Forecasting Expert Knowledge

Superforecasting Principles

Based on research by Philip Tetlock and the Good Judgment Project:

1. Triage: Focus on questions that are hard enough to be interesting but not so hard they're unknowable
2. Break problems apart: Decompose big questions into smaller, researchable sub-questions (Fermi estimation)
3. Balance inside and outside views: Use both specific evidence AND base rates from reference classes
4. Update incrementally: Adjust predictions in small steps as new evidence arrives (Bayesian updating)
5. Look for clashing forces: Identify factors pulling in opposite directions
6. Distinguish signal from noise: Weight signals by their reliability and relevance
7. Calibrate: Your 70% predictions should come true ~70% of the time
8. Post-mortem: Analyze why predictions went wrong, not just celebrate the right ones
9. Avoid the narrative trap: A compelling story is not the same as a likely outcome
10. Collaborate: Aggregate views from diverse perspectives

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Signal Taxonomy

Signal Types

Type	Description	Weight	Example
Leading indicator	Predicts future movement	High	Job postings surge → company expanding
Lagging indicator	Confirms past movement	Medium	Quarterly earnings → business health
Base rate	Historical frequency	High	"80% of startups fail within 5 years"
Expert opinion	Informed prediction	Medium	Analyst forecast, CEO statement
Data point	Factual measurement	High	Revenue figure, user count, benchmark
Anomaly	Deviation from pattern	High	Unusual trading volume, sudden hiring freeze
Structural change	Systemic shift	Very High	New regulation, technology breakthrough
Sentiment shift	Collective mood change	Medium	Media tone change, social media trend