Last March, a community health activist in Myanmar published a warning about escalating violence. By Wednesday, it vanished, flagged, filtered, and disappeared by content algorithms she'll never meet, applying standards she wasn't shown, through processes no one can appeal. Halfway across the world that same day, a political influencer with ten million followers posted similar warnings. His remained visible, amplified, promoted.

These decisions join the 3.8 billion moderation verdicts algorithms make daily. According to industry data, 94% receive no human review whatsoever. More telling still: 28% of posts containing keywords like "protest" or "rally" face automatic temporary visibility restrictions, with the severity varying by geographic origin data.

Neither decision was explained. Neither was argued before judges or juries. There were no briefs filed, nor precedents cited, no dissenting opinions. Just lines of code executing their silent calculus of who deserves to be heard. We've replaced courthouse steps with server farms, legal arguments with machine learning parameters, and public deliberation with proprietary algorithms. This isn't simply a technological upgrade. It's a fundamental restructuring of how expression is governed, who holds the power to silence, and which voices carry. Content moderation algorithms don't just enforce rules; they write the rules by deciding which enforcement patterns become normalized.

The EU Digital Services Act requires platforms to publish content moderation statistics. Fourth-quarter numbers showed 217 million removed posts globally. Researcher access to raw data remains restricted. Three platforms have faced preliminary fines for non-compliance with transparency requirements. Four have challenged these fines successfully.

The tech companies building these systems operate in a curious gray zone: too powerful to be mere platforms, too unaccountable to be proper governments, yet exercising authority that rivals both. Meta moderates more speech daily than all courts globally combined. Since 2021, Trust and Safety teams at major platforms have shrunk by an average of 72%, even as moderation decisions continue to multiply. This selective enforcement isn't a bug in the system of algorithmic governance. It might be its defining feature.

Let's take a closer look at who gets silenced and who doesn't.

Twitter (I Refuse to Call It by That Single-Letter Rebrand) - A Broken Dream of Neutrality and Algorithmic Fairness

There was a lot of speculation around the intentions and goals of Elon Musk when he wanted to buy Twitter, which he rebranded as Twitter. It promised a "free speech absolutist" utopia. Instead, it exposed a stark reality: AI content moderation is a tool of selective enforcement. Musk swiftly reinstated banned accounts, including those of Donald Trump and conspiracy theorist Alex Jones, while touting algorithmic transparency. Ironically, the latter was even more controversial, considering Alex Jones's involvement in the lawsuit regarding the Sandy Hook Elementary School shooting.

Yet, within months, Twitter quietly rolled back these policies under advertiser pressure, banning critics like journalist Aaron Rupar for "abusive behavior" while allowing far-right influencers like Andrew Tate to thrive. This naturally raised questions about Elon Musk's commitment to free-speech, considering the double standards on its implementation on the platform.

This flip-flop epitomizes a broader pattern across tech platforms: public claims of neutrality mask opaque, politically convenient enforcement that privileges tech elites and MAGA-aligned voices. A separate yet still worth considering fact was that one of the first decisions after Twitter's acquisition was firing roughly 80% of the staff (particularly engineers) working in Trust and Safety.

The worst part is this trend is not limited to Twitter. Other platforms are using content moderation to benefit certain groups while marginalizing others.

Me...