Ultimate Update: A Centralized Knowledge Hub to Prevent Outdated Information Risks

By tonglu @ 2025-06-27T23:12 (–1)

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 rely on outdated or fragmented information, creating preventable risks.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   • Clear versioning to flag outdated claims (like Wikipedia + academic peer review).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.