When Algorithms Know Us Better Than We Know Ourselves

By: Muhammad Tegar Qolbi
Communication Science Student, 17 Agustus 1945 University Surabaya

JurnalPost.com - Have you ever felt a bit surprised when opening TikTok or Instagram? Just as you become interested in something, content about that topic soon begins to appear. You search for a product, and suddenly its ads appear on various platforms. Even when you are looking for specific information, it feels as if social media already understands what you want to see.

Such situations often make us ask, "How does the algorithm know so much?"

The question sounds simple. But if thought about more deeply, there is an interesting issue behind it. Does the algorithm really know us? Or is it actually us who, without realizing it, keep providing information to the algorithm about who we are and what we like?

The internet and social media have now become an almost inseparable part of the lives of the Indonesian people. DataReportal noted that around 230 million people, or about 80.66 percent of Indonesia's total population, were using the internet by the end of 2025. Meanwhile, the number of social media user identities was recorded at around 180 million, or 62.9 percent of the population.

That figure shows how much space the internet and social media occupy in daily life.

Social media is no longer just used for communication. We use it to find information, enjoy entertainment, follow trends, build relationships, and even decide what items to buy.

However, every activity leaves something behind: a digital footprint.

We Are the Ones Teaching the Algorithm

When we press the like button, share a video, follow an account, type something in the search bar, or just watch a video to the end, we are actually providing information to the platform.

TikTok, for example, explains that its recommendation system considers various forms of user interaction. The content we watch, the content we skip, the accounts we follow, and even the information contained within a video can be part of the system's considerations in determining the next recommendation.

This means that when we feel the algorithm knows exactly what we like, some of that information actually comes from our own actions.

The problem is that this process happens so subtly that we often do not realize it.

For us, social media activity might just be scrolling, watching videos, laughing, giving a like, and then moving on to the next piece of content. But for digital systems, these actions are data.

From that data, the algorithm begins to read patterns.

If we often watch travel content, the likelihood of travel content appearing will increase. If we frequently interact with topics related to work and careers, our feed will slowly be filled with similar content.

The same applies when we frequently search for information regarding sports, music, technology, education, or other specific topics.

From here, a cycle is formed.

We choose content. The algorithm reads that choice. The algorithm then offers similar content. We become interested again and interact with that content.

The process repeats.

At a certain point, the algorithm is not just reading what we like, but also helping to determine what we will see next.

"For You" Is Not Necessarily All About Us

The term "For You" has become one of the most familiar phrases on various social media platforms.

It is as if the platform is saying, "This content was made specifically for you."

To a certain extent, that statement is true. The content that appears has usually been adjusted based on the user's activity patterns.

However, personalization does not mean the algorithm truly understands us.

The algorithm does not fully know the reason why someone likes a video. The system only reads measurable behavior.

For example, when we pause a few seconds longer on a piece of content, the system might interpret that action as a sign of interest. In reality, we might just be daydreaming, receiving a message from someone, or forgetting to scroll.

The algorithm reads actions, not necessarily the reasons behind those actions.

This is where another issue arises.

When a certain type of content constantly appears on the screen, we might start to feel that the content truly aligns with who we are. Yet, that interest could be growing stronger simply because we are too frequently exposed to the same thing.

In other words, the algorithm does not just follow our preferences. In certain conditions, the algorithm can also help reinforce those preferences.

When the Feed Feels Like a Reflection of the World

This phenomenon is also related to the concept of a filter bubble.

Simply put, users increasingly receive information that aligns with their interests, habits, and previous interaction patterns.

At a glance, this feels comfortable. We do not need to search too far because content deemed interesting is already available before our eyes.

However, there is a risk when we start assuming that what appears on our feed is a complete picture of the world.

That is not necessarily the case.

When someone continuously receives content with the same opinion, they may feel as if everyone holds a similar view.

When someone keeps seeing a certain lifestyle, they may assume that many people's lives are indeed as they appear on social media.

In reality, the algorithm only displays a small fraction of information deemed most relevant to the user's behavioral patterns.

The world is certainly much broader than the "For You" page we see every day.

Need to Be More Critical in Using Social Media

In my opinion, this condition is why we need to be more critical when using social media.

This does not mean technology or algorithms should always be viewed with suspicion.

Social media has provided many benefits. Through social media, one can learn, find new information, build communities, promote work, open business opportunities, and communicate with people living far away.

However, we still need to understand that what appears on the screen does not always happen by chance.

There is a system working behind it.

As a Communication Science student, I see the algorithm phenomenon not just as a technological issue, but also as a communication issue.

Every day, it is as if we are constantly communicating with digital platforms through very simple actions. Every click, search, comment, watch time, and interaction becomes a form of information provided to the system.

That data is then used by the platform to "communicate back" to us through content recommendations deemed most relevant.

The relationship between humans and digital media is no longer one-way.

We choose content, but the content displayed can also influence our next choices.

Therefore, perhaps we occasionally need to stop scrolling and ask ourselves:

"Do I really like this, or do I like it because I see it too often?"

That simple question is important because, in the midst of increasingly smart digital systems, the ability to understand oneself becomes increasingly valuable.

Perhaps the algorithm never actually knows us better than we know ourselves.

The algorithm only possesses a vast amount of data about our habits, including small habits that we sometimes do not even realize ourselves.

Ultimately, the challenge in the digital era is not just about how we use algorithms.

The greater challenge is how we maintain awareness of our own choices, interests, and ways of thinking as algorithms become increasingly adept at studying every footprint we leave behind.