
Filter bubbles are personalized query results on websites. Depending on your interest, search results and social media feed will differ from person to person. Algorithms on Facebook, Google, and many other websites decide what kind of information a user will see based upon interests, location, and other various demographics. For example, in Eli Pariser’s Ted Talk he asked two of his friends to Google “Egypt”. Eli’s friends got two very different search result pages. One search result page mentioned protests in Egypt while the other results page mentioned traveling to Egypt. Algorithms are filtering information for individuals, however this can be more of a hinderance than advantage for users.
I think that the “filter bubbles” are meant to enhance user experience on websites, no one wants to look at information they are not interested in. Users may be compelled to leave a website if content is not personalized to them. I don’t think that filter bubbles are inherently bad because as an advertising student I have been taught that personalization is a good thing, but I think filter bubbles could be causing more harm than good. Users are not being exposed to additional information or viewpoints. If people are willing to change their viewpoints but are not given the opportunity because new information is not available to them. I believe that filter bubbles are doing a disservice to those who are trying to learn new information and see viewpoints that are different from their own. For example, with the 2020 election approaching people may want to do some research on candidates. If Google and Facebook only shows users Republican and conservative information, they have not been given the chance to decide for themselves what information they want to learn and there is a possibility of their vote being swayed. Filter bubbles offer personalization to the extreme, this personalization comes at a cost where users are not given the opportunity to learn new information and decide for themselves what they want to see.






