I also agree that attribution can't be solved easily in the current paradigm. Perhaps, during training, one could deduce how much of the net gradient on a particular weight was derived from the batches covering some book, and then during inference, assign attribution based on the effect of that weight on the output. All of this is very expensive to do, and I don't have strong intuitions for whether the resulting attributions would be in any way meaningful.
To your point about hallucinations, if there's not a solution to that, then perhaps the whole point is moot when, after a while, the hype dies down. But if somehow hallucinations are solved (I don't see a technical way this can happen now, but who knows?), then I think we'll need to address attribution for non-technical material.