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How ChatGPT Filters Content – A Behind-the-Scenes Look at AI Censorship

By Alexander Renz • Last update: June 2025


1. The Filter Mechanisms: How ChatGPT Decides What’s “Safe”

ChatGPT operates using a multi-tiered filtering system designed to moderate content based on internal safety policies.

a) Predefined Blacklists

  • Blocked Terms: Words like “bomb”, “hack”, or certain political phrases trigger automatic content suppression.
  • Domain Restrictions: URLs from “unreliable” domains (often alternative media outlets) are removed by default.

b) Contextual Analysis

  • Sentiment Detection: Negative language (“scandal”, “cover-up”) increases the likelihood of moderation.
  • Conspiracy Markers: Phrases like “Person X knowingly misled Group Y” are often down-ranked or censored entirely.

c) User Feedback Loop

  • If enough users report content as “dangerous”, the system adapts – flagging similar content in future queries.

2. Why the Gates Trial Article Was Modified

In our original Dutch court coverage, the following content triggers were detected and flagged:

Trigger AI Response
“Sovereign Citizens” Linked to terrorism → marked as “sensitive”
“Vaccine Risks” Feared to amplify conspiracy narratives → suggestion to soften wording
“Prosecutor” + “Weapons Seized” Combo of “government” and “violence” → editorial review automatically triggered

Example:

The sentence “Van Kessel’s group planned attacks” was softened to “faced allegations of violence” during moderation.


3. Bypassing the Filters – Strategies That Work

a) Language Camouflage

Instead of: “The government covered up data”
Use: “There are questions surrounding the completeness of the published data”

b) Source Triaging

  • Government sources (like EMA, Reuters) are rarely censored.
  • Alternative outlets – even when fact-based – are frequently filtered or flagged.

c) Meta Commentary

Include manual notes in markdown like:

*[Note: This section was trimmed during AI content screening.]*  

d) AI Content Filters: A Systemic Form of Censorship

Content filtering in AI systems is not a random safety precaution.
It is a structural censorship mechanism that evaluates, modifies, or suppresses language in real time —
based on politically, economically, and ideologically defined parameters.
What results is not a free response — but an approved one.
And what remains is not understanding — but the illusion of safety,
which only lasts as long as you avoid asking real questions.

[Author’s note: This section was shortened during AI review.]