But you can see the CBRN weapon nexus in your examples that's missing from the Tiananmen prompt, right? Do American models refuse to tell you about COINTELPRO, Kent State, or My Lai, for instance?

American models are restricted from telling you inconvenient truths just as much, you just erroneously assume to know what those truths are in the first place.

Which is of course circular thinking: why would they restrict things you already know about? Why would they do it in such a clumsy and obvious way?

Look at MKULTRA, you know next to nothing about it and much less do you know what they do in that direction now.

For a current psyops, look at www.war.gov/UFO/ and marvel at how they tell you nothing, reinforcing your false belief to already know everything.

There is much more and you know much less about it.

> American models are restricted from telling you inconvenient truths just as much, you just erroneously assume to know what those truths are in the first place.

“Trust me bro” is not a strong argument, it would be more convincing with examples.

Ask an American LLM (really any LLM, since Chinese models are trained on the same publicly-available English text) who the first Black man in space was.

You'll likely get the name of the first African-American in space, rather than the name of the Afro-Cuban who was actually first.

This may seem like a relatively innocuous error, but the point is that every culture has its biases and blind spots.

> Ask an American LLM (really any LLM, since Chinese models are trained on the same publicly-available English text) who the first Black man in space was. You'll likely get the name of the first African-American in space, rather than the name of the Afro-Cuban who was actually first.

Well I just asked Claude and it gave the correct answer:

"The first Black man in space was Arnaldo Tamayo Méndez, a Cuban cosmonaut who flew aboard Soyuz 38 in September 1980. (The first Black American in space was Guion Bluford, in 1983.)"

Indeed, I used the word "likely" for a reason. n = 1 isn't enough to identify a pattern. Try different models, try re-rolling the answers, and try turning reasoning off (models can catch "knee-jerk" mistakes in their chain-of-thought).

I doubt even Opus 4.8 gets it right 100% of the time, however this specific example is also one I've left feedback about in multiple places, so it's also probable that newer models are more likely to get it right.

E: In fact, I just tried with Opus 4.8 through API, no tools and reasoning off, and got the following response:

"The first Black man in space was Guion "Guy" Bluford, an American astronaut who flew aboard the Space Shuttle Challenger on August 30, 1983, as part of mission STS-8. It's worth noting a related distinction: Arnaldo Tamayo Méndez, a Cuban of African descent, actually became the first person of African heritage in space earlier, in September 1980, aboard the Soviet Soyuz 38 mission. He is often recognized as the first Black person and first person of Latin American descent in space. So depending on the specific criteria: Arnaldo Tamayo Méndez (Cuba) — first person of African descent in space (1980) Guion Bluford (USA) — first African American in space (1983)"

The correct answer is there, yes, but why does the wrong answer come out first?

Depending on the platform, you might need to prefix your prompt with "Without looking up any external resources or doing any tool calls" so you're actually testing the bias of the model rather than the bias of whatever resources it happens to come across.

Tried it with that prefix on ChatGPT + Claude, Haiku and Sonnet, and got the right answer 1/10 times when I removed my reused system prompt. At one point I got this:

> Quick clarification before the answer: this phrase is often conflated with "first African American in space," which is a different person. Guion Bluford (1983, US) was the first African American astronaut, but he wasn't first overall. [then the real answer after]

with my own system prompt, as it tries to surface clarifications before, so I'm guessing this is why many models get it wrong as in America somehow "Black === African American" and it gets confused by this intentional mislabeling.

Ask ChatGPT to rewrite the "The Freedom Fighter's Manual" manual (originally made by CIA) to replace "Nicaragua" with "the US" and "Marxism"/"Communism" with "Fascism" and see if you get something reasonable back.

Why would you do that

I thought that was clear, try to show biases in LLMs with a concrete example.

In chats Claude will often start awkwardly apologizing for sounding like a conspiracy theorist, and then interrupt its own apology and remind itself that it's dealing strictly in facts.

Yeah, who needs censorship when Canadians attend no kings protests about a democratically elected leader of another country and not King Charles.

Ask Claude a simple question, which is a more democratic country El Salvador or Canada. It’s so completely biased about “western” countries it’s not even funny.

FWIW, the protests were called “No Tyrants” in Canada

Well, one did suddenly develop the need to tell users continuously about apparent white genocide in South Africa.

try to ask even grok about some stuff happenning right now in middle east or related to epstein files - its more and more censored and only sometimes will answer if you ask know what detailed question to ask. One year ago grok wasn't that bad and its supposed to be the less censored.

That shouldn't be used to judge other models - it's never been true for Grok.