Western
Governance Model
Decentralized • 3-5 year response
Switch to China for comparison
60%
Gap Closure (Best Case)
Critical: 15/25 challenges unaddressed
⚠️ Worse under accelerated scenarios
80%
Occupations at Risk
Within 2 years
⚠️ 60-80% possible in months
3-5
Response Lag (Current)
Years vs quarterly AI deployment
⚠️ Insufficient for rapid disruption
$200B+
Economic Impact
Catastrophic scenarios
⚠️ $5T+ possible in 0-2 years
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Critical Risk Assessment

POLICY INSUFFICIENCY: Current governance frameworks WILL NOT prevent catastrophic economic disruption under accelerated automation scenarios. Most forecasts don't account for LLM+agent breakthroughs that bypass human-in-the-loop limits.
TECHNICAL REALITY: 60-80% automation could occur in months if market/legal barriers lift. No historical precedent exists for self-improving software with infinite scalability.
RECOMMENDATION: All "moderate adjustment" policy responses must be stress-tested against maximal scenarios. Stakeholders should plan for speeds and scope beyond precedent.
🔥

Maximal Automation Scenario

70% labor automation in 0-2 years driven by API-scale LLM agents with vertical integration. Triggers: Major firms pivot to automation, legal greenlight, no-fault layoffs, rapid plugin adoption. Outcome: "System phase shift" not gradual S-curve; cascading supply chain reorganization. Effects visible in weeks, not years.
Scenario AI Growth Policy Lag Displacement Description
Baseline15%/yr3-5 yrs25-45%Mainstream scenario
Accelerated30%/yr5-7 yrs30-46%Plausible scale-up
Breakthrough60-100%/yr7-10 yrs35-50%Deployment cascade
Maximal100%+/yr0-6 months60-80%Full automation trigger
Disclaimer: Probabilities or scenario frequency bands are for scenario comparison, not predictive risk quantification. Because modern AI agent deployment operates outside historical precedent, risk should be assessed as a range of plausible futures.
📊 Explore Interactive Data Visualizations Below

Critical Regulatory Gaps by Domain

Employment Disruption Cascade

Dynamic Scenario Risk Assessment

Scenario probabilities and impacts adjust based on selected parameters

Policy Response Timeline

AI Deployment
Quarterly
Policy Response
3-5 Years
Critical Gap: 24-36 month uncontrolled disruption window before government response mechanisms activate.

Policy Implications & Recommendations

🇺🇸 Western Policy Priorities

Response Speed: Adopt China's 6-18 month policy cycle through emergency regulatory pathways and pre-authorized frameworks.
Coordination: Establish executive authority for AI governance similar to China's State Council model, bypassing legislative gridlock.
Workforce Transition: Implement state-coordinated retraining programs with guaranteed income support during transition periods.

🇨🇳 China Policy Priorities

Independent Oversight: Strengthen independent regulatory bodies and public accountability mechanisms to complement centralized coordination.
Innovation Balance: Maintain rapid deployment capability while adding Western-style safety reviews and ethical frameworks.
International Cooperation: Lead global AI governance standards while incorporating diverse stakeholder perspectives.

Cross-System Recommendations

Hybrid Approach: Combine China's speed with Western oversight. Adopt centralized coordination for rapid response while maintaining independent safety reviews and democratic accountability. This balanced approach optimizes both effectiveness and legitimacy.