If we observe a cause—for example, Bobby throws a ball toward a window—most of us can predict the effect (the ball will probably break the window). Human cognition works in this direction. But given the effect (the window is broken), we need much more information to deduce the cause (which boy threw the ball that broke it or even the fact that it was broken by a ball in the first place). It takes the mind of a Sherlock Holmes to keep track of all the possible causes. Bayes set out to break this cognitive asymmetry and explain how even ordinary humans can assess inverse probabilities.
Ah, such is the difficulty; the massive number of causes that could explain the same observed effects.
