Questions censored by DeepSeek

Original Article ↗ Hacker News Discussion ↗

Nature and extent of DeepSeek censorship

  • Many commenters attribute DeepSeek’s behavior to Chinese legal requirements to uphold “Core Socialist Values” and avoid politically sensitive topics (e.g., Tiananmen, Taiwan, Uyghurs).
  • Hosted DeepSeek (especially R1 671B on deepseek.com and some US-hosted APIs) often gives stock refusals or CCP‑aligned framings on such prompts, while answering similar questions about other countries.
  • Several note that the censorship can be asymmetric: detailed criticism of the US is allowed where criticism of Chinese state actions is blocked.

Hosted vs local, and model confusion

  • Strong distinction between:
    • DeepSeek-R1 671B (original reasoning model, heavily censored),
    • “R1 Zero” (earlier, reportedly less aligned),
    • Distilled models (Llama/Qwen fine‑tuned on R1 outputs) used by Ollama, Groq, etc.
  • Distilled smaller models often show much weaker or no censorship on Chinese politics, leading to conflicting anecdotes from users who think they’re “running R1 locally” when they’re actually running a distilled Llama/Qwen.
  • Some report additional bolt‑on moderation on hosted services: partial answers appear, then are wiped and replaced with a generic refusal.

Technical implementation and jailbreaks

  • Debate over whether censorship is:
    • post‑hoc filtering of outputs,
    • explicit safety fine‑tuning (RLHF),
    • or implicit via censored training data.
      Evidence suggests all three exist across different Chinese models and hosting setups.
  • Users show simple jailbreaks (e.g., leetspeak / ROT13 / alternative encodings) that bypass keyword filters and elicit detailed Tiananmen descriptions.
  • Similar multi‑layer safety stacks and browser‑side output filters are described for ChatGPT and other US models.

Comparison with Western LLMs

  • Many argue Western models also censor heavily (weapons, self‑harm, “crime stats,” group‑targeted questions, some live political scandals) but frame it as “safety” or “harm reduction.”
  • Examples show uneven treatment depending on country, religion, or person, and non‑deterministic refusals.
  • Some see Chinese censorship as more overt and state-driven; Western censorship as subtler, corporatized, and still influenced by governments and powerful individuals.

How much this matters

  • Split views:
    • Some only care about coding/technical tasks and see political censorship as irrelevant.
    • Others worry that people increasingly use LLMs instead of search, so embedded propaganda or omitted history is socially dangerous.
  • Several call for symmetric audits: similar prompt‑refusal datasets for ChatGPT, Gemini, Grok, etc., not just DeepSeek.