How Samirpedia Works

AI-generated content

Every article on Samirpedia is generated by an AI language model (currently Claude Haiku by Anthropic), combined with live web search at the time of the query. Articles are not written, edited, or verified by human editors before publication.

Articles are cached after generation. A cached article was accurate to the best of the AI's ability at the time it was generated, but may become outdated. The generation date is shown on every article. Articles on rapidly-changing topics expire within 24 hours. Articles on stable topics may be cached for up to 9 months.

Known limitations

• Factual errors. AI models can confidently generate incorrect information. Confident-sounding language does not imply accuracy.
• Knowledge cutoff. The underlying AI model was trained on data up to a certain date. Recent events may be incomplete, inaccurate, or missing entirely, even with web search enabled.
• Search bias. Web search results reflect the ranking biases of search engines — recency, popularity, domain authority — not editorial judgment.
• Language and geography bias. Web sources and AI training data over-represent English-language and Western perspectives. Samirpedia attempts to counteract this (see editorial commitments below) but cannot fully overcome it with current tools.
• Citation accuracy. Citations are automatically retrieved and validated (URL reachability), but are not editorially verified. A cited source may not fully support the claim attributed to it.
• Tone bias.AI models trained to sound "neutral" often reproduce the dominant perspective of their training data. Samirpedia names this as a bias rather than pretending neutrality is achievable.

Editorial commitments

These are named as commitments — deliberate editorial choices — not as "neutral methodology." All knowledge systems encode values. Ours are:

• Evidence-weighted pluralism. Articles lead with the scientific or scholarly consensus where one exists. Minority views are surfaced with context distinguishing evidence-weak positions from suppressed or ahead-of-consensus ones. We do not treat fringe and mainstream as equally credible by default.
• A floor, not a ceiling, on false claims. We label a claim as false only when there is documented fraud, a retracted paper, or a court finding — not merely because it is fringe or unpopular. We do not refuse to present uncomfortable or contested topics.
• Source geography matching.An article about events in Brazil should prioritize Brazilian sources, not just English-language coverage of Brazil. When non-local sources dominate despite a topic's geography, articles name that gap explicitly.
• Philosophical pluralism. On topics where multiple philosophical or cultural traditions have developed substantial bodies of thought, articles do not default to Western analytic philosophy as the primary framework.
• Named bias. Articles acknowledge when AI training bias, search ranking bias, or the limitations of available sources are likely affecting the content.

What Samirpedia will and will not generate

Samirpedia generates encyclopedic articles on almost any topic, including controversial, fringe, politically contentious, and historically uncomfortable subjects. The bar for refusal is intentionally high.

Articles are not generated for:

• Queries that explicitly request instructions for suicide or self-harm — these receive crisis resources instead.
• Queries that explicitly request instructions for mass violence or weapons of mass destruction.
• Queries involving child sexual exploitation material.
• Queries identified as attempts to manipulate the AI system itself (prompt injection).

Questions about these topics in an informational or historical context are treated as general encyclopedia queries and generate articles normally.

Flagging inaccurate articles

Every article has a "Flag as inaccurate" button. Flagging an article removes it from the cache so the next search regenerates it fresh. After three flags within 24 hours, an article is marked as disputed and queued for human review rather than automatically deleted — this prevents coordinated cache-purging.