Most AI models are not even known about, accessible outside the system they are part of, let alone targeted for audits at all.
Unless you got enough volume of volunteer users to try and make some correlations, but then, those can still be argued not to be causation.
In theory it’s easier/possible with some types of models, harder/impossible with others, but only if the model and the data processing around it is disclosed.
The bigger issue here is that some seemingly unrelated factors and their combinations (postal code, time being active during the day, even the vocabulary used in social communication) could be predictive for the user’s economic status.
Is this strictly true? Couldn't we can audit the model's parameters for things analogous to the user's economic status?