Studying asymptotics, I bumped into the concept of Observed Fisher Information, as a way to compute Fisher Information when the parameter $\theta$ is unknown. I am also aware that it is related in some ways to Maximum Likelihood Estimators but I am a bit confused.
Thus my questions are: Which is the difference between Expected and Observed Fisher Information? How the observed Fisher information is computed? And how it is used?
EDIT: From the linked pages, I have understood how the Observed Fisher Information is computed and how it may be better than the Expected one in cases of finite samples. But I have some doubts yet: is the only difference between Observed and Expected Information the presence of an estimate (possibly the MLE of $\theta$) or a known $\theta$ ? Thus, should it be used, for example, in the case of asymptotic estimations?