And for the semantic problem, [systems theorist Howard Pattee] adds, “[T]he concepts of causation have completely different meanings in statistical or deterministic models,” and gives the following example: If you were to ask “What is the cause of temperature?” a determinist will assume that cause refers to a microscopic event and say it is caused by the molecules exchanging their kinetic energy by collisions. But the skeptical observer, scratching his head, will note that the measuring device averages this exchange, and does not measure the initial conditions of all the molecules and that averaging, my dear sir (or madam), is a statistical process. An average cannot be observable in a microscopic, determinist model. We have a case of apples and oranges. Pattee wags his finger at those who champion one model over the other and instead champions the idea that they are both needed and are complementary to each other. “I am using complementary here in Boltzmann’s and Bohr’s sense of logical irreducibility. That is, complementary models are formally incompatible but both necessary. One model cannot be derived from, or reduced to, the other. Chance cannot be derived from necessity, nor necessity from chance, but both concepts are necessary… . It is for this reason that our concept of a deterministic cause is different from our concept of a statistical cause. Determinism and chance arise from two formally complementary models of the world. We should also not waste time arguing whether the world itself is deterministic or stochastic since this is a metaphysical question that is not empirically decidable.
— Gazzaniga, Michael S. Who’s in Charge?: Free Will and the Science of the Brain. New York: Ecco, 2011. (via carvalhais)