Appendix _ โ ๐ DIH Market Allocation
The $48 Billion Committee Problem
The NIH spends $48 billion per year on medical research. 200 reviewers decide where it goes. 90% of grant applications get rejected. 95% of diseases have zero treatments.
This is what happens when you let committees play god with money.
Markets vs Committees: The Track Record
Soviet Union (Central Planning):
- 5-year plans
- Bread lines
- Economic collapse
United States (Markets):
- Innovation explosion
- Abundance
- Global dominance
Guess which one the NIH copied?
How DIH Markets Work
Instead of 200 reviewers picking winners, we use:
1. Prediction Markets for Research Priorities
- Researchers bet real money on which diseases will be cured
- Market prices reveal collective intelligence
- Bad predictions lose money (skin in the game)
- Good predictors get more influence over time
2. VICTORY Bonds: Investors Pick Winners
- Bond holders vote on funding allocation
- Returns tied to actual health outcomes
- Bad investments = lost money
- Good investments = 40% annual returns
3. Patient Choice Markets
- Patients choose which trials to join
- Popular trials get more funding automatically
- Shitty trials die fast
- Natural selection for research
The Math: Why Markets Win
NIH Model:
- 200 brains making decisions
- No skin in the game
- Political influence matters
- 10% success rate on grants
DIH Model:
- 280 million brains contributing information
- Everyone has skin in the game
- Only results matter
- Natural selection ensures high success rate
Information Processing Advantage:
NIH: 200 reviewers ร 40 hours/week ร 50 weeks = 400,000 decision-hours/year
DIH: 280M participants ร 0.1 hours/year = 28,000,000 decision-hours/year
Advantage: 70x more brain power
Historical Proof This Works
Wikipedia vs Encyclopedia Britannica
- Britannica: Expert committees, 32 volumes, $1,400
- Wikipedia: Crowd wisdom, infinite content, free
- Winner: Wikipedia (by knockout)
Linux vs Windows Server
- Windows: Central planning by Microsoft committees
- Linux: Decentralized development by thousands
- Winner: Linux runs 96.3% of top servers
Prediction Markets vs Expert Polls
- Iowa Electronic Markets beat polls in 74% of elections
- Corporate prediction markets beat executive forecasts by 25%
- Sports betting markets beat ESPN experts consistently
What DIH Markets Fund vs NIH Committees
NIH Funds:
- Safe, incremental research
- Whateverโs politically popular
- Big institutions with lobbyists
- 2% of rare diseases
DIH Markets Fund:
- High-risk, high-reward moonshots
- Whatever might actually work
- Anyone with good ideas
- 100% of diseases with willing patients
Expected Returns
Conservative Estimate:
- 25% better allocation efficiency
- $27B annual budget (1% of military)
- = $6.75B additional value created annually
Realistic Estimate:
- 50% better allocation (markets typically beat committees by this much)
- = $13.5B additional value created annually
Optimistic but Possible:
- 2x better allocation (like Wikipedia vs Britannica)
- = $27B additional value created annually
Why Committee Members Hate This
Markets make their expertise worthless. No more:
- Playing god with billions
- Getting wined and dined by lobbyists
- Prestigious committee positions
- Power without accountability
Markets donโt give a shit about your PhD or your connections. They only care if youโre right.
The Network Effect
Markets get smarter over time.
Year 1: 1 million participants โ decent predictions Year 5: 50 million participants โ better than any committee Year 10: 280 million participants โ approaching optimal allocation
Every new participant adds information. Every bet refines predictions. Every outcome teaches the system.
The NIH stays equally dumb forever. Markets get exponentially smarter.
Bottom Line
NIH: 200 bureaucrats spending $48B based on politics and prestige. DIH: 280 million people allocating $27B based on results and skin in the game.
One of these systems put humans on the moon and created the internet. The other created Soviet bread lines.
Choose wisely. Or better yet, let markets choose.