said equilibria. This has fairly conclusively been shown not to be true these days. [Image source]

This isn't a vanished habit in economics, either. It's where concepts like the "rational consumer" come from. The rational consumer idea claims that people behave in a fundamentally rational manner in a market economy, which allows their behavior to be easily and precisely modeled in economic computer models that suspiciously resemble the computer models of physics. In actuality, however, consumers are seldom rational- they often act in economically inefficient and irrational manners- for instance, buying gas at the nearest gas station, even though it's much more expensive and considerably more money would be saved by driving farther to the next one- often even more than your time is worth according to your average hourly earnings. And yet people do this constantly, because humans don't measure their every free hour in terms of dollars- we're much more concerned with entertainment, socialization, a sense of artistic accomplishment, and other factors that are hard to quantify. Even our work hours are measured as much by our boredom as our wage. (Not to mention that simple number crunching shows that investors frequently act in absolutely ridiculous ways when dealing with risk that pretty clearly shows how bad humans are at acting rationally in many situations.)

There are also other criticisms revolving around that not all humans live in market economies- many live in gift economies, for instance, while many indigenous people around the world live in a fundamentally communitarian societies where the economic values of activities are hardly, if at all, measured by any means. Even people in market economies seldom live in pure ones- there are quite often elements of non-market economies mixed in. (Ever brought a fruit basket to a new neighbor, or helped a friend move just to be nice? Calling those things market activities is practically [Dadaistic](https://en.wikipedia.org/wiki/Dada_ in its absurdity.) These criticisms might seem a little tangential to the focus of this article, but it speaks strongly about one particularly damaging effect of physics envy- a tendency for scientists in its grasps to attempt to homogenize data sets in order to better fit them into models. The more diverse the individual entities in the data set are, the more harmful this process is going to be to the quality and rigor of the science, and gives a major clue as to why physics envy seems more dangerous in the social sciences than the hard sciences. Electrons might be universally uniform, but people sure as hell aren't.

[Image source]

To be clear, economics as a field is pretty aware of the problem. As I've mentioned before, economists are very aware of the bad reputation they've earned in many areas over the years, and many of them are actively seeking to confront the issue, in a variety of ways. (An expert in any field is much more likely to be aware of major criticisms in their field than an outsider is, and long before them as well.) Economics is, for instance, drawing on evolutionary and ecological models with increasing frequency these days. Since evolution and ecology both involve complex systems that resemble economies in many ways, this tends to be a much, much better fit than physics models. Economists are actually starting to hunker down and work with the actual data, instead of looking for high level immutable laws that simply aren't there.

Importantly, economists are also learning the perils of precisely translating scientific metaphors and language between the sciences- as are many other scientists. Often, a model or metaphor that works spectacularly in one science leads to absolute failure in another. This is because of an idea known as incommensurability. It literally means "no common measure", implying that two different and incompatible measurements are being used to examine an idea. The idea of incommensurability in science was developed by the physicist and philosopher of science, Thomas Kuhn. Different sciences have not only different uses for the same terms, but also mental models and metaphors that completely fail to work in different fields. This is, I think, essential to the proper functioning of science- there is immense diversity in the problems faced by science, so quite a few variants of the scientific method are necessary to tackle them. The mental tools an astrophysicist uses to solve problems are going to be radically different in many ways than the tool an etymologist uses- and yet they're still both recognizably science.

While his development of incommensurability was a valuable contribution to science, Thomas Kuhn had many others as well. The best known of those is probably his theory of paradigm shift, which has been adopted into widespread use outside of philosophy of science. [Image source]

A classic example of the incommensurability of various sciences is in the phenomenon known as "The Unreasonable Ineffectiveness of Mathematics," which refers to the lesser utility of mathematical analysis in the sciences outside of physics. You can basically mathematically analyze absolutely anything in physics. In, say, biology? Mathematically analyzing a bear's daily routine, or the social relationships between dolphins doesn't really make sense. That's not to say math has no role outside physics- that would be absurd. Mathematical models have been extremely effective in ecology, for instance.

A bit of jealousy for physicists is forgivable- they do tend to get a lion's share of the attention the public pays to science. When scientists- hard or social- take that too far, actually trying to make their fields behave like physics does, they're risking some pretty severe methodological failures. Each of the various fields of science has developed their own quite heterogenous methods for very good reasons, and it's best to pay attention to them.

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