In the time I’ve been away, Congress has repealed protections that would have blocked internet providers like AT&T, Comcast, and Verizon from sharing browsing data with other companies. It’s unlikely that these legislative changes will have a significant effect on the relationship between data brokers and internet-service providers, but they do bring concerns about privacy to the fore, even more than usual. And when the news first broke, it caused a lot of confusion about just how much data companies will one day be able to collect and just how far people need go to protect themselves.
It all sounded scary enough that I wondered what would come up if I bought data about myself from a data broker. With a quick Google search, I found a company that promised to detail net worth, age, zip code, and education, among other personal information. All I had to do was upload a text file of the email addresses of people whose info I wanted (in this case, just my own) and pay a $50 fee. The whole endeavor gave me pause. It seemed like I was about to do something that violated the company’s lengthy terms of service. Then there was the queasiness about the data itself: Did I really want to know?
The report arrived in my inbox a matter of hours later with an accompanied missive trumpeting, “Wow! That was easy.” Yes. I never had to talk to a customer service representative nor identify myself. It was just like any other transaction. My misgivings gave way to glee. A strong Christmas morning vibe overtook me. Would I find something I didn’t know? There was a part of me that genuinely believed the internet knew me best: Maybe I’d discover a pattern in my life that could point toward the future—a palm reading constructed from metadata.
In the zip file, I found a PDF, a spreadsheet, and a .txt file. I chose the spreadsheet first, and this was the first of many letdowns. It was merely a summary of how many of the email addresses had provided “matches” for the various information categories. I tried again with the charts, which aren’t visually interesting when they each feature one piece of data about a single subject. The pie chart, for example, was just an uninterrupted blue circle labeled “Female 100.0%.” I got a sense I had wasted my money. Finally, I opened the.txt file, and as though I had time traveled back to the advent of personal computing, a document I was reading in Notepad was the most useful of the three: It included each data point, organized email address by email address. But much of the data was flat-out wrong.
If you like percentages, nearly 50 percent of the data in the report about me was incorrect. Even the zip code listed does not match that of my permanent address in the U.S.; it shows instead the zip code of an apartment where I lived several years ago. Many data points were so out of date as to be useless for marketing—or nefarious—purposes: My occupation is listed as “student”; my net worth does not take into account my really rather impressive student loan debt. And the information that is accurate, including my age and aforementioned net worth (when adjusted for the student debt), is presented in wide ranges.