To my understanding, $P(A|B)$ is the probability of A given that B has already occur (or we know will occur): $P(A|B) = P(A \cap B) / P(B)$
What confuses me a lot is how to update the probability of A given that I know the value of $P(A|B)$ and also that B might occur with a probability $P_B$ but has not happened yet.
For example:
Let's say Bob enters a store to pick a movie. Initially, the chances of Bob choosing a movie are $\{\beta_1,...\beta_n\}$ for the all the $\{m_1,...m_n\}$ movies in the store. Then, he see his friend Anne also choosing a movie. Since Bob wants to see a movie with Anne, the chances that Bob accepts to see the move Anne chooses are known to be higher ($P(A_m|B_m)$ isn't?). However if Anne chooses a very bad movie, Bob will still take a different one. The chances of Anne choosing a movie from the store are $\{\alpha_1,...\alpha_n\}$ for the all the $\{m_1,...m_n\}$ movies in the store.
The question is what are the chances of Bob picking a given movie $m$ after seeing Anne but before knowing which movie Anne will choose?