Maxwell’s deduction of the probability distribution over the velocity of gas molecules—”one of the most important passages in physics” (Truesdell)—presents a riddle: a physical discovery of the first importance was made in a single inferential leap without any apparent recourse to empirical evidence.
Tychomancy proposes that Maxwell’s derivation was not made a priori; rather, he inferred his distribution from non-probabilistic facts about the dynamics of intermolecular collisions. Further, the inference is of the same sort as everyday reasoning about the physical probabilities attached to such canonical chance setups as tossed coins or rolled dice. The structure of this reasoning is investigated and some simple rules for inferring physical probabilities from symmetries and other causally relevant properties of physical systems are proposed.
Not only physics but evolutionary biology and population ecology, the science of measurement error, and climate modeling have benefited enormously from the same kind of reasoning, the book goes on to argue. Inferences from dynamics to probability are so “obvious” to us, however, that their methodological importance has been largely overlooked.
Tychomancy: Inferring Probability from Causal Structure by Michael Strevens (a philosophy professor at NYU). From the blurb:
There is also a brief chapter summary here.
Would you recommend it?