 Vaidman 1998 introduced the ignorance probability of an agent in the framework of the MWI in a situation of post-measurement uncertainty, see also Tappenden 2011, Vaidman 2012, Tipler 2014, 2019b, Schwarz 2015. It seems senseless to ask: “What is the probability that Lev in the world \(A\) will observe \(A\)?” This probability is trivially equal to 1. The task is to define the probability in such a way that we could reconstruct the prediction of the standard approach, where the probability for \(A\) is 1/3. It is indeed senseless to ask you what is the probability that Lev in the world \(A\) will observe \(A\), but this might be a meaningful question when addressed to Lev in the world of the outcome \(A\). Under normal circumstances, the world \(A\) is created (i.e. measuring devices and objects which interact with measuring devices become localized according to the outcome \(A)\) before Lev is aware of the result \(A\). Then, it is sensible to ask this Lev about his probability of being in world \(A\). There is a definite outcome which this Lev will see, but he is ignorant of this outcome at the time of the question. In order to make this point vivid, Vaidman 1998 proposed an experiment in which the experimenter is given a sleeping pill before the experiment. Then, while asleep, he is moved to room \(A\) or to room \(B\) depending on the results of the experiment. When the experimenter has woken up (in one of the rooms), but before he has opened his eyes, he is asked “In which room are you?” Certainly, there is a matter of fact about which room he is in (he can learn about it by opening his eyes), but he is ignorant about this fact at the time of the question.