That would make sense. I assume the problem is lotus eating - the system, given the choice between a large cost to optimize whatever you care about, or small cost to just optimize its own sense experiences, will prefer the latter.

I find this stuff extremely interesting. I mean, when we talk about value modelling what we're really talking about isolating some subset of the causal mechanics driving human behavior (our values) from those elements we don't consider valuable. And, since we don't know if that subset is a natural category (or how to define it if it is), we've got a choice of how much we want to remove. Asking people to make a list of their values would be an example of the extreme sparse end of the spectrum, where we almost certainly don't model as much as we want to, and we know the features we're missing are important. On the other extreme end, we're just naively modelling the behaviors of humans, and letting the models vote. Which definitely captures all of our values, but also captures a bunch of extraneous stuff that we don't really want our system optimizing for. The target you're trying to hit is somewhere in the middle. It seems to me that it's probably best to err on the side of including too much than too little, since, if we get close enough, the optimizer will likely remove a certain amount of cruft on its own.