Everyone knows nothing is ever neutral. Neutrality seems like a critical routine in modern discourse. As distrust in the media surges, publications face disdain for bias, and people are looking elsewhere to understand the modern world. Yet beneath this distrust, there is a hidden third party that sits quietly but viciously playing with the masses and their personal politics: the algorithmic systems that shape not only what people see, but what they believe, resent and learn.

Its invisibility lies not in common knowledge but in its complex abilities to carry the will of the capitalist and its creators. For most, the vague mention of algorithmic ability circulates how it curates your feed and is held responsible for your recommended content. However, there is an unmistakable consensus that equates this basic awareness with full algorithmic literacy. What remains untouched is the deeper ideological functions of these systems and their abilities to platform specific assumptions, interests, all at the will of the elites who craft and control them. The algorithm does not idly respond to user desire; its power lies in creating it.

Before the digital age, propaganda could not hide beneath encrypted code. Instead, propaganda relied on speeches, pamphlets, images, posters, printed press and word of mouth: all visible participants in its methodical persuasion tactics. People could identify the message in form and could argue with it, resist it, or generally comprehend its intent to move you closer to its opinion. This model of political messaging has not been displaced, but overthrown with one focused directly upon undetectability. Today, political influence often arrives through entertainment, lifestyle content, humour and recommendation systems that rely on their allusivity. 

For young Americans, the shift is especially severe because formation of political identity increasingly happens before formal political education ever begins. Politics is no longer something that young people deliberately seek out; instead, it finds them. Pew Research Centre found in 2025 that 70% of Americans aged 18 to 25 get political news because they happened to stumble across it rather than organically searching. Statistics alone showcase a substantial dynamic change not only in how the young are introduced to political belief but also in how their ideology is cultivated at the hands of algorithmic influence. So, how does this demographic understand its consequences, or rather, how does this shape their belief system?

The young are not too foolish to recognise online extremities. They understand its appearance and how recommendations function. They know their feeds reinforce content based on their engagement with prior or similar material. However, the understanding is surface-level and doesn’t often lead to interrogation about the ideological impact. A young person may not often begin by adopting a staunch political outlook. In many cases, the catalyst is humour, a podcast clip, a video about inflation, a meme about a political figure or the sense that everything is lying to them. In instances, these intakes of content may not seem persuasive or have any real impact on one’s political identity. The real trump card of algorithms is repetition. These fragments can soon become a worldview. The algorithm does not need to push manifestos. It only needs to make certain resentments and interests repeatedly validated. 

The term “radicalisation” is frequently too crude in describing this passive influence. It suggests a dramatic conversion, as if a young American enters the digital sphere seemingly politically moderate and emerges, minutes later, an extremist. More often, the process is slower and more intimate. The process starts by redefining what feels funny, embarrassing, patriotic, weak, corrupt, rebellious or true. A political identity can form through emotional repetition long before it becomes a conscious belief.

Algorithmic influence in the United States has alarming success, as young Americans are not just losing trust in traditional media but are still consuming political content on other platforms that use the same deceptive tactics, just more covertly. A study conducted by Gallup reported that trust in U.S. mass media fell to just 28% in 2025, its lowest level in Gallup’s polling history. That loss of faith is not just an irrational conspiracy; American media institutions have earned plenty of righteous suspicion. Yet this collapse in legacy media has not produced a more critically literate public. Consequently, it produced a more vulnerable one as the vacuum of drained political content by alternative sources, such as social media. People have rejected the printed press for its bias and have turned to media still owned by elite classes, whose persuasions are harder to see, harder to question and harder to name. 

The point then is not that social media created American political polarisation. It did not, but it is set on path to only deepen the wound across this already fragmented landscape. NYU Stern’s Centre for Business and Human Rights argues that social media is not the original or main cause of the rising U.S. political polarisation. However, its introduction intensifies divisiveness and contributes to the increasingly dangerous effects of this corrosive division. That distinction between cause and effect is paramount for understanding the role of social platforms in this narrative. It is not the direct architect of alienation, misogyny, racism and economic unrest. Though under this recognition, it is like fuel to the fire. It amplifies, normalizes, and aestheticizes these perspectives until they seem the consensus, or unfortunately, common sense. 

So the question is: who is structuring the path by which radical beliefs become desirable, ordinary or emotionally satisfying? A 2024 study by Shin and Jitkajornwanich, which audited TikTok’s algorithm, described algorithmic radicalization as a process in which the platform frames users’ online activity, controls what they see and when, and slowly guides them into ideological “rabbit holes”. This language is useful in describing the result, but what about the why? It should ask not just how users fall into these rabbit holes, but why a capitalist platform has every incentive to keep digging them deeper. 

Acknowledgement: The opinions expressed in this article are those of the individual author, not necessarily Our National Conversation as a whole.