The Filter Bubble of the internet

The “filter bubble” is the internet phenomenon where people are stuck in their own bubble of like-minded thought on the internet because of specialized algorithms that are meant to target the user and serve up ads that that person may like. For this project, we were tasked with getting on a friend’s computer and surfing the internet to see what ads and suggestions they are served up. I spent some time on my roommate’s computer. Logan and I are very alike, but we still have some very sharp differences when it comes to what we like and enjoy on the web. I spent some time on Logan’s MacBook and was interested in the results of this experiment.

               Logan and I both like riding longboards, but I only recently started while he had been doing it for many years now. Logan also watches lots of skateboarding and longboarding videos on YouTube. Because of this, the suggested videos for Logan are almost primarily videos from his favorite channel or those similar to it. My YouTube recommendations usually have something to do with computers, drones, science, or guns. These differences show you what we usually watch online, and shows that YouTube remembers the videos we watch and uses them to recommend new videos to watch. The websites we use daily are not learning what we like and using it to target ads toward us. It’s similar to the computers described in chapter 8 of “The Pattern on the Stone” where the author writes about computer that learn and adapt. Computers are learning our patterns of thoughts and likes and are adapting the advertising to be more relevant to us. The algorithms are sometimes similar to those described in chapter 5 of “The Pattern on the Stone” where the author writes about what algorithms are and how they are used. These specific algorithms are being used to track out movement across the web and figure out what we like.

               One of the other websites that I surfed while on Logan’s computer was Netflix. I was not surprised to see similar results as those on my recommendations, as we often watch the same shows together. One difference was that Netflix realized that I enjoyed documentaries specifically about topics related to science and computers. The algorithm that Netflix uses probably looks not only at what we watch, but how long we watch it. If we start a show but only watch a few minutes before turning it off, Netflix should assume that we did not like the show and should not give us recommendations similar to the show we did not like. The algorithm that Netflix uses was actually not created by them. There was a competition from 2006 to 2011 that challenged teams to create the algorithm that Netflix uses now, or at least is based off of. You can still see the website for the competition at http://www.netflixprize.com/.  Netflix awarded $1 Million to the grand prize winning team. Over one thousand teams entered and competed for the grand prize.

               The big questions about this type of targeted advertisement is privacy. How can a company like Facebook be so spot on with its advertisements? Facebook tracks us as we go onto nearly every page on the internet. If a webpage has a “like” button or a way to comment through Facebook, then they can see that you have visited that page. You could support a strong argument that some of these algorithms and websites know us better than we know ourselves, which seems to scare some people and not phase other people. Do you think we deserve more privacy from internet giants such as Facebook and Google?