Really good point csande17 but I'd be nervous to tar all ML folk with the same brush :) I know some incredible data science and ML folks who care deeply about privacy - check out http://openmined.org to see hope in the ML community. There are large numbers of talented engineers who are dedicated to building better data processing systems.

If I can offer my two cents: if we do better at annotating data at source of ingress (whether that's data provided by users, inferred about them, etc.) such that we can better describe the data we hold, why we have that dataset and for what limited uses, we can then enforce those conditions on models - right now that additional context just doesn't exist so privacy type enforcement on ML becomes arbitrary and subjective based on a teams needs. We can do so much better if just describe what, where, how and why we've collected data in our systems - then enforcement is layered on top of that.