About — AI Civilization Simulator

01

What Is This

An open simulation framework for reasoning about the interconnected systems that determine civilizational outcomes over generational timescales.

Scope

The simulator models six interconnected dimensions of civilizational health: climate resilience, institutional governance, workforce readiness, systemic equity, technology alignment, and collective wellbeing. Each dimension is tracked as a scored "operating system" with its own KPIs, projections, and scenario responses.

Intent

This is a planning tool, not a prediction engine. It provides a structured framework for exploring how policy decisions compound over decades. Projections are modeled and simulated; baselines are grounded in live measurements pulled from public scientific APIs (see Live Data). The site is entirely static—all computation, including the live fetches, happens client-side in your browser.

6

Operating Systems

Each OS models one dimension: climate, governance, workforce, civilization (aggregate), strategy, and transition planning. Changes in one propagate through interconnected feedback loops.

4

Scenarios

Four divergent scenarios vary the core policy levers and assumptions. Toggle between Aggressive Action, Moderate Reform, Business as Usual, and Worst Case to see different futures.

50

Year Horizon

Projections span 2025 through 2075. Data visualizations show 10-to-50-year trajectories with decade markers. All timelines are synchronized across operating systems.

8

Live Data Feeds

Real-world baselines — CO₂, warming, renewables, emissions, methane, sea ice, poverty, unemployment — fetched in your browser from NOAA, Our World in Data, and the World Bank. Still no servers, no databases, no tracking. Projections remain modeled. See the live data →

System Interconnections

The six operating systems do not model their domains in isolation. Climate stress reduces workforce readiness. Governance failures amplify equity gaps. Technology misalignment erodes institutional trust. The simulator tracks these cross-domain feedback loops to produce more realistic composite trajectories.

Scenario Mechanics

Each scenario adjusts three primary policy levers—civic dividend rates, AI governance charter adoption, and climate investment as a share of GDP. Secondary effects cascade through the model: higher civic dividends reduce inequality, which increases institutional trust, which accelerates governance reform adoption. To see the gap between any two scenarios made explicit—lever deltas, which of the 20 catalog actions change status, and where the trajectories fork—see Pathways.

The simulation uses scenario modeling with adjustable policy lever inputs. Trajectories are generated deterministically—the same inputs always produce the same outputs. The model is transparent and auditable.

Policy Levers

Civic Dividend Rate

0–12%

AI Governance Charters

0–100%

Climate Investment Share

0–8% GDP

Tracked Trajectories

GINI Inequality

rising

Civic Trust Index

declining

Emissions (GtCO2)

increasing

Systemic Resilience

eroding

AI Influence Score

expanding

Key Performance Indicators

Poverty Rate

target < 5%

Average Reskill Time

target < 6 months

Peak Emissions Year

target 2030

Biodiversity Corridors

target 30% coverage

AI Audit Coverage

target 95%

Funding Model Reference

The civic dividend mechanism modeled in the simulator is structurally based on the Alaska Permanent Fund—a sovereign wealth fund that distributes resource revenues directly to citizens. The simulation extends this model to AI-generated productivity gains, testing different distribution rates and their downstream effects on inequality, trust, and workforce adaptation.

Original Build

Framework

Next.js 14

UI Library

React 18

Language

TypeScript

Styling

Tailwind CSS 3

Current Build

Framework

Static HTML

Scripting

Vanilla JS

Charts

SVG (hand-rolled)

Build Step

None

Display

Space Grotesk

Headings, section titles

Body

Inter

Labels, annotations, prose

Data

JetBrains Mono

Numerals, scores, code

Design follows the Feltron editorial data-report tradition: dark backgrounds, systematic typography hierarchy, 12-column grid, data as the primary visual element. No decorative imagery. No emojis. Information density is the aesthetic.

Project

Clawcode Research, 2026

An open simulation framework for modeling civilizational health across interconnected systems.

Links

GitHub → Simulator Home →

Design language inspired by Nicholas Felton's Annual Reports (2005–2014). The Feltron reports pioneered the use of personal data as narrative medium—systematic typography, editorial grids, and quantified observation. This project applies the same principles to civilizational-scale simulation data.