Anika Outsmarts the Algorithm

Anika was no ordinary eighth grader. While other kids were busy scrolling, Anika was reverse-engineering the recommendation engine of the biggest video app around. She wasn’t trying to be a hacker—just curious.

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One evening, after watching a cooking video, Anika noticed her feed was suddenly full of noodle recipes. She smiled and wondered, “Can I trick the algorithm into thinking I love llamas?”

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So, she clicked on every llama video she could find. Then she let them play on loop while she did her homework. Within 48 hours, her feed transformed—llamas doing yoga, llamas skateboarding, llama memes galore.

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Then she took it further: she created a chart, mapping how long it took the app to change based on different types of engagement. Her school’s computer science teacher spotted her working on it in the library and was amazed. He encouraged her to present her findings at the school’s innovation fair.

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Anika didn’t stop there. She turned her experiment into a project on how digital platforms profile users. She titled it: "Feeding the Feed: How I Trained My App to Think I'm a Llama Whisperer."

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When judges at the fair asked her what her goal was, she said, “To show that we shouldn’t let machines decide what we see, eat, or believe. We should be the ones training them—not the other way around.”

Anika won first prize. Her project is now being used as a fun case study in a digital literacy program run by a youth tech foundation.

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Did You Know? Recommendation engines use a mix of algorithms like collaborative filtering and content-based filtering to decide what to show you.

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Anika’s friends now joke she’s the “algorithm tamer.” But Anika just shrugs and says, “I’m just feeding it a new story.”