Abductive reasoning—the sort formalized by Bayesian inference— is all about finding the best explanation for a set of observations, when these observations are incomplete, uncertain, or otherwise ambiguous. Like inductive reasoning, abductive reasoning can also get things wrong. In seeking the “best explanation,” abductive reasoning can be thought of as reasoning backward, from observed effects to their most likely causes, rather than forward, from causes to their effects—as
