Applying the BIC in practice is far from straightforward and fraught with difficulties because it requires the regularization of space-time infinities by implementing some cosmic “measure.” Furthermore, a suitable physical quantity must be chosen as proxy for the number of reference class observers in some given space-time region. Unfortunately, the choices made in this procedure are prone to being exploited – often unintentionally – by the researchers as so-called researcher degrees of freedom (a term from the social science literature) to yield those results that would best conform to their theoretical preferences. In the light of this difficulty, the prospects for obtaining compelling evidence in favor of any specific multiverse theory by testing whether our observations are those that typical multiverse inhabitants would make do look bad. As it turns out, the multiverse theories that have the best chances of being successfully tested empirically are those that do not behave as typical multiverse theories in important respects – i.e., those multiverse theories according to which all universes in the multiverse are similar or identical in a significant number of ways.

This chapter turns to the prospects for empirically testing specific cosmological multiverse theories such as the landscape multiverse scenario or cyclic multiverse models. The most commonly pursued strategy to extract concrete empirical consequences from specific multiverse theories is to regard them as predicting what typical multiverse inhabitants observe if the theories are correct, where "“typical” is spelled out as “randomly selected from some suitably chosen reference class.” I scrutinize a proposal by Srednicki and Hartle to treat the self-sampling assumption and the reference class to which it is applied as matters of empirical fact that are themselves amenable to empirical tests. Unfortunately, this proposal turns out to be incoherent. A much better idea, which coheres well with the intuitive motivation for the self-sampling assumption, is that we should make this assumption with respect to some reference class of observers precisely if our background information is consistent with us being any of those observers and neutral between them. I call this principle the “background information constraint” (BIC) and point out that it at least formally solves the problem of selecting the appropriate observer reference class.