How TikTok and Instagram Use Artificial Intelligence: Is the Algorithm Choosing What We See?

We scroll with a swipe, and like magic, the perfect videos appear. But how does TikTok know we love funny cats or cooking hacks? And why does Instagram keep suggesting posts on a topic we barely glanced at? The answer lies in artificial intelligence. The algorithms that power social media feeds aren’t just lines of code—they’re complex systems that learn from our behavior to deliver personalized content. Convenient? Sure. But also a bit unsettling.

Every time we like a post, watch a video to the end, or linger for a few seconds, we’re feeding information to a recommendation engine. That engine compares our actions with data from millions of users and predicts what we’re likely to enjoy next. This is how the famous “personalized bubble” forms a continuous stream of custom-tailored content designed to keep us scrolling.

The problem isn’t efficiency it’s the side effects. We risk being exposed only to viewpoints that mirror our own, reinforcing our beliefs without challenge. Worse, we might be nudged toward extreme or manipulative content, not because the algorithm has intent, but because it has learned what keeps us hooked.

A study by the Center for Humane Technology revealed how social platforms unintentionally fuel the spread of polarizing content. TikTok, for instance, has been criticized for quickly guiding users toward radical or conspiratorial videos based on even minimal initial interest. Source: The Social Dilemma – Center for Humane Technology]

All of this happens through a mix of machine learning, predictive analytics, and large-scale data collection. That’s where privacy concerns come in. The data we give up—often just by interacting—are used to map our preferences, vulnerabilities, and emotional states. The goal is to keep us engaged as long as possible. But at what cost?

In our article“AI and Social Media: Algorithms That Guide Us,”we already explored these dynamics. For more on the dangers of misinformation, see“Fake News and AI: An Informational War.””.

There’s also the issue of algorithmic bias. Algorithms aren’t neutral they learn from human data, which are often flawed. If a certain type of content has been rewarded in the past, it will likely continue to be promoted, reinforcing existing patterns and silencing diversity. This creates dynamics that privilege some voices while marginalizing others.

Artificial intelligence in social media has two faces. On one hand, it helps us discover new content, connect with like-minded people, and enjoy smoother digital experiences. On the other, it can distort reality, showing only what keeps us scrolling.

To navigate this complexity, we need awareness. Digital literacy can help us recognize how these systems work, and why we see certain content instead of others. Only then can we shift from passive users to critical digital citizens.

The future of social media doesn’t just depend on technology it depends on how we choose to use and regulate it, and on our willingness to understand what’s really behind every scroll.