AI Ownership - Countries

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The Coordination Dilemma

The distribution of AI capabilities among nations creates a classic coordination dilemma analyzed in the international coordination game.

Game-Theoretic Dynamics

Game-theoretic modeling shows that defection (racing) mathematically dominates cooperation when actors believe cooperation probability falls below 50%—a threshold currently unmet in US-China relations. This creates multipolar trap dynamics where rational actors pursuing individual interests produce collectively catastrophic outcomes.

Both superpowers are "turbo-charging development with almost no guardrails" because neither wants to slow down first.

Why Geographic Concentration Matters for Safety

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Mechanisms

Mechanism	Effect	Example
First-mover pressure	Reduces safety investment	Winner-take-all competition
Export controls	Strains cooperation	US semiconductor restrictions
Coordination failure	Enables racing	No binding agreements

Current International Landscape

Coordination Mechanisms

Initiative	Scope	Budget	Effectiveness
AI Safety Institute network	11 countries	~$150M combined	Emerging
Council of Europe AI Treaty	14 signatories	N/A	First binding agreement
US-China bilateral dialogues	2 countries	N/A	Limited by competition
Private sector investment	Global	$100B+ annually	Dwarfs public efforts

Key Uncertainties

Question	Possible Answers
Do US-China dynamics inevitably tend toward confrontation?	Confrontation vs. cooperation through mutual catastrophic risk awareness
Do democratic nations maintain structural advantages?	Innovation ecosystem vs. state-directed focus
Can alternative power centers influence trajectory?	EU, UK, emerging economies as third pole vs. bipolar lock-in

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What Drives Country AI Distribution?

Causal factors affecting national AI capabilities. 94% of AI funding in US; US-China competition dominates.

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Scenarios Influenced

Scenario	Effect	Strength
AI Takeover	—	weak
Human-Caused Catastrophe	—	weak
Long-term Lock-in	↑ Increases	strong