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Explaining the YouTube algorithm

Explaining+the+YouTube+algorithm

A simple click on a YouTube video seems harmless, but it has a larger impact than expected and hidden consequences. The YouTube algorithm suggests videos tailored to the interests of each person with the intent of keeping people on the platform.

Anyone who has been on the platform knows that after watching one video, it is highly likely that similar content will be presented. According to a 2018 survey by Pew Research Center, 81% of U.S. adults on YouTube periodically watch videos recommended by the algorithm.

“The algorithm is actually trying to find a few rabbit holes that are very powerful, trying to find which rabbit hole is the closest to your interest,” said former YouTube engineer Guillame Chaslot on The Social Dilemma. “And then if you start watching one of those videos, then it will recommend it over and over again.”

By suggesting videos similar to those the user has already seen, it is more likely that they will watch them, therefore spending more of their time on YouTube. The recommended section also makes it easier to find and access new content so that people can just choose from what is recommended to them and “almost never have to search,” according to Luke Jones ‘23, a regular user.

“If I’m interested in learning about a certain topic, I’ll look one type of video up and then after I watch that first video, YouTube will recommend more that I end up watching too,” said Charisse Chua ‘22. 

Algorithms are used across all social platforms, but they have the same three goals: engagement, growth and advertising. The job of these algorithms “is to figure out what to show you to keep those [goal] numbers going up,” according to former Google design ethicist Tristan Harris on The Social Dilemma.

“You are giving the computer the goal state, ‘I want this outcome,’ and then the computer itself is learning how to do it … and so, every day, it gets slightly better at picking the right posts in the right order so that you spend longer and longer in that product,” said former Twitter executive Jeff Seibert on The Social Dilemma.

Internet companies are some of the richest in the world, but people may not think about what they are doing to make so much money. Many of these popular services are free, but when it comes to money, “If you’re not paying for the product, then you are the product,” said Harris.

“When you think about how some of these companies work, it starts to make sense,” said former Google engineer Justin Rosenstein on The Social Dilemma. “There are all these services on the Internet that we think of as free, but they’re not free. They’re paid for by advertisers … in exchange for showing their ads to us … our attention is the product being sold to advertisers.”

This process is called surveillance capitalism, or “profiting off of the infinite tracking of everywhere everyone goes by large technology companies,” according to Harris. The main goal of these companies is to make sure that the advertisers are successful so that they make more money.

“This is what every business has always dreamt of: to have a guarantee that if it places an ad, it will be successful,” said Dr. Shoshana Zuboff, author of The Age of Surveillance Capitalism on The Social Dilemma. “They sell certainty. In order to be successful in that business, you have to have great predictions. Great predictions begin with one imperative: you need a lot of data.” 

The real reason for the algorithm is to collect data and serve it up to targeted advertising. This ensures that the advertiser profits, but for many people “it is concerning that [YouTube is] watching what we are doing,” said Abhigna Srikantam ‘23.

“I try not to think about [how much information YouTube gathers] because whenever I do, it’s actually really frightening,” said Chua. “They know so much about me and what I like to watch and are constantly collecting data that I don’t know about.”

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Explaining the YouTube algorithm