Since I know author (he had the desk next to me in the lab) I feel I should add something here. Let me just say that he was someone who had recently finished his PhD and was taking a summer data science sabbatical with Uber. I know that they were also working on how to optimize the distribution of cars to best serve a market but that would be pretty boring to talk about. I think what you are seeing in "having fun" with the data is actually more of the neuroscientist/psychologist coming out in him combined with his propensity for making science topics interesting and maybe a little sensational. This is the guy who also brought us zombie neuroscience remember (check it out if you aren't familiar). At best we are daily trying to infer subjects internal processing/motivations from the sorts of actual behavioral measures we collect in the lab. This is one where behavioral inferences are perhaps better than self-report. As to your other point, I can even see how knowing how many people are being frisky and where they live being used to improve public health policy although that was obviously not the point (and it being kept anon of course). But let's not forget that a cohort of uber riders is not a very uniform sample of the population and you are going to be somewhat limited in your ability to use it as a tool for social justice. He did a similar analysis although more in line with our lab work where he combined a big brain training app's anon user data with their state geography and its demographics to draw some interesting conclusions that you wouldn't have expected. These are just the application of techniques that we use in the lab to make inferences about brain activity and unravel its complexity and weave an understandable story. I am certainly not trying to defend Uber's other data privacy issues which are in the news and very concerning but I don't think this is one of them. I hope this helps a little knowing more of the backstory.
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