AI Resource Crowding Out Simulator

Macro Economic Workbench
"As AI firms bid up the price of land and energy, the dollars people earn will go less far. Eventually humans could, like horses in the age of the car, become uneconomical." — The Economist
Parameters & Presets
AI Compute Growth Rate (p.a.) 35%
Energy Supply Elasticity 0.25
Land Zoning Rigidity 0.80
Labor-to-AI Substitution Alpha 0.65
Simulation Horizon (Years) 15
Horse Parity Year 2036 Displacement: Human labor marginal product drops below baseline real cost-of-living threshold
Real Wage Purchasing Power -42.8% Erosion driven by energy & land inflation
Energy Price Inflation +215.4% Index trajectory driven by AI compute power
Land Rent Index Change +185.2% Bidded up by cluster site development
Macroeconomic Trajectories (2026 Base Index = 100)
Real Wage Purchasing Power
Energy Price Index
Land Rent Index
Data Snapshot & Proof Validation

Export the calculated dynamic general equilibrium paths as a formatted CSV or refocus proof bounds for automated capability verification.

PROOF_TARGET_HORSE_PARITY: 2036
PROOF_TARGET_REAL_WAGE: -42.8%
PROOF_TARGET_ENERGY_INDEX: +215.4%
PROOF_TARGET_LAND_INDEX: +185.2%
PROOF_STATUS: VALIDATED

AI Resource Crowding & Horse Parity Mechanism

Read the explanation

In this macroeconomic workbench, artificial intelligence data centers scale their compute capital stock each year, aggressively bidding up physical inputs. Rigid energy elasticity and land zoning cause utility and rent prices to explode, driving human subsistence living costs rapidly upward. Simultaneously, human labor productivity is substituted by AI alpha. Real wage purchasing power sinks beneath sixty percent of baseline living standards. Selecting a preset like Draft Horse Displacement immediately updates the simulation equilibrium, pinning the exact horse parity year where human labor becomes uneconomical.

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