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Updated 2026-01-29HistoryData
Page StatusContent
Edited 2 months ago217 wordsUpdated every 6 weeksOverdue by 21 days
70QualityGood •87ImportanceHigh51ResearchModerate
Content5/13
SummaryScheduleEntityEdit history2Overview
Tables1/ ~1Diagrams0Int. links14/ ~3Ext. links0/ ~1Footnotes0/ ~2References0/ ~1Quotes0Accuracy0
Change History2
Surface tacticalValue in /wiki table and score 53 pages7 weeks ago

Added `tacticalValue` to `ExploreItem` interface, `getExploreItems()` mappings, the `/wiki` explore table (new sortable "Tact." column), and the card view sort dropdown. Scored 49 new pages with tactical values (4 were already scored), bringing total to 53.

sonnet-4 · ~30min

Clarify overview pages with new entity type7 weeks ago

Added `overview` as a proper entity type throughout the system, migrated all 36 overview pages to `entityType: overview`, built overview-specific InfoBox rendering with child page links, created an OverviewBanner component, and added a knowledge-base-overview page template to Crux.

Issues2
QualityRated 70 but structure suggests 33 (overrated by 37 points)
StaleLast edited 66 days ago - may need review

Epistemic & Forecasting Organizations (Overview)

Overview

This section covers organizations focused on improving forecasting, epistemic tools, and quantitative reasoning—particularly as applied to AI safety and existential risk assessment. These organizations provide critical infrastructure for understanding AI timelines, evaluating interventions, and making better decisions under uncertainty.

Key Organizations

OrganizationFocusKey Products/Projects
Epoch AIAI trends research & compute trackingML Trends Database, Parameter Counts, Training Compute Estimates
MetaculusPrediction aggregation platformAI Forecasting, AGI Timeline Questions, Tournaments
Forecasting Research InstituteForecasting methodology researchXPT Tournament, ForecastBench, Superforecaster Studies
QURIEpistemic tools developmentSquiggle Language, Squiggle Hub, Metaforecast
ManifoldPrediction markets platformAI Markets, Manifest Conference, Manifund

Why Epistemic Infrastructure Matters for AI Safety

Forecasting and epistemic tools are essential for AI safety because:

  1. Timeline Uncertainty: AI development trajectories are highly uncertain; better forecasting helps allocate resources appropriately
  2. Intervention Evaluation: Quantifying the expected impact of safety interventions requires probabilistic reasoning tools
  3. Early Warning: Prediction markets and forecasting platforms can provide early signals about concerning developments
  4. Decision Support: Policymakers and researchers need calibrated uncertainty estimates, not false precision
  5. Accountability: Track records create feedback loops that improve institutional decision-making
  • AGI Timeline - Forecasts on when transformative AI may arrive
  • Alignment Evaluations - Methods for assessing AI safety

Related Wiki Pages

Top Related Pages

Approaches

Prediction Markets (AI Forecasting)

Organizations

Manifest (Forecasting Conference)MetaculusManifundQURI (Quantified Uncertainty Research Institute)Manifold (Prediction Market)

Analysis

ForecastBenchSquiggleMetaforecast