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by striking 4224 days ago
To me, it's not even the use of data per se that is most creepy about this post. Really, the tone of the essay seems to revel in "having 'fun' with user data," as if a sophomore at a university wrote it.

I mean, I found the idea behind the post interesting: of course you can analyze trends in ridership to draw interesting conclusions. At the end of the day, however, it's a horrible idea to say "Hey, we know which of you are being 'frisky' and where!"

Perhaps with a different motivation, this post wouldn't be nearly as ruinous. How about ridership patterns of sick or socioeconomically disadvantaged people? That's the kind of data that can change lives for the better.

4 comments

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.
Agreed, it's all about the vibe. The writer feels like that uncle that conspicuously left openings for you to talk about your 18 year old love life in every conversation. And who was just a bit too enthusiastic the time you dated a cheerleader for a few months.
ridership patterns of sick or socioeconomically disadvantaged people

You mean the sort of people who take the bus, who are pretty much the opposite of their target customers?

The author is Bradley Voytek (http://darb.ketyov.com), who is now a professor of neuroscience and should probably know better.
He acknowledges the questionable nature of his blog posts on his website:

> Between June 2011 and August 2011 I worked with my friends over at Uber as their data scientist, writing (what I thought were) amusing, data-driven blog posts (among other, more serious roles).

I've found a pretty high prevalence of stunted maturity in academia, so it's none too surprising.