NYC taxi ride data suggest cozy relationship between big banks and the Fed. Here's the research paper. And the abstract reads like poetry:
In this paper, I employ anonymous New York City yellow taxi records to infer variation in interactions between insiders of the Federal Reserve Bank of New York (New York Fed) and insiders of major commercial banks around Federal Open Market Committee (FOMC) meetings. Taxi rides between the vicinities of the New York Fed’s and the major commercial banks’ buildings serve as indicators of meetings at those institutions, and coincidental drop-offs of passengers picked up around those institutions serve as indicators of offsite meetings. Cieślak, Morse and Vissing-Jørgensen (2016) posit systematic leakage from the Federal Reserve around FOMC meetings along unofficial channels, and, in line with that hypothesis, I find highly statistically significant evidence of increases in meetings at the New York Fed late at night and in offsite meetings during typical lunch hours.
Let's begin this with a brief section on Cambridge Analytica & co. I finally manage to gather some links that I think make a respectable job of summarizing the entire thing in a proper way.
Conversely, if this psychographics business is so effective, why isn’t it commonly used by smart e-commerce players like Amazon, or anyone else beyond the brand advertisers who like keeping old marketing folklore alive?
One of the ironies of this most recent Facebook brouhaha is the differing reactions between the digital marketing professionals who’ve spent a career turning money into advertising pixels and a concerned public otherwise innocent to the realities of digital advertising. Most ad insiders express skepticism about Cambridge Analytica’s claims of having influenced the election, and stress the real-world difficulty of changing anyone’s mind about anything with mere Facebook ads, least of all deeply ingrained political views.
The public, with no small help from the media sniffing a great story, is ready to believe in the supernatural powers of a mostly unproven targeting strategy. What they don’t realize is what every ads practitioner, including no doubt Cambridge Analytica itself, knows subconsciously: in the ads world, just because a product doesn’t work doesn’t mean you can’t sell it. Before this most recent leak, and its subsquent ban on Facebook, Cambridge Analytica was quite happy to sell its purported skills, no matter how dubious they might really be.
The problem here goes beyond Cambridge Analytica and what it may have done. What other apps were allowed to siphon data from millions of Facebook users? What if one day Facebook decides to suspend from its site a presidential campaign or a politician whose platform calls for things like increased data privacy for individuals and limits on data retention and use? What if it decides to share data with one political campaign and not another? What if it gives better ad rates to candidates who align with its own interests?
A business model based on vast data surveillance and charging clients to opaquely target users based on this kind of extensive profiling will inevitably be misused. The real problem is that billions of dollars are being made at the expense of the health of our public sphere and our politics, and crucial decisions are being made unilaterally, and without recourse or accountability.
Facebook and Cambridge Analytica. Schneier doesn't comment on the alleged effectiveness of the Cambridge Analytica systems, but makes a point that as of now everybody should have in mind:
Surveillance capitalism drives much of the internet. It's behind most of the "free" services, and many of the paid ones as well. Its goal is psychological manipulation, in the form of personalized advertising to persuade you to buy something or do something, like vote for a candidate. And while the individualized profile-driven manipulation exposed by Cambridge Analytica feels abhorrent, it's really no different from what every company wants in the end. This is why all your personal information is collected, and this is why it is so valuable. Companies that can understand it can use it against you.
It's not only that you are the product, as gurus past their expiration date like to claim. You're unpaid labor too.
This is how Cambridge Analytica’s Facebook targeting model really worked — according to the person who built it. This is one of the few articles, apart from the one opening this section, that really stops and takes a look at the model that was built. It's not different from what thousands of companies are doing right now. But psychographics sound scary.
The other elephant in the room. What Are 'Data Brokers,' and Why Are They Scooping Up Information About You?.
Data brokers are entities that collect information about consumers, and then sell that data (or analytic scores, or classifications made based on that data) to other data brokers, companies, and/or individuals. These data brokers do not have a direct relationship with the people they're collecting data on, so most people aren't even aware that the data is even being collected.
Emblematic of this unprecedented surveillance apparatus are the facial recognition devices deployed in Shenzhen last April that are meant to deter jaywalkers. These devices take photos of offenders and display them on large LED screens above the intersection, along with their name and part of their government ID number. (There is also a website showing photos and information for jaywalkers in Shenzhen.)
In the hopes of deterring violence, schools are turning to big data analytics to examine social media posts for the earliest signs of violence—depression, resentment, and isolation. Shawsheen Valley Technical High School in Massachusetts has turned to Social Sentinel, a data analytics company that says it can use the type of threat detection police agencies use to identify students at risk. But experts worry student social media mining, even with the best intentions, is a slippery slope to treating students the way we treat suspects.
- If you ever wondered how Spotify shared its revenue with artists, here you have a very nice visualization.
Data Links is a periodic blog post published on Sundays (specific time may vary) which contains interesting links about data science, machine learning and related topics. You can subscribe to it using the general blog RSS feed or this one, which only contains these articles, if you are not interested in other things I might publish.
Have you read an article you liked and would you like to suggest it for the next issue? Just contact me!