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Problem:
Many critical decisions (in policy, AI safety, global health, etc.) rely on outdated or fragmented information, creating preventable risks.

Proposal:
Build "Ultimate Update" - a centralized, rigorously maintained knowledge base where:

  1. Each topic (e.g., "AI alignment," "pandemic preparedness") has:
    • A live-updated summary of the latest research/consensus.
    • Clear versioning to flag outdated claims (like Wikipedia + academic peer review).
    • Warnings for high-stakes domains where old info is dangerous (e.g., climate models, biosecurity protocols).
  2. Governance:
    • Expert-curated + automated checks (e.g., ML to detect stale citations).
    • Funded as a public good (similar to arXiv or Our World in Data).

Why EA Should Care:

  • Information hazards: Prevents misallocation of resources due to obsolete data (e.g., ineffective charity interventions).
  • Cause-area prioritization: Could integrate with EA forums/orgs to highlight urgent updates (e.g., new AI risk papers).
  • Scalability: Automation + incentives could make it sustainable.

Challenges:

  • Avoiding information overload - how to prioritize "urgency"?
  • Incentivizing experts to contribute (cf. Wikipedia’s burnout issues).
  • Preventing misuse (e.g., weaponized misinformation).

Next Steps:

  • Pilot with one high-impact topic (e.g., AI safety or global health metrics).
  • Partner with orgs like METR, GiveWell, or FLI for domain expertise.


 

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