I guess the question is what are you trying to protect? The model is fundamentally lossy as it is a rank reduction method so your original data is gone (i.e. no

I guess the question is what are you trying to protect? The model is fundamentally lossy as it is a rank reduction method so your original data is gone (i.e. no one would be able to accuse you of liking a particular controversial post, just that you are likely to like that post). So it sort of has the differential privacy thing going on. I guess it is another question as to if such models should be built at all. I think the fidelity of the models will answer that in time, if they work really well it is scary, if they are poor models they will cease to be used. I suspect that it will be in the middle and highly sensitive to the quality of the original data and the quality of the implementation like all ml applications.