[D] Do ML researchers ever treat the user base as part of the model’s effective dimensionality?

Not asking about RLHF or online updates. My question is more structural.

Scaling laws talk about parameters, data, compute, right? But I’ve seriously been wondering whether the interactive boundary (number + diversity of users) effectively increases the system’s dimensionality – in practice – even if the weights stay fixed.

Who studies this? Does anyone? Is there literature on treating the model + its active user ecology, together, as one coupled system?

Genuinely curious if this is a solved question (and I’ve missed it), or if it’s still pretty open (which is how it feels)