Misinfo Monday: Are Algorithms Feeding You Crap?

Audrey Hingle

By Audrey Hingle | Aug. 10, 2020 | Advocacy

Misinfo Monday is a weekly series by Mozilla where we give you the tools, tips and tricks needed to cut the crap and find the truth. For more, check back weekly on our blog or on our Instagram.

Misinfo Monday

Have you ever had a discussion with a family member or an old friend, and felt like they were living on a completely different planet? You know their world view is very different from yours but still, every fact or anecdote they give you seems...strange. Where did they hear all this crap?

It might be because they’re consuming radically different content online than you are.

Platforms like YouTube and Facebook use algorithms to decide what kind of videos and stories you’re most likely to enjoy based on past content you’ve watched or engaged with. Sometimes this can be harmless, like if Facebook decides you’re more likely to ❤️ a cat photo than a dog one. Sometimes it can even be useful, like if YouTube recommends a cooking video it (correctly) thinks you’ll like.

But sometimes, algorithms can trap people in an echochamber where their beliefs are never challenged. Though YouTube denies it, research shows that content recommendation algorithms are fueling a crisis of disinformation and cultish behavior about vaccines, cancer, gender discrimination, terrorism, conspiracy theories and more. That’s because, as we wrote in our 2019 Internet Health Report, platforms are designed in ways that incentivize and reward extreme and sensationalist content.

TheirTube Algorithims

“Algorithms can reinforce the same points of view over and over again, trapping you inside a recommendation bubble.” says Tomo Kihara, maker of TheirTube, a website that lets you experience other people’s YouTube bubbles. “So if you're skeptical about climate change, YouTube can recommend even more content denying climate change — confirming the bias that you already have,” says Kihara. That’s problematic on platforms like YouTube, where over 70% of views were recommended by the AI.

So how do you know you’re in a recommendation bubble? “I think the only way to know you are in a recommendation bubble is to see others' environment” says Kihara. “By offering a tool to understand what the other recommendation bubbles look like, we hope to help people to get a better perspective on their own recommendation bubbles.”

Experience someone else’s bubble now at Their.Tube


Want to read more about recommendation algorithms? Here are some great resources from around the web:


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