But the additional observers exactly cancel the extra data needed to identify a specific one, no?

That would be true in an SIA approach (probability of a hypothesis is scaled upwards in proportion to number of observers). It's not true in an SSA approach (there is no upscaling to counter the additional complexity penalty of locating an observer out of N observers). This is why SSA tends to favour small N (or small M for a specific reference class).