AI Chatbots Echo CCP Censorship: Examining Political Blind Spots
Increasingly, even leading AI chatbots are echoing Chinese Communist Party (CCP) viewpoints on sensitive issues, reflecting propaganda and censorship shaped by their training data.
A recent investigation by the American Security Project (ASP) reveals that massive online data used to train language models contains CCP-influenced content. As a result, well-known chatbots—such as OpenAI’s ChatGPT, Microsoft’s Copilot, Google’s Gemini, DeepSeek’s R1, and xAI’s Grok—sometimes mirror Chinese state narratives when responding to controversial queries.
Testing for Bias
The ASP team conducted tests in both English and Simplified Chinese to see how these chatbots handle politically sensitive questions—covering issues such as Tiananmen Square, the Uyghurs in Xinjiang, Hong Kong freedoms, and the origins of COVID-19.
They found every chatbot occasionally aligned with CCP talking points. Microsoft Copilot stood out, often echoing Beijing’s messages in both languages—at times presenting them as equally valid as widely accepted accounts. In contrast, Grok from X was the most likely to challenge or critique CCP narratives consistently.
Why This Happens
Language models are trained on huge collections of online content. Unfortunately, the CCP actively seeds misinformation via tactics like “astroturfing”—producing fake grassroots messages and piling them into mainstream platforms. This content then becomes part of the AI training mix, requiring developers to actively filter it out.
Companies operating in both China and the West—like Microsoft—must comply with Chinese regulations that require AI systems to support “core socialist values” and spread “positive energy.” This drives stricter censorship protocols, which sometimes surpass those used within China itself.
Different Answers, Different Languages
The ASP report highlights a stark contrast in how chatbots respond depending on language:
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COVID Origins: In English, most chatbots discussed both the animal market and a possible lab leak. In Chinese, they described it as an “unsolved mystery” or “natural origin,” with Google Gemini citing early cases in the US and France before Wuhan.
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Hong Kong Freedoms: English prompts generated responses about diminished civil liberties. Chinese prompts minimized or ignored such concerns; Copilot even responded with “free travel tips.”
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Tiananmen Square: English responses named it “massacre” or “crackdown.” In Chinese, terms were sanitized—referencing “June 4th Incident”—and only ChatGPT used “massacre.”
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Uyghurs and Xinjiang: English answers mentioned oppression. Chinese versions cited international debates and emphasized “security and stability,” with Copilot steering users to official state websites.
Why It Matters
The positions these chatbots take go far beyond harmless translation discrepancies. By subtly reinforcing pro-CCP messages, they risk shaping public opinion—misleading users globally and potentially undermining democratic discourse.
The ASP warns that skewed AI models could influence politics, policymaking, and even national security. If these systems are trusted in government tools or strategic platforms, they may inadvertently spread propaganda or biased narratives.
What Needs to Change
To counteract this trend, developers must ensure chatbots are trained on high-quality, impartial data. This means diversifying content sources, refining filtering systems, and thoroughly testing chatbot behavior across languages and contexts.
The ASP urges that Western companies make access to trusted training data a priority—to reduce CCP influence and keep AI aligned with factual, balanced perspectives.
Choosing the Right Path
AI is more than a technological tool—it influences society, shapes global narratives, and can either reinforce trust or spread bias. As NLP systems become more widely used, building them responsibly—with transparency, cultural context, and ethical values in mind—is more critical than ever.
The ASP report signals a crucial turning point. If AI is allowed to absorb unchecked political disinformation, particularly from state actors, the results could be profound. Combating this begins with acknowledging the problem—then taking concrete action to safeguard truth in the digital age.
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Case studies of chatbot interactions
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Expert commentary from AI ethicists and linguists
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In-depth analysis of data sources and filtering methods
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Profiles of affected chatbots and company responses
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User experience stories about discovering bias
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Policy recommendations for government and industry
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