Researchers think that adversarial examples could help us maintain privacy from machine learning systems

Machine learning systems are pretty good at finding hidden correlations in data and using them to infer potentially compromising information about the people who generate that data: for example, researchers fed an ML system a bunch of Google Play reviews by reviewers whose locations were explicitly given in their Google Plus reviews; based on this, the model was able to predict the locations of other Google Play reviewers with about 44% accuracy.

A generalized method for re-identifying people in "anonymized" data-sets

"Anonymized data" is one of those holy grails, like "healthy ice-cream" or "selectively breakable crypto" — if "anonymized data" is a thing, then companies can monetize their surveillance dossiers on us by selling them to all comers, without putting us at risk or putting themselves in legal jeopardy (to say nothing of the benefits to science and research of being able to do large-scale data analyses and then publish them along with the underlying data for peer review without posing a risk to the people in the data-set, AKA "release and forget").

Fitness app releases data-set that reveals the location of sensitive military bases, patrol routes, aircrew flightpaths, and individual soldiers' jogging routes

Strava is a popular fitness route-tracker focused on sharing the maps of your workouts with others; last November, the company released an "anonymized" data-set of over 3 trillion GPS points, and over the weekend, Institute for United Conflict Analysts co-founder Nathan Ruser started a Twitter thread pointing out the sensitive locations and details revealed by the release.

Postcapitalism: A Guide to Our Future

Economist Paul Mason's blockbuster manifesto Postcapitalism suggests that markets just can't organize products whose major input isn't labor or material, but information, and that means that, for the first time in history, it's conceivable that we can have a society based on abundance.