Wrighton: Elementary Principles of Probability and Information (1973)

This is a strange little book. It is essentially an introduction to information theory, but with a bunch of digressions into all sorts of philosophical and methodological issues. It's not always completely clear to me where Wrighton is going with his arguments, but some of them are quite thought-provoking.

The Reshuffled Hierarchy of Science

The book begins with a discussion of what probability is, using the philosophy of Giambattista Vico as a starting point.

A core claim of Vico's philosophy is, according to Wrighton, that the sciences should not be sorted on a scale with mathematics and theoretical physics in one end, and social and human science in the other. Rather, one should categorize them according to the artificiality of their objects:

Mathematics retains a special position, since in mathematics Man creates the object of his study, which therefore he wholly understands. Likewise, Man may hope to acquire an understanding of comparable depth within the humanities; for he has created his own history, his own language and his own social environment. The Natural Sciences suffer a demotion, relative to the ideal of certainty, and revert to the status which Bacon accorded them; experiment and observation provide, and must always provide the true foundation of physics, since, as Vico puts it, Man can never wholly understand what God has created; physical theory primarily reflects, or epitomises, man's increasing control over his physical environment, rather than an independent reality. (p. 3)

A crude way of putting the same point would be that math is a human science. Whatever is conceptual, mental, or cultural falls on one end of of the scale, and the study of natural phenomena falls on the other.

Probability as Deliberately Created Uncertainty

Once we have reshuffled the sciences like this, we have to decide whether we categorize probability theory as a study of "Man's creation" or of "God's creation." Here, Wrighton squarely comes down on the side of the first team:

It is sometimes said to be a mere empirical fact that when a coin is tossed it comes down heads with probability one half; and that a suitably-devised machine could toss coins so that they came down heads every time. The suggestion is based on a total misconception. A coin comes down heads with probability on half because we arrange that it should do so: the empirically-verifiable consequences cannot be other than they are. If an operator, within the terms of our instructions to him, were to train himself to toss a coin so that it always came down heads, we should have to regard our instructions as misconceived, and would either have to raise the minimum angular momentum assigned or supply him with a smaller or lighter coin: it is a matter of making the task implicitly assigned to the operator sufficiently difficult. Thus we cannot think of a random event without somehow involving a human being in its generation. (p. 3; his emphasis)

So "real" probability is "artificial" probability; a random experiment is an experiment that allows us to say that something went wrong if it is predictable. Only metaphorically can we transfer this artificially created complexity to natural systems.

Points of Contact

I find this idea interesting for two reasons:

First, it turns information theory upside-down so that system complexity becomes more fundamental than probability. This is an interesting idea also championed by Edwin Jaynes, and which I have been exposed to through Flemming Topsøe.

And second, it relates the philosophical problems of probability theory to the thorny issues surrounding the notions of repetition, identity, rule-following, and induction. It is probability fair to say that one can't solve any of these problems without solving the others as well.