Sociologists discuss sociological methods, physicists discuss physics

The title of this piece is a quote attributed to the great french physicist and philosopher of science, Henri Poincare. To further learn about his perspective on the discipline here is another quote of his :

Nearly every sociological thesis proposes a new method, which, however, its author is very careful not to apply, so that sociology is the science with the greatest number of methods and the least results.

Poincare lived from 1854 to 1912, but in my opinion his quote is still true today. We have been studying social sciences since Ibn Khaldun, or perhaps even before that, yet we have failed to replicate the successes of the natural sciences in these fields. In fact, there is no real consensus as to how the social sciences should be approached methodologically.

What is more, it seems like laypeople know this intuitively and demarcate between “soft” and “hard” sciences. But what is the reason for this cleavage ? What are the inherent differences between the two domains of inquiry that can explain their differences in success ? I will proceed to lay in writing my intuitions about these questions.

The butterfly effect

Everyone has heard about the butterfly effect, that “a butterfly batting its wings in India can cause a tornado in Texas”.

This metaphor illustrates the idea than in certain systems, called dynamical systems, minuscule changes in conditions can lead to massively different outcomes.

Human society is one of those systems. And this is the simple, yet fundamental reason, that predictions about the future state of society, especially in the long term, are impossible.

Black swan events, like the 2008 financial crash or the 2011 Fukushima disaster, are a manifestation of the butterfly effect. They are the tornado that we couldn’t predict because we did not pay attention to the butterfly.

“But what if we did pay attention to the butterfly ?” you might ask. We can’t. Everything in our modern world is interconnected and there would be way more information to take into account to perfectly predict such complex systems than even the world’s most powerful supercomputers could handle.

But it is not only that some historical events are fundamentally unpredictable, it is that history itself is defined by a succession of these black swan events.

In the book The poverty of historicism, Karl Popper makes the following argument :

  1. Technological innovation can completely transform society.
  2. If we knew with precision what technologies we would have in the future we would start building them in the present.
  3. From 2. follows that we cannot know exactly what technologies we will have in the future.
  4. From 1. and 3. follows that we cannot know the future state of society.

This argument is, in a sense, a black swan argument. Small technological innovations can transform the world so much that it becomes unrecognizable. They are rare events with potentially humongous consequences, the definition of a black swan.

And although this is true of the technological innovation, these are not the only type of events that can radically change the face of human society. The extinction of a species of fish, changes in climate, the assassination of a a world leader, these are all events that could make the world of our grandchildren seem foreign to us.

I have to concede that it is not only the social sciences that study complex and dynamical systems, the earth’s climate is one and is being studied by “hard” science professionals. But there is an additional property of social systems that makes them even more difficult to study, that we will proceed to look into.

The Oedipus effect

In his short book The poverty of Historicism Karl Popper gives a name to predictions that influence the system they are trying to predict, the Oedipus effect.

Imagine you are an eminent political scientist and you predict there is going to be a war. World leaders react to your prediction and take the necessary measures to prevent the war. That means your prediction turned out wrong, but what would have happened if you said nothing ? It is impossible to know since we don’t have access to counterfactual worlds.

This phenomenon is ubiquitous is social life and I don’t think we have a real answer as to how to deal with it. An other example could be found in econometrics.

Economist Robert Lucas voiced a critique of the field of macro-econometrics, which lies on the Oedipus effect, in his 1976 paper. He summarizes it as follows :

Given that the structure of an econometric model consists of optimal decision rules of economic agents, and that optimal decision rules vary systematically with changes in the structure of series relevant to the decision maker, it follows that any change in policy will systematically alter the structure of econometric models.

Essentially, you predict an economic problem X is going to happen. You take action. X doesn’t happen. Was your prediction good or bad ?

Systems, like society, which react to the predictions we make about them are called second order chaotic systems or level two chaotic systems.

Large social systems tend to be second order chaotic systems. This is in contrast with a lot of studies phenomena in the natural sciences, your prediction about the trajectory of a ball you throw will not influence it.

The fact that many phenomena in the natural sciences are not affected by the Oedipus effect makes them predictable and possible to engineer. Nonetheless, hard sciences do experience something similar to the Oedipus effect.

Many sub-fields of physics such as electronics, thermodynamics or quantum mechanics experience what are called observer effects. This means the very fact that you are observing a phenomenon can disturb it. The observer effect is slightly different than the Oedipus effect in the strict sense, insofar as it is not the predictions that you make that influence the phenomenon but the fact that you are observing it. Although observer effects can be problematic, I do not believe they are as problematic as strict sense Oedipus effect.

The fundamental difference that I want to underline is that when we study society, we study a system that we are part of. The predictions you make about the system are also part of the system and influence it. The inability to have an outside view of such a complicated system makes it all the more difficult to apprehend and predict.

Can we replicate the success of the natural sciences in the social sciences ?

Perhaps the reason sociologists discuss sociological methods and not sociology itself is because most methods fail to make sociology understandable to us. We don’t know what methods to use to predict dynamical and second order chaotic systems.

There is a field of inquiry which specializes in studying not instances of complex systems, but complexity itself. Complexity theorists try to use the latest technologies and algorithms, such as deep learning algorithms, to try and look inside the black box of complexity.

My personal view is that, if we want to make important strides in the inquiry of social phenomena, we first have to advance the study of complexity itself.

Specialized research centers such as the Sante Fe institue or the New England Complex Systems Institute are trying to achieve just that. We can only hope that they will have important breakthrough to share with us in the future.

But to answer the initial question of whether I think social sciences can be as successful as the hard sciences, my answer is no.

One reason is, as I’ve said a previous article, although I have faith we will better understand complexity in the future, some systems are just to complex to understand. And that also holds true for many social systems.

The second reason is, even if we perfectly understood how society functions, social engineering would still be problematic and undesirable. Indeed, even if we understand what is true of the world, that tells us nothing about what we should do in the world. Epistemic knowledge does not translate into ethics.

Even if we reached that perfect understanding, we would probably still disagree on ethical matters, which would make molding a perfect society impossible still, since perfect means something different to each and every one of us.

I have the intuition that sciences are often judged by what they bring to engineering and technology. And in the case the the social sciences, I have made the argument that even if we understood them perfectly, social engineering would still fail.

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