You’ve heard the A-word. Maybe you first learned what an algorithm was in math class, but no doubt by now you’ve noticed since then that its usage has exploded into the world of tech and big data. Unless you have been holed up in some doomsday shelter or traversing the Gobi desert or something, you’ve heard that this kind of computer process has been providing some pretty incredible new insights into consumer patterns, politics, social media, and much more.
What Does This Nerdy Stuff Really Mean?
Algorithms are guiding our social media feeds. It’s not a coincidence that after spending an hour looking at navy-blue dress shirts, H&M will appear plastered all over your Facebook feed. Math is delivering the advertising we see. It might seem like a small detail, but in this way, algorithms inevitably influence human life.
It’s Not All Fun and Games
If you ever had to suffer through calculus you know that math is not always pleasant. Using these algorithms can have terrible consequences. For example, let’s look at university admissions. You might think that decisions about hiring and admissions would be much fairer if based on objective, computer-processed calculations rather than someone’s gut feeling.
After all, these algorithms judge everyone on the same scale, right? This is not quite the case. Impersonal machine-based information processing has made this process next-level challenging for some, and it’s hackable.
Influencing Through Arithmetic
Social media and even search engines are vulnerable to algorithms that can influence the decision of unsuspecting users (just let the concept of “fake news” flicker across your mind for a second!) What makes this tricky, though, is that we can’t always know for sure whether individual search engines or social network algorithms are designed to influence users. It is murky territory—but what is crystal clear is that there is huge potential for abuse and fraud.
In the beginning, algorithms were never intended to be anything but neutral and fair processes by avoiding all-too-human biases and faulty logic. But, as per usual, our grey-suited friends from the insurance market or large staffing companies have incorporated bias and prejudice into their design to prioritize money over fairness.