finances, where they bought things, how much they paid for them, where they went on vacation, what they read.
We matched this data to their political information (their voting habits, which were accessible publicly) and then matched all that again to their Facebook data (what topics they had “liked”). From Facebook alone, we had some 570 individual data points on users, and so, combining all this gave us some 5,000 data points on every single American over the age of eighteen—some 240 million people.
The special edge of the database, though, Tayler said, was our access to Facebook for messaging. We used the Facebook platform to reach the same people on whom we had compiled so much data.
What Alex told me helped bring into focus two events I’d experienced while at the SCL Group, the first when I’d just arrived. One day in December 2014, one of our senior data scientists, Suraj Gosai, had called me over to his computer, where he was sitting with one of our research PhDs and one of our in-house psychologists.
The three of them had developed, they explained, a personality quiz called “the Sex Compass”—a funny name, I thought. It was ostensibly aimed at determining a person’s “sexual personality” by asking probing questions about sexual preferences such as favorite position in bed. The survey wasn’t just a joyride for the user. It was, I came to understand, a means to harvest data points from the answers people gave about themselves, which led to the determination of their “sexual personality,” and a new masked way for SCL to gather the users’ data and that of all their “friends,” while topping it up with useful data points on personality and behavior.
The same was true for another survey that had crossed my desk. It was called “the Musical Walrus.” A tiny cartoon walrus asked a user a series of seemingly benign questions in order to determine that person’s “true musical identity.” It, too, was gathering data points and personality information.
And then there were other online activities that, as Tayler explained, were a means to get at both the 570 data points Facebook already possessed about users and the 570 data points possessed about each of the user’s Facebook friends. When people signed on to play games such as Candy Crush on Facebook, and clicked “yes” to the terms of service for that third-party app, they were opting in to give their data and the data of all their friends, for free, to the app developers and then, inadvertently, to everyone with whom that app developer had decided to share the information. Facebook allowed this access through what has become known as the “Friends API,” a now-notorious data portal that contravened data laws everywhere, as under no legislative framework in the United States or elsewhere is it legal for anyone to consent on behalf of other able-minded adults. As one can imagine, the use of the Friends API became prolific, amounting to a great payday for Facebook. And it allowed more than forty thousand developers, including Cambridge Analytica, to take advantage of this loophole and harvest data on unsuspecting Facebook users.
Cambridge was always collecting and refreshing its data, staying completely up to date on what people cared about at any given time. It supplemented data sets by purchasing more and more every day on the American public, data that Americans gave away every time they clicked on “yes” and accepted electronic “cookies” or clicked “agree” to “terms of service” on any site, not just Facebook or third-party apps.
Cambridge Analytica bought this fresh data from companies such as Experian, which has followed people throughout their digital lives, through every move and every purchase, collecting as much as possible in order, ostensibly, to provide credit scores but also to make a profit in selling that information. Other data brokers, such as Axiom, Magellan, and Labels and Lists (aka L2), did the same. Users do not need to opt in, a process by which they agree to the data collection, usually through extensive terms and conditions meant to put them off reading them—so with an attractively easy, small tick box, collecting data is an even simpler process for these companies. Users are forced to click it anyhow, or they cannot go forth with using whichever game, platform, or service they are trying to activate.
The most shocking thing about data that I learned from Alexander Tayler was where it all came from. I hate to break it to you, but by buying this book (perhaps even by reading it, if you have downloaded the e-book or Audible version), you have produced significant data sets about yourself that have already been bought and sold around the world in order for advertisers to control your digital life.
If you bought this book online, your search data, transaction history, and the time spent browsing each Web page during your purchase were recorded by the platforms you used and the tracking cookies you allowed to drop on your computer, installing a tracking device to collect your online data.
Speaking of cookies, have you ever wondered what Web pages are asking when they request that you “accept cookies”? It’s supposed to be a socially acceptable version of spyware, and you consent to it on a daily basis. It comes to you wrapped in a friendly-sounding word, but it is an elaborate ruse used on unsuspecting citizens and consumers.
Cookies literally track everything you do on your computer or phone. Go ahead and check any browsing add-on such as Mozilla’s Lightbeam (formerly Collusion), Cliqz International’s Ghostery, or the Electronic Frontier Foundation’s Privacy Badger to see how many companies are tracking your online activity. You could find more than fifty. When I first used Lightbeam to see just how many companies were tracking me, I found that by having visited merely two news Web pages within one minute, I had allowed my data to be connected to 174 third-party sites. These sites sell data to even larger “Big Data aggregators” such as Rocket Fuel and Lotame, where your data is the gas that keeps their ad machines running. Everyone who touches your data along the way makes a profit.
If you are reading this book on your Amazon Kindle, on your iPad, in Google Books, or on your Barnes and Noble Nook, you are producing precise data sets that range from how long you took to read each page, at which points you stopped reading and took a break, and which passages you bookmarked or highlighted. Combined with the actual search terms you used to find this book in the first place, this information gives the companies that own the device the data they need to sell you new products. These retailers want you to engage, and even the slightest hint of what you might be interested in is enough to give them an edge. And all this goes on without your being properly informed or consenting to the process in any traditional sense of the term consent.
Now, if you bought this book in a brick-and-mortar store, and assuming you have a smartphone with GPS tracking switched on—when you use Google Maps, it creates valuable location data that is sold to companies such as NinthDecimal—your phone recorded your entire journey to the bookshop and, upon your arrival, tracked how long you spent there, how long you looked at each item, and even perhaps what the items were, before you chose this book over others. Upon buying the book, if you used a credit or debit card, your purchase was recorded in your transaction history. From there, your bank or credit card company sold that information to Big Data aggregators and vendors, who went on to sell it as soon as they could.
Now, if you’re back home reading this, your robot vacuum cleaner, if you have one, is recording the location of the chair or couch on which you’re sitting. If you have an Alexa, Siri, Cortana, or other voice-activated “assistant” nearby, it records when you laugh out loud or cry while reading the revelations on these pages. You may even have a smart fridge or coffeemaker that records how much coffee and milk you go through while reading.
All these data sets are known as “behavioral data,” and with this data, it is possible for data aggregators to build a picture of you that is incredibly precise and endlessly useful. Companies can then tailor their products to align with your daily activities. Politicians use your behavioral data to show you information so that their message will ring true to you, and at the right time: Think of those ads about education that just happen to play on the radio at the precise moment you’re dropping your kids off at school. You’re not paranoid. It’s
