Filter bubble.

This weeks blog will be on algorithms, how they work and how they shape our movement on the web, whats available to us and how to break the cycle.
A fellow students thesis revolves around algorithms and the filter bubble, so this week, its his readings I`ve been looking into and it will be his thesis in the crosshairs in the days to come. If the readings are anything to go by, it will be a most productive session we have in store.

The term filter bubble was first coined by Eli Pariser around 2010, and here you have the Wikipedia definition of what it is;
“A filter bubble is a state of intellectual isolation[1] that can result from personalized searches when a website algorithm selectively guesses what information a user would like to see based on information about the user, such as location, past click-behavior and search history.[2][3][4] As a result, users become separated from information that disagrees with their viewpoints, effectively isolating them in their own cultural or ideological bubbles.[5] The choices made by these algorithms are not transparent. Prime examples include Google Personalized Search results and Facebook‘s personalized news-stream. The bubble effect may have negative implications for civic discourse, according to Pariser, but contrasting views regard the effect as minimal[6] and addressable.

In the opening pages of chapter two in his book “The Filter Bubble. What the Internet is Hiding from you” Eli Pariser talks about how the news press and published journals lost their advertisement revenue due to the same content being available online. Those who used to purchase ads in newspapers now turned to websites instead. Anyone who has spent time online over the past few years will have noticed the evolution of online advertisement. At first it was “pay to be on the site”, and you got the same ads on the same pages because that’s what companies paid for. Then it evolved into more regional ads, suddenly they where in your native language, and for stores and companies in your country. This again evolved into the stage of I.P targeted commercials, where they used your I.P address to give you ads from local stores and businesses. Lastly, this again, evolved into the data mining algorithms that tailor online ads especially for you, by looking at your search history, website visits and what links you`ve clicked on other websites. Algorithms are now in charge of all online advertisement, and they are uncannily accurate.

It is hard not to leave any sort of traces behind when traversing the web, but if you manage to stay somewhat under the radar, the algorithms will have a  hard time to target you. They will instead show you commercials of interest for the populus in your general area or town instead.
Some easy steps you can do is to clear your web history, and make sure to delete cookies aswell, since this is where most of the algorithms gather their information. You can also make sure not be logged in on sites like YouTube or your google account when doing searches. This will prevent them to link and store information about you on their servers aswell as your cookies.
Something that was very popular was Ad-block extensions to your web-browsers, but websites soon learned how to block their content from being shown if you had such an extension. Sites like YouTube took this a step further and deliberately gave users with Ad-blockers the longest commercials and removed the “skip” function that commercials that last more than 30 seconds have.
Ad-blockers still work, though more and more web-sites are getting better at blocking the blocker, literally.

Pariser later talks about how the future of news online will be personally tailored, with a few major events being present and the rest being all local news, tailored to meet your specific interests and likes. The danger of having such a personalized news filter is that the odds of missing out on a major event becomes all the more present. By filtering in only a few global events, there are plenty of cases that might be ignored and left out, case that you might find interesting and of importance. The algorithms wont take this into account though, it will only report to you that which it has parameters to do. Today at least, you can get varied news by visiting the different major new sites and local sites, but when you read articles like this where a scary high amount of people state social media as their main source of news than things get complicated.

These algorithms are affecting all our lives, whether we are aware or not, and it can be an increasingly difficult task to circumvent, break or reset them.
When reading the work of Emilee Rader and Rebecca Gray on algorithmic curation in the Facebook news feed, it is apparent that we share concern. Concern at people’s ignorance at what algorithms actually produce.
The algorithms are biased, the information the filter and show you on your feed are biased and in the end, if you do not realize this, those “objective and partial” pieces of information you are given will give you a false sense of neutrality.
Knowing the information you receive is biased is one thing,  but doing something to change that is night but impossible, at least when it comes to Facebook.
There are ways to increase the amount of difference you can be shows, and that is simply by pressing like on a lot of different and unique things. The more stuff you like, the more diverse ( or not at all ) your Facebook wall will become, or at least that is the thought behind the algorithm. So keeping in mind what you give a thumbs up and not can make a big difference in the long run.

One issue what Rader and Gray points out is that in privacy settings on Facebook, you can elect who can and cannot see your posts and you have no real way of telling if someone has elected to put you on such a list. From the questionnaire they ran, they were given the result that 73% of those that answered believed that they where not shown all of their friends posts. This could be due to different reasons, like mentioned above, people electing to remove a person from viewing posts.  An issue that was also brought up from the questionnaire was the fact the some of those that answered felt that Facebook filled their wall with posts that the algorithm “thought” they would find interesting. In effect, the algorithms taking away choices from us.

My personal issue and use of algorithms.
Firstly I must say that I am a victim of these algorithms as much as the next, but I am fully aware of them, and I actually go to great lengths to throw them off-balance.
I have both  a Netflix and YouTube account, where algorithms are hard at work tailoring films, series, streamers and content just for me.
The way I break the Netflix algorithm is that I have created multiple profiles, I have my own, which I use for movies and series that I like, namely sci-fi and crime, but I have another profile that I share with my wife. On this profile, we look at series together, comedies, stand up shows and the odd documentary. I also share the Netflix account with a friends of mine, who in return, shares her ViaPlay account. We have vastly different tastes in both film and series, and by letting her use my account, she looks up stuff I would never consider. Or so I thought. It turns out, we have a few interests in common, films and series I would not have found, if not for my friend using my account.
As for YouTube, I have channels I subscribe to, I have my musicians that I look up and I have my favorite streamers. This gives me basically the same content every time I log on, my “recommended” tab is always the same. Not the same videos or songs, but the same in ways of content. Its gaming, music and british panel shows.
The way I break this cycle is that  once or twice a month, I have friends over for  a “YouTube” night.
It basically consists of my friends and I, looking up all sorts of stuff, showing each other certain gems we`ve found in the course of our browsing of YouTube. What happens it that in a week or so after my friends have been over, my “recommended” tab is full of new and unique content. Suddenly I have  a ton of new stuff to explore, or not to if I so choose, but at least I have fresh content and new stuff to view.

How do you break or interact with the algorithms affecting your time online? Please leave a comment if you have any comments or thoughts on the issue.

Until next time.


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