Outer loss transmits very limited bits of information through the info-theoretic bottleneck of the training process... so yes, if your function family (eg wetware brains) priors mesa-optimizers relatively densely, no sparsely delivered outer loss (death in the EEA) suffices...
"Train it to be nice" is the obvious thought. Alas, I predict that one idiom that does generalize from natural selection to gradient descent, is that training on an outer loss gets you something not internally aligned to that outer loss. It gets you ice cream and condoms.