Corporations and governments are using information about us in a new—and newly insidious—way. Employing massive data files, much of the information taken from the Internet, they profile us, predict our good or bad character, credit worthiness, behavior, tastes, and spending habits—and take actions accordingly.
As a result, millions of Americans are now virtually incarcerated in algorithmic prisons.
Some can no longer get loans or cash checks. Others are being offered only usurious credit-card interest rates. Many have trouble finding employment because of their Internet profiles. Others may have trouble purchasing property, life, and automobile insurance because of algorithmic predictions. Algorithms may select some people for government audits, while leaving others to find themselves undergoing gratuitous and degrading airport screening.
An estimated 500 Americans have their names on no-fly lists. Thousands more are targeted for enhanced screening by the Automated Targeting System algorithm used by the Transportation Security Administration. By using data including "tax identification number, past travel itineraries, property records, physical characteristics, and law enforcement or intelligence information" the algorithm is expected to predict how likely a passenger is to be dangerous.
Algorithms also constrain our lives in virtual space. They determine what products we will be exposed to. They analyze our interests and play an active role in selecting the things we see when we go to a particular website..
Eli Pariser, argues in The Filter Bubble, "You click on a link, which signals your interest in something, which means you are more likely to see articles about that topic" and then "you become trapped in a loop." The danger being that you emerge with a very distorted view of the world.
If you’re having trouble finding a job as a software engineer, it may be because you got a low score from the Gild, a company that predicts the skill of programmers by evaluating the open source code they have written, the language they use on LinkedIn, and how they answer questions on software social forums
Algorithmic prisons are not new. Even before the Internet, credit reporting and rating agencies were a power in our economy. Fitch’s, Moody’s, and Standard & Poor’s have been rating business credit for decades. Equifax, the oldest credit rating agency, was founded in 1899.
When algorithms get it right (and in general they do a pretty good job), they provide extremely valuable services to the economy. They make our lives safer. They make it easier to find the products and services we want. Amazon constantly alerts me to books it correctly predicts I will want to read. They increase the efficiency of businesses.
But when algorithms get it wrong, real suffering follows.
Most of us would not be concerned if 10 or 100 times too many people ended up on the TSA’s enhanced airport screening list as long as an airplane hijacking was avoided. In times when jobs are scarce and applicants many, most employers would opt for tighter algorithmic screening. There are lots of candidates to hire and more harm may be done by hiring a bad apple than by missing a potentially good new employee. And avoiding bad loans is key to the success of banks. Missing out on a few good ones in return for avoiding a big loss is a decent trade off.
But we’ve reached the point where, in many cases, private companies and public institutions stand to gain more than they will lose if a lot of innocent people end up in algorithmic prison.
A related concern is this: Surveillance has become automated through the use of Internet tools, capturing data from cellular phones, low cost cameras, and the ability to economically analyze big databases. As a result, it has become much easier—and a lot less costly—to construct algorithmic prisons. Not only can we expect to see a great increase in the number of algorithmic prisons, but thanks to cheaper and more efficient tools the value derived from establishing them will increase.