In Human Action and elsewhere, Mises emphasizes the difference between the natural and social sciences by pointing out that there are no constants in the latter. He means that there are no natural laws in social science equivalent to the law of gravity, or the constant speed of light. Human beings are not automata. Thus, our understanding of human action comes not from the empirical observation of constant relationships between the elements of the social system (the human actors), but rather from our “understanding” of their motives and the logic of action itself in terms of means and ends, categories that have no meaning or application in the natural sciences.
One might be tempted to conclude that the absence of such categories, as intention, or means and ends, is sufficient to render the subject matter equivalent to the natural sciences with its constant relationships, its natural laws – that if human beings were automata simple prediction would be possible. But, of course, as Hayek pointed out, natural systems displaying such natural law regularities, that enable precise quantitative prediction, are, most probably, in the minority in the natural world. Biological, chemical, astronomical and cybernetic systems for example, are "complex phenomena" for which prediction of a quantitative kind is impossible. A striking example is the work of Stephen Wolfram on systems of automata. Wolfram shows how some very simple systems of interacting automata produce complex outcomes that are not predictable. In fact, this suggests that, in one sense, Mises’s claim implies the opposite. If human beings were automata (given that human societies are characterized by huge numbers of multi-level interactions) we would be at a total loss to predict likely outcomes. It is because they are not automata that we have more knowledge than we otherwise would – through understanding the logic of human action and armed with empathizing insights into the motives of our subjects. It is an understanding of the incentivized behavior of human beings that allows us to understand and predict invisible-hand outcomes.
Yet, the complexity problem remains. Can we be certain, as a logical matter, that if certain conditions obtain, certain definite types of outcomes will result from the free market process? It is on this type of thinking that the more sophisticated Keynesians might base their arguments for benevolent and effective intervention in the face of economic crisis. And this is the subject of my next blog.