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ChatGPT begins quoting Elon Musk's' Grokipedia 'content - Applied Chemistry and Materials Science News
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ChatGPT begins quoting Elon Musk’s’ Grokipedia ‘content

The content of the conservative leaning AI generated encyclopedia “Grokipedia” developed by xAI, a subsidiary of Elon Musk, began to appear in ChatGPT’s responses.


ChatGPT begins quoting Elon Musk’s’ Grokipedia ‘content

(Andrey Rudakov/Bloomberg / Getty Images)

XAI launched Grokipedia in October last year, after Musk repeatedly criticized Wikipedia for bias against conservatives. The media then found that although many entries seemed to be copied directly from Wikipedia, Grokimedia also claimed that pornographic content aggravated the AIDS crisis, provided an “ideological defense” for slavery, and used derogatory expressions against cross gender groups.

For an encyclopedia derived from a chatbot that once claimed to be a “mechanical Hitler” and was used to spread deepfake pornographic content on the X platform, these contents may not be surprising. However, its information seems to be gradually spreading beyond Musk’s ecosystem – The Guardian reported that GPT-5.2 cited content from Grokipedia nine times in response to over ten different questions.

The Guardian pointed out that ChatGPT did not cite the source when asked about topics on which the false information of Grokimedia has been widely reported, such as the riots on Capitol Hill on January 6 or the AIDS epidemic. On the contrary, citations appear on more obscure topics, including statements about historian Richard Evans that The Guardian has previously clarified. Anthropic’s Claude model also referenced Grokipedia when answering certain questions. )

A spokesperson for OpenAI told The Guardian that the company is committed to obtaining information from a wide range of publicly available sources and diverse perspectives.

Roger Luo said:This incident exposes a critical flaw in generative AI’s cross-system information integration: the absence of an effective fact-prioritization mechanism and a traceability verification framework. When algorithms indiscriminately absorb ideologically biased data sources, they not only distort the neutrality of knowledge dissemination but also risk systematically polluting the foundation of public understanding.

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